Author: Richard Johnston

Recently while reviewing PFT reports I ran across a test from a patient who had been having spirometry, lung volume and DLCO tests performed at regular intervals for the last several years. Compared to the last several set of tests the most recent DLCO had decreased significantly while the FVC, FEV1 and TLC hadn’t changed. I took a closer look at the raw data from the DLCO test and when I did I saw that the washout volume was not correct.

Or more correctly, even though the washout volume matched the ATS/ERS standard for DLCO testing it was evident the expiratory gas sample was not taken from the alveolar plateau. The CO and CH4 concentrations at this point in the exhalation are higher than they are in the alveolar plateau and this means the reported DLCO was underestimated.

When I re-adjusted the washout so the gas sample was taken from the alveolar plateau, the DLCO went from 18.56 ml/min/mmHg to 22.26 ml/min/mmHg, which is a 20% increase and far more in line with the patient’s prior DLCO test results.

This, however, increased the washout volume from 0.75 L to 1.34 L. Why was the washout volume so high? The answer is it probably wasn’t.

Our DLCO test systems use a real-time gas analyzer. In this kind of test system the gas analyzer signals are delayed because of the length of time it takes a gas sample to transit the sample line and then for the gas analyzer to respond. This time delay is measured during a calibration and is used to match the volume and gas analyzer signals.

The patient exhaled quite forcibly after the breath-holding period and by analyzing the graph I was able to see the expiratory flow rate during the washout period was about 12 L/sec. The entire sample volume was therefore exhaled in approximately 60 milliseconds and the difference between an alveolar sample beginning at 0.75 L and at 1.34 L is about 50 milliseconds.

When I looked at our calibration records I found that depending on the test system in question transit delays ranged from about 300 to 800 milliseconds. I also found that the difference in delay time from one calibration to the next was usually at least 20 milliseconds and often more. This happens even when two calibrations are done back-to-back which means there are limits to the accuracy of the delay time measurement. At the patient’s high exhaled flow-rate even small errors in the delay time determined during calibration can lead to relatively large mismatches between exhaled volume and the exhaled gas concentrations. It also means that the patient’s true washout volume probably wasn’t as high as it was reported.

The ATS/ERS Statement on DLCO testing currently recommends:

Vital Capacity (L):	Washout (L):	Alveolar Sample (L):
>2.00 L	0.75 to 1.00	0.50 to 1.00
>1.00 and <2.00	0.50	0.50
<1.00	0.50	<0.50

Washout volume, like some of the other aspects of the single-breath DLCO test, was originally a somewhat arbitrary decision made by the authors of the first standardized procedure for DLCO. Their 1957 paper advocated the use of a 0.75 L washout volume and for them this was a balance between being confident that the subject’s dead space was completely washed out while still being able to acquire an adequate sample volume in less than 3 to 4 seconds.

This decision was based in technology that was available at that time. Prior to the 1990’s almost all carbon monoxide gas and tracer gas analyzers analyzers had relatively slow response times and it was necessary for a single, discrete sample of alveolar gas to be collected for analysis. This meant that the washout volume and sample volume had to be set before a single breath DLCO test was performed. The ATS/ERS standards for washout and sample volume originate in the requirements of these kinds of analyzers.

Since that time, real-time gas analyzers for CO and CH4 have become relatively standard. With these analyzers it is possible to directly view the exhaled gas waveforms of a single-breath DLCO test and to be able to determine when washout of dead space gas has occurred. For this reason the need to strictly hew to the ATS/ERS recommendations has become much less necessary.

The ATS-ERS recommendations are just that, recommendations. At least one research study showed that a washout volume of 0.75 liter may be inadequate in up to a half of the patients tested and further, that even a washout of 1.0 liter may be inadequate in approximately a quarter of the patients tested. Although the average difference was small, in approximately 10 percent of the patients increasing the washout volume above 1.0 liter increased the measured DLCO significantly primarily because the alveolar sample contained less dead space gas.

For all these reasons it is important to inspect the exhaled gas waveforms to determine where the alveolar plateau is located and then manually select the correct washout volume even if it doesn’t meet the ATS/ERS standards. This is necessary not only because default settings don’t work for every patient but also because our testing hardware and software isn’t perfect and errors are not uncommon.

That’s not to say that finding the alveolar plateau or selecting a washout volume is always easy. A patient with severe COPD often has a marked ventilation inhomogeneity and this often appears as the lack of a clearly defined alveolar plateau.

The two different sample windows both meet ATS-ERS criteria but each produces different CH4, CO and BHT times. Because calculated alveolar volume (VA) depends on the average tracer gas (CH4) value in the sample volume, it can be seen that a leftward shift in the sample window increases the average CH4 whereas a rightwards shift decreases it. Since the calculated VA is inversely related to the change in CH4, a leftward shift decreases the calculated VA, a rightwards shift increases it. By the same token, a leftward shift in the sample window decreases breath-hold time (BHT) and a rightwards shift increases it. In this example there was a 7% increase in BHT and a 7% increase in alveolar volume from the left to the right sample windows. Although VA and BHT to some extent cancel each other out there is still a 5% difference between DLCO calculated with the different sample windows.

Which washout volume is correct? The answer is both and neither, and this highlights one of the limitations of the single-breath DLCO test. The problem in this example is that the inhaled gas mixture is maldistributed and a relatively small sample of exhaled gas is unable to represent the lung as a whole.

The need to match gas analyzer and volume signals that are out of synch with each other is necessary in real-time DLCO test systems (and most CPET systems). In order to match these signals the time delay caused by the transit of gas through a sampling line and the response time of gas analyzers must be determined with a high level of accuracy. It’s not clear to me however, what level of accuracy is possible when delay times are measured.

In most systems a test gas is switched off and on with a solenoid valve and the time it takes the gas analyzers to respond is used to determine the transit time. There are at least two factors that affect this measurement, the most important of which is the rise time of the gas analyzer. No gas analyzer responds instantaneously and this is due to the internal volume of the sensor and the electronic amplifiers of the gas analyzer. Gas analyzers are usually characterized by the length of time it takes to reach 90% of the maximum signal and the delay time measurement must somehow take this response curve into consideration.

Another factor is the smearing that gas samples undergo as they travel through a sampling line. This is because gas flow has a parabolic cross-section (i.e. gas flow is slowest near the wall of the sample line and fastest in the center) and means that an abrupt change in gas concentration at one end of a sampling line becomes a more gradual change as it passes through the line.

Both of these factors cause a certain level of indeterminacy when the transit delay time is measured. When signals are changing rapidly even minor discrepancies in the measured transit time can cause a mismatch between different signals. Whether or not this mismatch is significant depends a lot on the specific test. In this case the only apparent problem was a washout volume that was likely mis-calculated.

Everybody that performs and reviews DLCO tests should be aware of the issues surrounding the washout volume. Manufacturers usually default to the ATS/ERS standards, but these standards are recommendations, not requirements. Since washout volume is not factor in the DLCO calculation what matters is that the exhaled gas sample comes from the alveolar plateau and staff should feel able to adjust the washout volume in whatever way is necessary to achieve this goal.

References:

Brusasco V, Crapo R, Viegi G editors. ATS/ERS Task Force: Standardization of Lung Function Testing. Standardization of the single-breath determination of carbon monoxide uptake in the lung. Eur Resp J 2005; 26:720-735

Graham BL, Mink JT, Cotton DJ. Overestimation of the Single-Breath Carbon Monoxide Diffusing Capacity in Patients with Air-Flow Obstruction. Am Rev Resp Dis 1984; 129:403-408

Huang YCT, MacIntyre NR. Real-Time Gas Analysis Improves the Measurement of Single-breath Diffusing Capacity. Am Rev Resp Dis 1992; 146: 946-950

Ogilvie CM, Forster RE, Blakemore WS, Morton JW. A standardized breath holding technique for the clinical measurement of the diffusing capacity of the lung for carbon monoxide. J Clin Invest 1957; 36: 1-17.

Prediletto R, Fornai E, Catapano G, Carli C. Assessment of the alveolar volume when sampling exhaled gas at different expired volumes in the single breath diffusion test. BMC Pulmonary Medicine 2007; 7:18

PFT Blog by Richard Johnston is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

I’ve been reviewing my CPET textbooks trying to get a better idea of how to differentiate between different cardiovascular limitations. The other day I ran across an article on a related subject and thought it might be instructive.

The hallmark of cardiovascular limitations is the inability to deliver enough oxygenated blood to the exercising muscles. Another limitation that has similarities to this (and one that is infrequently diagnosed) is the inability of the exercising muscle to utilize the oxygen delivered to it. The best examples of this type of exercise limitation are mitochondrial myopathies (MM).

The mitochondria are the primary source of the ATP used by exercising muscle. There are several conditions that can cause the number of mitochondria to be reduced and there is wide variety of mitochondrial genetic defects. Mitochondria have their own genes and these can have both inherited or acquired genetic defects which can cause anything from mild to severe decreases in the ability to produce ATP. Mitochondria require oxygen to produce ATP so when the number of mitochondria are reduced or their ability to produce ATP is reduced the rate at which oxygen is consumed by an exercising muscle is also reduced.

A relatively common complaint of individuals with MM is dyspnea and exercise intolerance. One study found that 8.5% of all the patients referred to a dyspnea clinic had a mitochondrial myopathy of one kind or another. A definitive diagnosis requires a muscle biopsy but because the symptoms are often non-specific and a biopsy is an invasive procedure, it is usually not performed unless there more significant evidence suggesting a MM.

In general MM affects the ability of muscles to exercise and this includes respiratory muscles. For this reason maximal inspiratory and expiratory pressures are often reduced. Since the MVV also depends on the respiratory muscles this is usually reduced as well. Unless the MM is severe however, spirometry, lung volumes and DLCO tend to be normal. A CPET is able to provide a lot more evidence but results must be analyzed carefully.

First, and perhaps most obviously, the most common CPET finding is that the maximum oxygen consumption expressed either as ml/kg/min or as percent predicted is reduced. Because the maximum heart rate is usually normal this means first that the slope of the heart rate-VO2 response will be elevated. This is the chronotropic index and is calculated as:

A chronotropic index above 1.30 indicates that the heart rate is advancing faster than it should and subjects with a MM will likely have a value at or above this threshold.

Blood lactate is occasionally elevated at rest and usually elevated post-exercise. Even when post-exercise lactate levels are within normal limits the lactate/max VO2 ratio is well above normal. Because lactic acid and carbon dioxide production are usually elevated early during exercise individuals have a hyper-ventilatory response. Ventilation is in particular elevated relative to VO2 which means that the Ve/VO2 will be elevated likely throughout exercise.

Ve/VCO2 is also usually elevated and the maximum PETCO2 is usually reduced. RER can occasionally be markedly elevated at peak exercise but this will depend on the willingness and ability of the individual to exercise to a maximal level. Interestingly, the evidence about Vd/Vt is equivocal with both normal and elevated values reported.

Despite the overall hyperventilatory response the maximum minute ventilation is usually reduced. This is partly because the maximum VO2 is usually reduced and partly because of respiratory muscle weakness.

Because the exercising muscles do not extract as much oxygen as they should, the arterial-venous O2 content difference does not decrease and in fact the venous blood can have an elevated PO2. Poor oxygen extraction by the exercising muscle has much the same effect as poor oxygen delivery. For this reason anaerobic threshold usually occurs early both in terms of workload and in terms of oxygen consumption. For the same reason the VO2-Work Rate relationship is often abnormal and tends to show patterns similar to subjects with cardiac disease.

A handful of studies have measured cardiac output in individuals with MM, either by the acetylene rebreathing method or by the Fick equation utilizing PaO2 and PvO2. When this has been done subjects with MM have shown a normal maximum cardiac output but a cardiac output/VO2 ratio that is markedly elevated relative to normal individuals.  The blood pressure response is also usually normal.

There are still a number of open questions for me because there are some CPET results that have the potential to be diagnostic for MM but do not appear to have been studied. One of these is the O2 pulse pattern. Because the maximum VO2 is reduced but the maximum heart rate is normal this also means that the maximum O2 pulse will be reduced.

O2 pulse can be used as an index of stroke volume but it does not correspond exactly since it also depends on the O2 content difference between arterial and venous blood. Stroke volume tends to reach its maximum relatively early during exercise but O2 pulse usually continues to rise throughout exercise and reaches a maximum at peak exercise. The difference in patterns between stroke volume and O2 pulse is because more oxygen is extracted from arterial blood and the arterial-venous O2 content difference increases.

But because the arterial-venous O2 content difference in MM remains low, this would imply that the O2 pulse should plateau early. Several studies have stated that the maximum O2 pulse is low, but none of them have discussed the O2 pulse pattern during a CPET so the presence of a plateau is unclear.

Additionally, most studies of CPETs in patients with MM have discussed the elevated Ve/VO2 but only a few have even mentioned Ve/VCO2 and then usually only at peak exercise. I would presume that because ventilation is elevated because of increased lactic acid as well as an increased VCO2 that the Ve-VCO2 slope would also be elevated but some confirmation of this would be appreciated.

CPET results on an individual with a mitochondrial myopathy usually show:

• reduced maximum VO2
• elevated Ve/VO2
• early Anaerobic threshold
• elevated RER
• normal maximum heart rate
• elevated chronotropic index
• reduced PETCO2
• normal blood pressure

This pattern however, is similar to individuals with a cardiovascular limitation. The primary differences between a mitochondrial myopathy and a cardiac limitation are:

• normal cardiac output
• reduced arterial-venous O2 content difference
• elevated blood lactate

and these values can only be measured either invasively or with specialized testing equipment. Routine CPET results can therefore lead you to suspect a mitochondrial myopathy, but cannot be definitive.

There is a spectrum of mitochondrial disorders. Depending on the specific defect an individual may exhibit some or all of the limitations noted here. The studies that have assessed the exercise response in individuals with mitochondrial myopathies are occasionally contradictory and this is probably due to differences in specific mitochondrial defects contained within their study populations.

Taken individually, the limitations are somewhat non-specific. Although MIP, MEP and MVV tend to be reduced, pulmonary function results are usually normal. The overall CPET pattern is similar to individuals with a low cardiac output secondary to cardiac disease with the major exception that cardiac output is normal. Because of this, individuals that show this overall pattern without any sign of cardiac disease should at least be considered for a mitochondrial myopathy.

Update:

A primarily cardiovascular limitation to exercise is discussed at greater length in How does a CPET show a cardiac limitation? 

References:

Clay AS, Behnia M, Brown KK. Mitochondrial disease. A pulmonary and critical-care medicine perspective. Chest 2001; 120: 634-648.

Dandurand RJ, Matthews PM, Arnold DL, Eidelman. Mitochondrial disease. Pulmonary function, exercise performance and lactate levels. Chest 1995; 108: 182-189.

Flaherty KR, Wald J, Weisman IM, Zeballos RJ, Schork MA, Blaivas M, Rubenfire M, Martinez FJ. Unexplained exertional limitation. Characterization of patients with a mitochondrial myopathy. Am J Respir Crit Care Med 2001; 164: 425-432.

Haller RG, Lewis SF, Estabrook RW, DiMauro S, Servidei S, Foster DW. Exercise intolerance, lactic acidosis, and abnormal cardiopulmonary redulation associated with adult skeletal muscle cytochrome c oxidase deficiency. J Clin Invest 1986; 84: 155-161.

Taivassalo T, Abbot A, Wyrick P, Haller RG. Venous oxygen levels during aerobic forearm exercise: An index of impaired oxidative metabolism in mitochondrial myopathy. Ann Neurol 2002; 51: 38-44.

Taivassalo T, Jensen TD, Kennaway N, DiMauro S, Vissing J, Haller RG. The spectrum of exercise tolerance in mitochondrial myopathies: a study of 40 patients. Brain 2003; 126: 413-423.

PFT Blog by Richard Johnston is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Obesity has become far more commonplace than it was a generation ago. The reasons for this are unclear and have been attributed at one time or another to hormone-mimicking chemicals in our environment, altered gut biomes, sedentary lifestyles or the easy availability of high calorie foods. Whatever the cause, obesity affects lung function through a variety of mechanisms although not always in a predictable manner.

Spirometry:

Many investigators have shown a relatively linear relationship between an increase in BMI and decreases in FVC and FEV1. These decreases are small however, and FVC and FEV1 tend to remain within normal limits even in extreme obesity. The decreases in FEV1 and FVC tend to be symmetrical which is shown by the fact that the FEV1/FVC ratio is usually preserved in obese subjects without lung disease. Several studies have shown that the decreases in FVC and FEV1 are reversible since a decrease in weight showed a corresponding increase in FVC and FEV1.

In one study a 1 kg increase in weight correlated with a decrease in FEV1 of approximately 13 ml in males and 5 ml in females. The same increase in weight correlated with a decrease in FVC of approximately 21 ml in males and 6.5 ml in females. The greater change in FVC and FEV1 in males than females has been attributed to the fact that males tend to accumulate extra weight primarily in the abdomen.

The notion that abdominal weight has a disproportionate effect on lung function is seconded to some extent by studies that have shown that decreases in FVC and FEV1 correlated better with increases in waist circumference and the waist to hip ratio than with BMI. One study showed a 1 cm increase in waist circumference caused a 13 ml reduction in FVC and an 11 ml reduction in FEV1 across a range of elevated BMI’s.

Expiratory and inspiratory flow rates (PEF, MEF50, PIF and MIF50) and MVV also decrease relatively linearly with increasing BMI, although for different reasons. Decreases in expiratory flows are most likely caused when a decreased FVC causes flows to move to a lower position on the maximal flow-volume curve. Inspiratory flow rates are limited by an increase in the mass that must be moved during inspiration.

Despite the increase in abdominal girth with increasing BMI there is no significant difference in FVC and FEV1 between sitting and standing.

Lung Volumes:

There is also a relatively linear association between an increase in BMI and decreases in TLC and RV, however they also usually remain within normal limits and the RV/TLC ratio is preserved even in morbidly obese individuals. FRC and ERV however, show exponential decreases with increasing BMI so that even mildly overweight individuals can show noticeable changes. Morbidly obese individuals frequently show a maximal decrease in ERV and FRC and in these individuals FRC is usually not significantly different from RV. These lung volume changes are attributed to the increased body mass which causes an extra loading on the thorax, marked increases the intra-abdominal pressure and impedes movement of the diaphragm. In general this means that RV tends to be preserved and FRC and ERV decrease as BMI increases. The changes in lung volumes are reversible since several studies have shown that when weight decreases TLC, FRC and ERV increase.

One study showed a 30 ml decrease in FRC per kilogram increase in weight for males and a 20 ml decrease in FRC per kilogram increase in females. The investigators attributed the difference between the genders to the fact that central (abdominal) obesity is more common in males than females and in fact several studies have shown that decreases in FRC and ERV correlate better with waist circumference and the waist to hip ratio (which tend to be lower in females) than they do to BMI.

FRC and ERV tends decrease even further in the supine position. Several investigators have shown that when this happens it is likely accompanied by an increase in regional gas trapping since the Closing Volume may exceed the ERV and occur above FRC in the supine position. This may be why many obese subjects report increased dyspnea in the supine position.

Although decreases in FVC, FEV1 and ERV are generally associated with obesity, determining the effect on a specific individual is often less precise. One study of obese individuals showed that individuals with a low MVV also tended to have larger decreases in FVC, FEV1, ERV, IC and TLC than did subjects with a normal MVV and that this did not correlate with BMI. Individuals with a low MVV also had lower inspiratory and expiratory flow rates, a decrease in respiratory muscle strength and a higher RV/TLC ratio. This pattern would seem to show that a decrease in MVV is a symptom, not a cause, of the difference in lung function between the two groups.

N2 washout time and helium wash-in time may be increased during lung volume measurements in obese subjects because of poor ventilation in the dependent lung units but this is primarily seen in patients with obesity hypoventilation syndrome and a low PaO2. One study showed data indicating a slightly higher TLC measured by plethysmography than by helium dilution which was attributed to gas trapping. It’s unclear that this is the case since after weight loss the same study showed that plethysmographic TLC increased more than helium dilution TLC.

DLCO:

There is a great deal of conflicting evidence about obesity’s effect on DLCO. At least one retrospective study showed no significant correlation between BMI and either DLCO or KCO and another study showed no difference in DLCO before and after significant weight loss. Numerous other studies however, have shown that in individuals without evident lung disease DLCO was usually reduced in obesity and the decrease correlated with increasing BMI. Where noted this has been attributed this obesity related atelectasis.

Other investigators have shown that DLCO increases with increasing BMI. This has usually been attributed to an increased resting VO2 which causes an increased cardiac output and pulmonary capillary blood volume. In a large population study of individuals with an elevated DLCO there was a high correlation with an elevated BMI and another study showed that DLCO decreased during weight loss.

Regardless of whether they’ve shown that DLCO increases or decreases most investigators have noted an increase in DLCO/VA (KCO) that correlates with increasing obesity. The discrepancy between these different observations may be related to alveolar volume since one study noted that when alveolar volume was preserved DLCO tended to be elevated and when VA was decreased, DLCO was reduced. Another study noted that DLCO tended to be lower with increasing BMI in men than women and attributed this to women having a lower waist-to-hip ratio. This could well be the case, however the differences in DLCO based on waist-to-hip ratios in males has not been explored.

Exercise:

Numerous studies have shown that VO2, VCO2 and Ve are higher at rest in obese individuals than in those with a normal weight. VO2 and VCO2 are also higher for any given workload than for subjects with a normal body weight. The rate of increase in VO2 with increasing workload in obese subjects tends to be the same as for normal weight subjects but is shifted upwards which means that the maximum workload tends to be reduced and that maximum VO2 will be reached in a shorter period of time. Minute ventilation tends to increase faster with exercise in obese subjects which leads to an increased Ve/VO2 at any workload. The Ve-VCO2 slope however is usually normal. Anaerobic threshold usually occurs at a lower workload but the VO2 in LPM at AT is usually normal. Peak VO2 when expressed as ml/kg/min is usually reduced but in LPM it is also usually normal. SpO2 is usually normal.

Work of breathing:

The work of breathing increases with increasing body weight. This is attributed both to the increase in mass and to the fact that when FRC decreases, tidal breathing occurs at a less efficient portion of the pressure-volume curve of the lung. In addition when breathing at low lung volumes expiratory flow may encroach on the maximal flow volume loop envelope which increases the likelihood of expiratory flow limitation. Total respiratory compliance has been shown to decrease significantly and RAW to increase significantly during tidal breathing in obese subjects. The decrease in compliance has been primarily attributed to a decrease in chest-wall compliance from an increase in fat in and around the ribs, diaphragm and abdomen. The increase in RAW has been attributed to airway narrowing from an FRC that is closer to RV than in normal-weight subjects. These effects are reversible since several studies have shown that RAW decreases and SGaw increases after weight loss.

There is a relatively linear relationship between increases in RAW, decreases in SGaw and increases in BMI although these tend to be greater in males than in females. Like other lung function values this is attributed to a greater amount of abdominal obesity in males compared to females.

Asthma:

Although a number of studies have shown an association between asthma and obesity at least one study showed that even though wheezing increased with a longitudinal increase in body weight the presence of asthma as defined by an increase in FENO did not. This is seconded to some extent by the general finding that a decreased FEV1/FVC ratio is not associated with obesity and that a decrease in weight does not decrease airway reactivity as judged by methacholine responsiveness.

One study showed that obese asthmatics had a larger increase in FRC and ERV, and a larger decrease in IC during methacholine-induced bronchoconstriction than did individuals with a normal BMI. A closer look at their data however, showed that prior to bronchoconstriction their most obese cohort (BMI>30) had normal FRCs and elevated ERVs which is more than somewhat contrary to effects on lung volume that are usually associated with obesity. Other studies of obese asthmatics have shown the expected decreases in FRC and ERV so it is unclear the results from this study are actually representative.

COPD:

Interestingly, the effects of obesity tend to act in opposition to some of the effects from COPD. An elevated FRC and a reduced IC (hyperinflation) are frequent consequences of severe COPD and studies have shown that FRC and IC decreased with an increasing BMI compared to subjects with a normal body weight when the FEV1 and FEV1/FVC ratio were the same.

Obesity also tends to counteract some of the effects of COPD during exercise. When compared to individuals with a normal weight individuals with COPD those with an elevated BMI had a lower TLC, a lower FRC and a higher IC. During exercise obese individuals with COPD were able to reach a higher maximum oxygen consumption and a higher Ve than their normal weight counterparts. Although at peak exercise both normal weight and obese individuals had similar levels of dynamic hyperinflation, this occurred at a significantly higher minute ventilation for the obese individuals.

Reference equations:

Although it is clear that obesity affects lung function body weight, BMI, BSA, waist circumference and waist to hip ratios are almost never factors in reference equations. In fact, studies often indicate that weight was not a statistically significant factor. This is likely due to the in which study populations are selected. Obese individuals are often excluded either explicitly or because they often have co-morbid factors. For this reason, despite the fact that obesity has become commonplace reference equations are usually based on a population with relatively normal body weights.

An interesting question would be whether reference equations should be re-factored to include a wider range of body weights. I don’t think they should and part of the reason for this is that when the effects of obesity are determined for a group the relationship between BMI and the value being studied are often statistically relevant but extending this relevance to a specific individual has frequently been shown to be problematic. Another reason is that even though it is possible to be overweight and healthy, obesity is not the normal default condition for humans and if reference equations include weight as a factor then results that should probably be considered abnormal may instead look normal.

 

Pulmonary function testing can be more challenging when the patient is obese. Patient chairs and wheelchairs may be tight and uncomfortable, plethysmographs may be too small and dyspnea can prevent the patient from cooperating fully with testing directions. Since obesity is encountered so frequently however, accommodations for these factors should be routine for any pulmonary function lab.

When pulmonary function reports are reviewed from an individual with an elevated BMI the FVC, FEV1, TLC, RV and DLCO are likely going to be within normal limits until obesity is extreme. This says something about the resilience of the human body but it also isn’t the same as saying there is no effect. Obese individuals are far more likely to complain of dyspnea. Sleep apnea, cor pulmonale, orthopnea, hypoxia and hypercapnia are some of the potential pulmonary consequences of obesity. Obesity can also exacerbate existing cardiovascular, pulmonary and metabolic disorders. The effects of obesity are not necessarily predictable however, and individuals with the same gender, age, height and BMI may can have substantially different pulmonary function results. Part of this may be due to differences in factors like waist circumference and waist to hip ratios but co-morbid conditions likely factor in this as well.

Since a decreased ERV is a relatively accurate indicator of the effect obesity has on lung volumes more than one investigator has proposed that the ERV and ERV/VC ratio can be obtained from just a Slow Vital Capacity maneuver. This is a simple and cost effective way of monitoring lung function and another reason that slow vital capacities should be performed as part of routine spirometry more often

References:

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Santana ANC, Souza R, Martins AP, Macedo F, Rascovski A, Salge JM. The effect of massive weight loss on pulmonary function of morbid obese patients. Respir Med 2006; 100: 1100-1104.

Saydain G, Beck KC, Decker PA, Cowl CT, Scanlon PD. Clinical significance of elevated diffusing capacity. Chest 2004; 125: 446-452.

Steir J, Lunt A, Hart N, Polkey MI, Moxham J. Observational study of the effect of obesity on lung volumes. Thorax 2014; 69: 752-759.

Sutherland TJT, Cowan JO, Taylor DR. Dynamic hyperinflation with bronchoconstriction. Differences between obese and nonobese women with asthma. Am J Respi Crit Care Med 2008; 177: 970-975.

Wasserman K, Hansen JE, Sue DY, Stringer WW, Whipp BJ. Principles of exercise testing and interpretation, Fourth edition. Lippincott, Williams & Wilkins, 2006.

Zahir M, Sharma P, Eneh K, Patolia S, Vadde R, Schmidt MF. Correlation of body mass index (BMI) with the diffusing capacity (DLCO) and the diffusing capacity adjusted for alveolar volume (DLCO/VA) in overweight adults: a retrospective analysis. Chest 2009; 136(4): 120S.

Zavorosky GS, Christou NV, Kim DJ, Carli F, Mayo NE. Preoperative gender difference in pulmonary gas exchange in morbidly obese subjects. Obes Surg 2008; 18: 1587-1598.

PFT Blog by Richard Johnston is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

I thought I was done with lung volume issues for at least a little while but a short time ago I was reviewing a report from another PFT lab and I ran across something that didn’t seem to make sense. What the report showed was a normal TLC (99% of predicted) with a normal VC (101% of predicted) but the RV was 70% of predicted.

When I took a closer look, it was evident that the predicted VC came from the NHANESIII study and the predicted TLC and RV came from the ERS 1993 Statement. In my PFT lab our equipment manufacturer made the decision to use the predicted RV from whatever source the end-user selected (which in our case is the ERS93 study as well) but to re-calculate the predicted TLC using the predicted FVC, again from whatever source the end-user selected (which in our case was also NHANESIII). What this means is that for my lab:

predicted TLC = predicted VC + predicted RV.

What I saw in the report however, was that the predicted TLC and RV came from the ERS93 study and the predicted VC came from NHANESIII but that meant that:

predicted TLC ≠ predicted VC + predicted RV.

In fact the predicted TLC was almost a half a liter less than if it had been calculated from the predicted RV and predicted VC. What I also saw was that:

predicted TLC ≠ predicted FRC + predicted IC

predicted RV ≠ predicted FRC – predicted ERV

Leaving aside the problems with IC and ERV, this discrepancy brings up some interesting questions. First, is it right to substitute the VC from a set of spirometry reference equations with the VC from a set of lung volume reference equations? Presumably manufacturers and PFT labs do this so there is no confusion about the predicted VC when a report has both spirometry and lung volume results. But the predicted TLC and RV were derived using the VC from the same set of reference equations, which means that if you’re going to insert a VC from a different set of reference equations and if you want everything to add up properly you’re going to have to re-calculate either the predicted TLC or the predicted RV and is that right?

If the predicted VC from the lung volume reference equations is kept (and it was about 8% less than the predicted VC from the NHANESIII reference equation for the individual in the report) then there is going to be a different percent predicted when the VC is the same as the FVC. This means that a VC that was mildly reduced in spirometry can be within normal limits in lung volumes and is that right?

Or, you can leave the predicted TLC and RV alone and plug in the predicted VC without altering anything, but that means that you can have a normal TLC and VC with an abnormal RV (the original problem) or even a normal RV and VC with an abnormal TLC and does that make sense?

[BTW, I still don’t have any idea where the predicted IC and ERV came from. They are different by a couple percent from those calculated from the original reference equations and no matter whether I use the VC from ERS93 or NHANESIII they still don’t add up so at this point I remain somewhat baffled.]

In one sense this is a reference equation problem and is exacerbated by the fact that there are relatively few lung volume reference equations to choose from and all of them are derived from relatively small populations. When I reviewed James Hansen’s textbook on Pulmonary Function testing, he felt there were only three sets of reference equations that are in common use. Of these studies, the largest had 627 participants (Gutierrez et al, plethysmography), the smallest had 176 (ERS93, helium dilution) and the middle one had 245 (Crapo, single breath helium dilution). Compare these to 3975 participants in the NHANESIII study and 74,187 in the GLI Study.

So, the final question is should reference equations be mixed at all? The ATS/ERS standards are mute on this issue so there are no guidelines, which leaves it in the hands of equipment manufacturers and end-users. I think the most important point is that the sub-volumes should always add up properly (i.e., TLC = VC + RV, TLC = FRC + IC and RV = FRC – ERV) and for me this is pretty much non-negotiable. That leaves only two alternatives:

• Leave the original reference equations for lung volumes alone and accept the fact that the predicted FVC and VC are going to be different. On the minus side this is going to lead to a certain amount of confusion from whoever reads the report. On the plus side it would mean that the ratios between different volumes such as RV/TLC, IC/ERV and RV/VC found in the original study population would remain correct

• Choose either RV or TLC as the “real” lung volume and re-calculate the other lung volumes using the new VC accordingly. A significant question about this approach is what then happens to the other lung volumes? For example, if TLC is recalculated from RV and a new VC, then the predicted RV/TLC ratio decreases. If FRC is unchanged, then the predicted IC will also increase.

What’s wrong with this is that numerous investigators have shown that the RV/TLC ratio is primarily dependent on age and is independent of the actual TLC so the new RV/TLC ratio is incorrect. The relationship between FRC, IC and TLC is more complex and we don’t use an FRC/TLC ratio or an IC/TLC ratio, but once you’ve “corrected” the TLC these relationships have also changed and are now different from that of the original reference equation. So the real question is that once you start “correcting” lung volumes with a new VC, where do you stop?

It seems to me that the least number of problems are caused by leaving the lung volume reference equations alone and accepting the fact that the predicted VC and the predicted FVC may well be different. Having different predicteds for VC and FVC is what seems to bother people the most however, and I think this points to a lack of understanding of reference equations.

Reference equations for spirometry, lung volumes and DLCO are (with only exceedingly rare exceptions) always derived from different populations, in different locations, using different types of equipment, at different times and are statistically analyzed in different ways. Trying to dovetail these different reference equations into a coherent whole is an ongoing issue for all PFT Labs whether they realize it or not (and I suspect that many don’t). The real solution would be to have reference equations for spirometry, lung volumes and DLCO derived from the same (diverse and very large) population but this isn’t going to happen anytime soon, so the final answer is that we need to continue to be aware of the limitations of the reference equations we use.

The lab the report came from was recently completely re-equipped from the ground up with new equipment and software from a different manufacturer than they had previously so the report and reference equations date at least from the changeover. I know that the lab’s previous reference equations were transferred to the new equipment and it is possible that an error was made along the way and that these aren’t the default settings of the software. But that also means that either by error or intent it is possible to make reference equation settings that don’t add up. This fact should be taken as a reminder that whenever new equipment or new software (even if it is just a new version of existing software) is acquired that you shouldn’t assume that everything adds up and that results always need to be scrutinized carefully.

My biggest concern about this situation is that I think that we all expect, with good reason, for lung volumes to add up correctly. I know that if I hadn’t noticed the discrepancy between the percent predicted VC, TLC and RV it would never have occurred to me that it was necessary to check the math of the predicted values. In this case, for reasons that remain unclear, none of the predicted lung volumes in the report added up correctly and this makes interpreting the results more than a bit problematic.

Manufacturers and end-users are making decisions about VC reference equations and their use with lung volume reference equations in whatever way seems to be right to them. This issue has a critical bearing on the interpretation of lung volume measurements and badly needs to be addressed in the next ATS/ERS statement on interpretation.

References:

Crapo RO, Morris AH, Clayton PD, Nixon CR. Lung volume in healthy nonsmoking adults. Bull Eur Physiopathol Respir 1983; 18: 419-425

Gutierrez C, et al. Reference values of pulmonary function tests for Canadian caucasians. Can Respir J 2004; 6: 414-424.

Hankinson JL, Odencrantz JR, Fedan, KB. Spirometric reference values from a sample of the general U.S. Population. Amer J Resp Crit Care 1999; 159: 179-187

Hansen JE. Pulmonary Function Testing and Interpretation. Published by Jaypee Brothers Medical Publishers, 2011.

Quanjer PH, Tammeling GJ, Cotes JE, Pedersen OF, Peslin R, Yernault J-C. Lung volumes and forced ventilatory flows. Report working party standardization of lung function tests European community for steel and coal. Official statement of the European Respiratory Society. Eur Respir J 1993; 6: Supplement 16, 5-40.

Quanjer PH, Stanojevic S, Cole TJ, Baur X, Hall GL, Culver BH, Enright PL, Hankinson JL, Ip SM, Zheng J, Stocks J. Multi-ethnic reference values for spirometry for the 3-95 yr age range: the global lung function 2012 equations. Eur Respir J 2012; 40: 1324-1343.

PFT Blog by Richard Johnston is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

I was reading James Hansen’s textbook on pulmonary function testing and ran across a spot where he made a minor criticism of the NHANESIII (Hankinson et al) reference equations for the FEV1/FVC ratio. Specifically he noted that the NHANESIII equation ignored height and only used age as a variable but that when he compared the directly calculated FEV1/FVC ratio with one indirectly derived from predicted FEV1 and FVC there was a discrepancy across the normal ranges of height of up to 2.4%.

I had also noticed this discrepancy and wrote about it a while back but at the time I’d only been discussing my lab’s adoption of the NHANESIII reference equations. Hansen’s observation intrigued me, so I decided to re-visit this issue more systematically.

To do this I’ve taken 23 different reference equations for men and women and a variety of ethnicities and plotted the change in the FEV1/FVC ratio versus height, and then repeated this across a range of ages.

When I did this I saw that almost universally the FEV1/FVC ratio decreases with increasing height and that the magnitude of the decrease grew smaller with increasing age.

For men at age 20, the average predicted FEV1/FVC ratio for a height of 165 cm was 86.89 and for a height of 185 cm was 84.36, a difference of 2.53 percent. At age 65, the average predicted FEV1/FVC ratio for a height of 165 cm was 78.05 and for a height of 185 cm was 77.15, a difference of 0.90 percent. For women at age 20 the average predicted FEV1/FVC ratio for a height of 150 cm was 86.97 and for a height of 170 cm was 84.94, a difference of 2.03 percent. At age 65m the average predicted FEV1/FVC ratio for a height of 150 cm was 79.26 and for a height of 170 cm was 78.68, a difference of 0.58 percent.

This matters because an FEV1/FVC ratio below the lower limit of normal (LLN) is an indication of airway obstruction. The NHANESIII LLN for FEV1/FVC ratio does not take height into consideration and means that a tall individual is more likely to be considered to be below the LLN and a short individual is more likely to remain above the LLN.

I have a great deal of respect for the NHANESIII study since it includes an exceptionally large and ethnically diverse study group and a sophisticated statistical analysis was performed on the results. Their reason for excluding height as a factor for the FEV1/FVC ratio reference equation was not discussed however, other than stating that “Only age is needed…”. I have tended to accept this because my lab has seen some exceptionally short and exceptionally tall individuals and the predicted FEV1/FVC ratio derived from their predicted FEV1 and predicted FVC appeared to be in error.

Male 48”	Observed:	Predicted (M)	%Pred (M):	Predicted (N)	%Pred (N)
FVC:	1.72	1.69	102%	2.01	86%
FEV1:	1.35	1.68	82%	1.66	81%
FEV1/FVC Ratio:	78.6	97.5	81%	78.4	100%

Male 84”	Observed:	Predicted (M)	%Pred (M):	Predicted (N)	%Pred (N)
FVC:	8.24	7.40	111%	8.01	103%
FEV1:	5.41	5.44	97%	6.36	85%
FEV1/FVC Ratio:	65.5	73.5	89%	81.45	80%

(M) = Morris 1971 (N) = NHANESIII

These examples are from several years ago when my lab was still using Morris’ 1971 reference equations and the problem was more obvious for the shorter of these two individuals but in either case it was apparent there was a problem. Our response at the time was to use the predicted NHANESIII FEV1/FVC ratio in place of Morris’ predicted when the results were interpreted.

A good part of the problem probably lies with the Morris reference equations for individuals that are outliers in height. When the predicted FEV1/FVC ratio is calculated from the NHANESIII predicted FEV1 and FVC it is 82.6 for the shorter individual and 79.4 for the taller. Even so, the difference between the directly and indirectly calculated NHANESIII FEV1/FVC ratios are 4.60% and 2.05%.

I have been unable to find any study that has directly addressed the issue of height versus FEV1/FVC ratio. Given that 44 out of 46 reference equations show a decrease in the FEV1/FVC ratio with increasing height I have to think that this relationship is correct. My only thoughts about why this is the case would be that airway dimensions do not scale exactly with lung volume. It is still pretty amazing that the FEV1/FVC ratios are almost exactly the same over a very wide range of lung volumes but I don’t think we should be surprised that there is a difference.

Based on this observation, I think this means that the FEV1/FVC ratio should be calculated from predicted FEV1 and FVC. I’d prefer to continue to use the NHANESIII set of reference equations but there is no LLN for an indirectly calculated FEV1/FVC ratio. The LLNs for the directly calculated FEV1/FVC ratio range from 88.3% to 89.9% (based on gender and ethnicity) of the predicted FEV1/FVC ratio. I think that these would probably make a good estimate of the LLN for an indirectly calculated FEV1/FVC ratio.

	Caucasian:	Black:	Hispanic:
Male:	89.0%	88.3%	89.9%
Female:	89.25%	88.35%	89.9%

When reference equations from a large number of studies are compared a relationship between height and the FEV1/FVC ratio becomes evident. The NHANESIII reference equation for the FEV1/FVC ratio does not use height as a factor. Because of this, taller individuals are more likely to be classified with airways obstruction than shorter ones and this is likely because airway dimensions and lung volumes scale at different rates. When the NHANESIII reference equations are used the best solution would be to derive the FEV1/FVC ratio from the predicted FEV1 and FVC instead of using the reference equation for the FEV1/FVC ratio.

References:

Hansen JE. Pulmonary Function Testing & Interpretation. Jaypee Brothers Medical Publishers, 2011.

[A] Hankinson JL, Odencrantz JR, Fedan, KB. Spirometric reference values from a sample of the general U.S. Population. Amer J Resp Crit Care 1999; 159: 179-187

[B] Gutierrez C, et al. Reference values of pulmonary function tests for Canadian caucasians. Can Respir J 2004; 6: 414-424.

[C] Morris JF, Koski A, Johnson LC. Spirometric standards for healthy nonsmoking adults. Am Rev Resp Dis 1971; 103: 57-67.

[D] Morris JF, Koski A, Temple WP, Claremont A, Thomas DR. Fifteen-year interval spirometric evaluation of the Oregon Predictive equations. Chest 1988; 93: 123-27

[E] Knudson RJ, Lebowitz MD, Holberg CJ, Burrows B. Changes in the normal maximal expiratory flow volume curve with growth and aging. Am Rev Resp Dis 1983; 127: 725-734

[F] Johannessen A, Lehmann S, Omenaas ER, Side GE, Bakke PS, Gulsvik A. Post-bronchodilator spirometry reference values in Adults and implications for disease mangement. Amer J Resp Crit Care Med 2006; 173(12): 1316-1325

[G] Marion MS, Leonardson GR, Rhoades ER, Welty TK, Enright PL. Spirometry reference values for American Indian adults. Chest 2001; 120: 489-495

[H] Fulambarker A, Copur AS, Javen A, Jere S, Cohen ME. Reference values for pulmonary function in Asian Indians living in the United States. Chest 2004; 126: 1225-1233

[I] Ip MS, Ko FW, Lau AC, Yu W, Tang K, Choo K, MM Chan-Yeung. Updated spirometric reference values for Adult Chinese in Hong Kong and implications on clinical utilization. Chest 2006; 129: 384-392.

[J] Singh R, Singh HJ, Sirisinghe RG. Spirometric studies in Malayasian between 13 and 69 years of age. Med J Malaysia 1993; 48: 175-184

[K] Perfura-Yone EW, Kanko-Nguekam NF, Kengne AP, Balkissou AD, Noseda A, Kuaban C. Spirometric Reference Equations for semi-urban and urban Bantu Cameroonians. Open J Resp Dis 2013; 3: 164-174.

[L] Steinvil A, Fireman E, Wolach O, Rebhun U, Cohen M, Shapira I, Berliner S, Rogowski O. The effect of ethnic origin on pumonary prediction equations in a Jewish immigrant population. Respiratory Medicine 2008; 102: 919-926.

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[N] Roberts CM, MacRae KD, Winning AJ, Adams L, Seed WA. Reference values and prediction equations for normal lung function in a non-smoking white urban population. Thorax 1991; 46: 643-650.

[O] Lam DCL, Fong DYT, Yu WC, Ko FWS, Lau ACW, Chan JWM, Choo KL, Mok TYW, Tam CY, Ip MSM, Chan-Yeung MMW. FEV3, FEV6 and their derivatives for detecting airflow obstruction in adult Chinese. Int J Tuberc Lung Dis 2012; 16(5): 681-686.

[P] Pereira CADC, Sato T, Rodrigues SC. New Reference Values for forced spirometry in white adults in Brazil. J Bras Pneumol 2007; 33: 397-406.

[Q] Razi E, Moosavi GHA, Akbari H. Spirometric standards for healthy Iranians dwelling in the centre of Iran. Tanoffos 2005; 4(15): 19-26.

[R] Al Ghobain MO, Ahamad EH, Alorainy HS, Hazmi MA, Al Moamary MS, Al-Hajjaj MS, Idress M, Al-Jahdali H, Zeitouni M. Spirometric reference standards for healthy nonsmoking Saudi adults. Clinical Respir J 2014; 8: 72-78.

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[T] Kuster SP, Kuster D, Schindler C, Rochat MK, Braun J, Held L, Brandli O. Reference equations for lung function screening of healthy never-smoking adults aged 18-80 years. Eur Respir J 2008; 31: 860-868.

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PFT Blog by Richard Johnston is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

 

My guidelines for interpreting CPETs originally started as notes to myself about what needed to be on the report and what the normal values were. They grew into a more formal set of instructions that were given to the pulmonary fellows when they were reviewing CPETs. Lately I’ve been reviewing them and re-reading the source material in order to make sure what I had written was still correct and so I could add references.

I tend to focus on one aspect of testing at a time and noticed while reviewing material that the measurements made at peak exercise or anaerobic threshold are almost always considered to be the most important test values. This is true to an extent, but information gathered both before and after testing is also important. In particular, after exercise has ended, during the recovery period, there are several measurements that should be made routinely and are diagnostically significant.

Heart rate recovery (HRR)

When exercise ends, an individual’s heart rate should start decreasing from its peak value. The heart rate recovery (HRR) is the difference between the heart rate at peak exercise and at some interval, usually 1 minute, post-exercise. The rise in heart rate during exercise is due to a combination of parasympathetic withdrawal and sympathetic activation. Vagal reactivation is the principle determinant of heart rate recovery after exercise and a reduction in the heart rate recovery (HRR) indicates a decrease in vagal tone specifically, and parasympathetic tone generally.

In a study of several thousand people the median decrease in heart rate during the first minute following exercise was approximately 17 BPM (normal range 12 to 23 BPM). Numerous investigators have shown that a decrease in heart rate less than 12 BPM in the first minute is associated with an elevated risk of mortality. Individuals with an abnormal HRR have more adverse health risk profiles which includes heart and both obstructive and restrictive lung diseases. They were also more likely to reach a lower workload and had a lower maximum heart rate during exercise. Interestingly, more than one study has shown no significant difference angina, ST-segment depression, or in other abnormal ST-segment changes in patients with either a normal or a reduced HRR.

At least one study has indicated that the HRR less than 22 at two minutes may be a better predictor of mortality than the HRR at one minute, and that abnormal values made the presence of CAD probable but only a small number of studies have followed up on this observation.

The most recent AHA/EACPR CPET guidelines indicated that a HRR less than 12 should be considered abnormal. The increased risk in mortality has been variously shown to be 2 to 4 times higher in individuals with a low HRR than in those with a normal HRR. Some studies have indicated that mortality risk increases even more significantly at a HRR less then 8.

For obvious reasons HRR measurement requires accurately marking the end of exercise. Since the HRR has been studied in primarily in maximal CPETs, a submaximal test may also have a submaximal HRR.

Blood pressure recovery

Systolic blood pressure should reach a maximum at or near peak exercise. Although not as strong an indicator of mortality risk as HRR, a delayed decrease in blood pressure following exercise is a reasonably strong indicator of CAD and hypertension. Individuals with CAD usually have left ventricular dysfunction during exercise due to limited perfusion of the heart muscle. When exercise ends, myocardial oxygen demand decreases and ventricular function improves which causes systolic blood pressure to remain at elevated levels. When the systolic blood pressure (SBP) is measured 3 minutes following exercise and compared to peak systolic blood pressure, a ratio greater than 0.95 should be considered abnormal.

One study showed that an SBP measured 2 minutes post-exercise greater than 195 mm Hg was predictive of an increased risk for myocardial infarction. In a different study the same researchers showed that a ratio of the SBP measured 2 minutes post-exercise to the peak systolic blood greater than 0.95 showed an increased risk for stroke.

The comparison of post-exercise blood pressure depends on the accuracy of the peak exercise blood pressure measurement. Several studies have shown that exercise blood pressure measurements are can be inaccurate and that SBP can be mis-estimated by up to 40 mm Hg. This would appear to be particularly true during treadmill exercise and at high ergometer workloads. For these reasons the post-exercise SBP should be reported, but it should not be the sole parameter used to suggest the presence of cardiovascular disease.

O2 Pulse

It should not be overly surprising that individuals with a low cardiac output not only have difficulty in achieving a normal maximum VO2, but that the rate at which oxygen uptake decreases following exercise is reduced in comparison with normal individuals. These post-exercise differences are somewhat subtle however, and depend greatly on variables such test intensity and subject fitness and are therefore hard to quantify.

A more useful measurement is the O2 pulse at one minute post-exercise. O2 pulse is VO2 (in ml) divided by heart rate (BPM) and is an index of stroke volume. In normal individuals stroke volume decreases relatively rapidly following exercise. An increase in stroke volume is abnormal and tends to be seen in individuals with left ventricular failure and myocardial ischemia. This post-exercise increase in O2 pulse is thought to happen because left ventricular afterload decreases when blood pressure decreases following exercise which in turn improves left ventricular ejection and stroke volume. When this happens the O2 pulse at one minute following exercise will be higher than the O2 pulse at peak exercise.

FEV1

CPETs are often performed in order to assess an individual for exercise-induced bronchospasm (EIB). For this reason spirometry needs to be performed both pre- and post-exercise. There is, however, a lack of consensus regarding both the number and the timing of post-exercise spirometry efforts. Interestingly, the ATS/ACCP CPET guidelines are completely mute on the issue of post-exercise spirometry. The ATS clinical practice guidelines for EIB state that spirometry should be performed at 5, 10, 15 and 30 minutes. The AHA/EACPR CPET guidelines state the FEV1 and PEF should be measured at 1, 3, 5, 7, 10, 15 and 20 minutes post-exercise. The AHA CPET guidelines only state that FEV1 should be measured “periodically” post-exercise. Wasserman et al, states that spirometry should be performed at 3, 6, 10, 15 and 20 minutes post-exercise. Anderson et al, states that spirometry should be measured 5, 10, 15 and 30 minutes post-exercise. Madama states that spirometry should be performed every 5 minutes until FEV1 has returned to baseline or until 30 minutes have passed. Rundell et al, suggest 5, 10, 15 and 30 minutes post-exercise.

Since there are late as well as early responders for EIB, there does appear to be some value in performing spirometry out to 30 minutes. Measurements made earlier than 5 minutes post-exercise however, will likely interfere with post-exercise measurements of VO2, heart rate and blood pressure. For this reason, spirometry performed at 5, 10, 15 and 30 minutes following exercise appears to be the most reasonable approach.

Interestingly, the presence of asthma is usually based on a decrease in FEV1 following exercise but a small number of asthmatics actually increase their FEV1 instead. Normal individuals usually have an increase in FEV1 up to 5% or 7% following exercise. An increase greater than 20 percent however, is likely a sign of asthma.

Recommendations

There is clear evidence concerning the utility of the HRR and post-exercise O2 pulse. For this reason, gas exchange and heart rate measurements should continue for a minimum of 1 minute post-exercise and these values should be reported. Post-exercise blood pressure measurements should be performed for patient safety reasons regardless of the utility of comparing post-exercise SBP to peak SPB but there is no reason not to perform a BP measurement at 3 minutes post-exercise as opposed to a different time. When EIB is suspected, spirometry performed at 5, 10, 15 and 30 minutes post-exercise appears to have a good balance between the need for both early and late measurements. Improvements as well as decreases in FEV1 should be reported.

A CPET doesn’t end when the patient stops exercising. What happens during recovery is in many ways as important as what happened at anaerobic threshold and peak exercise. There are several measurements that should be made during the post-exercise period that are both informative and diagnostically significant, and should be a standard part of all CPET procedures.

Cardiopulmonary exercise testing is resource intensive. Not only does it require an investment in relatively expensive equipment, it requires an investment in patient, technician and physician time. It is therefore important to extract as much information as possible from every CPET. Some labs perform targeted testing, that is CPETs designed to evoke a particular set of results, but there really isn’t a lot of difference between a pre-op VO2 max CPET and a CPET to determine the presence of EIB. Not all CPET measurements will turn out to have been necessary after the fact, but determining which exercise limitations are actually present in a patient (particularly when expectations are to the contrary) is only possible when all possible measurements have been made and are available for review.

References:

Anderson SD, Pearlman DS, Rundell KW, Perry CP, Boushey H, Sorkness CA, Nichols S, Weiler JM. Reproducibility of the airway response to an exercise protocol standardized for intensity, duration and inspired air conditions, in subjects with symptoms suggestive of asthma. Respiratory Research 2010; 11:10

ATS/ACCP Statement on cardiopulmonary exercise testing. Am J Resp Crit Care Med 2003; 167: 211-277.

Chick TW, Cagle TG, Vegas FA, Poliner JK, Murata GH. Recovery of gas exchange variables and heart rate after maximal exercise in COPD. Chest 1990; 97: 276-279.

Cohen-Solal A, Laperche T, Morvan D, Geneves M, Caviezel B, Gourgon R. Prolonged kinetics of recovery of oxygen consumption in patients with chronic heart failure. Circulation 1995; 91: 2927-2932.

Cole CR, Blackstone EH, Pashkow FJ, Snader CE, Lauer MS. Heart-rate recovery immediately after exercise as a predictor of mortality. New Eng J Med 1999; 341: 1351-1357.

Gelb AF, Tashkin DP, Epstein JD, Gong H, Zamel N. Exercise-induced bronchodilation in asthma. Chest 1985; 87: 196-201.

Guzzi M, et al. EACPR/AHA Joint Scientific Statement. Clinical recommendations for cardiopulmonary exercise testing data assessment in specific patient populations. Eur Heart J 2012; 33: 2917-2927.

Koike A, Itoh H, Doi M, Taniguchi K, Marumo F, Umehara I, Hiroe M. Beat to beat evaluation of cardiac function during recovery from upright bicycle exercise in patients with coronary artery disease. Am Heart J 1990; 120: 316-323.

Laukkenen JA, Kurl S, Salonen R, Lakka TA, Rauramaa R, Salonen JT. The blood pressure response to exercise stress test and risk of stroke. Stroke 2001; 32: 2036-2041.

Laukkenen JA, Kurl S, Salonen R, Lakka TA, Rauramaa R, Salonen JT. Systolic blood pressure during recovery from exercise and the risk of acute myocardial infarction in middle-aged men. Hypertension 2004; 44: 820-825.

Lipinski MJ, Vetrovec GW, Froelicher VF. Importance of the first two minutes of heart rate recovery after exercise treadmill testing in predicting mortality and the presence of coronary artery disease in men. Am J Cardiol 2004; 93: 445-449.

Madama VC. Pulmonary function testing and cardiopulmonary stress testing. Published by Cengage Learning, 2007.

McHam SA, Marwick TH, Pashkiw FJ, Lauer MS. Delayed systolic blood pressure recovery after graded exercise. An independent correlate of angiographic coronary disease. J Am Coll Cardiol 1999; 34: 754-759.

Nishime EO, Cole CR, Blackstone EH, Pashkow FJ, Lauer MS. Heart rate recovery and treadmill exercise score as predictors of mortality in patients referred for exercise ECG. JAMA 2000; 284(11): 1392-1398.

Parsons JP, et al. An official American Thoracic Society Clinical Practice Guideline: Exercise-induced Bronchoconstriction. Am J Resp Crit Care Med 2013; 187(9): 1016-1027.

Rundell KW, Slee JB. Exercise and other indirect challenges to demonstrate asthma or exercise-induced bronchoconstriction. J Allergy Clin Immunol 2008; 122: 238-246.

Seshadri N, Gildea TR, McCarthy K, Pothier C, Kavuru MS, Lauer MS. Association of an abnormal exercise heart rate recovery with pulmonary function abnormalities. Chest 2004; 125: 1286-1291.

Sietsema KE, Ben-Dov I, Zhang YY, Sullivan C, Wasserman K. Dynamics of oxygen uptake for submaximal exercise and recovery in patients with chronic heart failure. Chest 1994; 105: 1693-1700.

Singh JP, Larson MG, Manolio TA, O’Donnell CJ, Lauer M, Evans JC, Levy D. Blood pressure response during treadmill testing as a risk factor in new-onset hypertension. Circulation 1999; 99: 1831-1836.

Wasserman K, Hansen JE, Sue DY, Stringer WW, Whipp BJ. Principles of exercise testing and interpretation, Fourth Edition. Lippincott, William and Wilkins, 2005.

PFT Blog by Richard Johnston is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

As workload increases during a progressive cardiopulmonary exercise test (CPET) there comes a point at which the amount of oxygen delivered to the exercising muscle is no longer able to meet its needs. This is the point at which lactic acid begins to accumulate, CO2 production increases and is the accepted definition of the Anaerobic Threshold (AT). The “gold” standard for determining AT is lactic acid measurements but these require sampling blood at regular intervals throughout the CPET. AT is far more commonly determined from respiratory parameters.

Recently I had the opportunity to observe a CPET performed at another PFT Lab. Following the CPET I saw that there was some difficulty in determining the AT. Part of the reason for this is that the staff had only been shown the V-slope method and weren’t aware that there are several alternative approaches.

The V-slope method graphs VCO2 versus VO2. The slope of relationship between VCO2 and VO2 both above and below AT is relatively linear, but changes at AT.

CPET data is often “noisy” however, and it can be difficult to know which data points should be included in the upper and lower slopes.

Another approach is to use the ventilatory equivalents for O2 and CO2 (Ve/VO2 and Ve/VCO2). When these two values are plotted against time, the point at which Ve/VO2 reaches a minimum and then begins to rise without a corresponding increase in Ve/VCO2 is the AT.

A similar approach is to use the PETO2 and PETCO2. When these two values are plotted against time, the point at which the PETO2 reaches a minimum and then begins to rise without a corresponding increase in PETCO2 is also the AT.

There are a couple other secondary techniques. Ve, VCO2 and Rq also rise along with the increasing workload and the VO2 at which the rate of increase in Ve, VCO2 or Rq suddenly increases should coincide with AT. These changes are often quite subtle however and hard to detect.

The ATS/ACCP and AHA guidelines for cardiopulmonary exercise testing do not recommend one technique over another and in fact state “there appears to be no clear advantage of any one noninvasive method for AT determination”. Depending on the patient, AT may be clearer in one method over another, but once it has been detected it by one method it should always be verified by the other methods.

Regardless of how “evident” an AT may appear to be, it should also get some kind of an overall reality check. As an example, a patient with a low VO2 at AT should not be able to reach a high maximum VO2. It should also be remembered that not all patients reach AT and that not all patients who have a normal exercise capacity have an identifiable AT. For these reasons there is no particular “shame” in not being able to identify an AT.

Some test systems will attempt to automatically determine AT, but this occurs with varying degrees of accuracy. I’ve seen some rather wild computer-generated AT’s so it is always important to understand the different methods for determining AT and to be able to verify them manually.

Anaerobic threshold is usually reported as the oxygen consumption (VO2) at which it occurs, and most often as the percent predicted of the maximum VO2. The VO2 at AT says a lot about cardiovascular fitness. The higher the VO2 at AT, the more fit an individual is. When the percent predicted VO2 at AT is below a certain threshold however, this is an indication that there is an abnormal limitation in the oxygen supply to the muscles. This can be due to a reduced cardiac output, vascular disease or even to mitochondrial myopathies.

	Male:		Female:
Age:	Mean:	LLN:	Mean:	LLN:
20	53	42	52	41
30	54	43	55	44
40	55	44	58	47
50	56	45	60	49
60	57	46	63	52
70	58	47	65	54

Anaerobic threshold will vary in a given individual depending on what testing mode is used. Arm ergometry produces the lowest VO2 at AT. Treadmill testing produces the highest VO2 at AT with cycle ergometry between 5% and 11% lower than treadmill. For this reason it is important to select a predicted VO2 reference equation that takes the testing mode into consideration.

Not only is the VO2 at AT an important part of CPET interpretation, but the minute ventilation at AT can be informative. When a CPET is submaximal it can be difficult to determine if a patient has a pulmonary mechanical limitation. If the patient has achieved AT however, the minute ventilation at AT can help determine whether this would have occurred. Specifically, a minute ventilation at AT that is greater than 42% of the predicted maximum indicates the patient likely has a pulmonary mechanical limitation.

Maximum oxygen consumption has been the primary tool of surgical risk and general mortality assessments. VO2 max will likely be reduced when a CPET is submaximal and a CPET can be submaximal due to musculoskeletal limitations, patient safety concerns (EKG and blood pressure changes) or poor patient motivation. An individual can have a submaximal CPET and still attain anaerobic threshold. When patients with heart failure were studied, investigators found that those with a VO2 at AT less than 11 ml/kg/min showed an elevated mortality risk and that this was more significant than a low peak VO2. Similarly a survey of patients with post-operative complications and mortality showed that individuals with VO2 at AT less than 50% of predicted or 11 ml/kg/min had an elevated risk. VO2 at AT can also be used to assess which cardiac class a patient belongs to.

Class:	Severity:	VO2 at AT:
A	Mild to none	> 14
B	Mild to moderate	11 to 14
C	Moderate to severe	8 to 11
D	Severe	5 to 8

Anaerobic threshold occurs as increases in workload surpass the ability to provide oxygen to the exercising muscles. The VO2 at which it occurs is a reflection of cardiovascular fitness and is a crucial part of interpreting CPET results. Accurate detection of the AT is therefore important and there are a variety of methods for doing this. The only reason that one method may be superior the others is that the data signaling AT may be more evident for the patient being evaluated. Regardless of which method is initially used to detect AT, AT should be verified across all methods.

References:

ATS/ACCP Statement on cardiopulmonary exercise testing. Am J Resp Crit Care Med 2003; 167: 211-277.

Balady GJ, et al. Clinician’s guide to Cardiopulmonary exercise testing in Adults. Circulation 2010; 122: 191-225.

Caiozzo VJ, Davis JA, Ellis JF, Azus JL, Vandagriff R, Prietto CA, McMaster WC. A comparison of gas exchange indices used to detect the anaerobic threshold. J Appl Physiol 1982; 53(5): 1184-1189.

Gitt AK, Wasserman K, Kilkowski C, Kleeman T, Kilkowski A, Bangert M, Schneider S, Schwarz A, Senges J. Exercise anaerobic threshold and ventilatory efficiency identify heart failure patients for high risk of early deat. Circulation 2002; 106: 3079-3084.

Medoff BD, Oelberg DA, Kanarek DJ, Systrom DM. Breathing reserve at the lactate threshold to differentiate a pulmonary mechanical from a cardiovascular limitation to exercise. Chest 1998; 113: 913-918.

Older P. Anaerobic threshold, is it a magic number to determine fitness for surgery? Perioperative Medicine 2013: 2:2

Smith TB, Stonell C, Purkayastha S, Paraskevas P. Cardiopulmonary exercise testing as a risk assessment method in non cardio-pulmonary surgery: A systematic review. Anaesthesia 2009; 64: 883-893.

Sue DY, Wasserman K, Moricca RB, Casaburi R. Metabolic acidosis during exercise in patients with chronic obstructive pulmonary disease. Use of the V-slope method for anaerobic threshold determination. Chest 1988; 94: 931-338.

Wasserman K, Hansen JE, Sue DY, Stringer WW, Whipp BJ. Principles of exercise testing and interpretation, Fourth Edition. Lippincott, William and Wilkins, 2005.

Weber KT. What can we learn from exercise testing beyond the detection of myocardia ischemia? Clin Cardiol 1997; 20: 684-696.

PFT Blog by Richard Johnston is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Recently I was reviewing test results from another PFT Lab that uses equipment from a different manufacturer than what my lab uses. When I came to the lung volumes it became evident that the FVC had been substituted for the SVC. I understand the point of using the largest vital capacity when calculating TLC and RV but there are some issues affecting these values when this is done.

Strictly speaking using the FVC is permitted by the ATS/ERS guidelines on lung volume testing, but how an FVC is to be used, as opposed to an SVC, is not addressed. The reason this is an issue is that all lung volume tests regardless of which method is used do not measure TLC and RV directly, they measure FRC. The preferred ATS/ERS TLC calculation is then:

RV = FRC – ERV and TLC = RV + VC

But

TLC = FRC + IC and RV = TLC – VC

is also permitted.

IC and ERV are not explicitly measured from an FVC maneuver and are instead measured during an SVC measurement.

It is here is where the problems of using an FVC in lung volume calculations appears. Specifically, the FVC was substituted for the SVC because the SVC was smaller than the FVC. When this happens then either the IC or the ERV (or both) are also smaller than they “should” be but there is no way to tell which of these is the case. My general inclination is to believe the ERV is reduced since exhaling to RV is harder than inhaling to TLC but I’ve run across many instances where the opposite occurred.

Further inspection of the reported lung volumes showed another problem, however. It was evident that the system was calculating TLC from IC + FRC and then RV from TLC – VC. When this order of calculations is performed the ATS/ERS lung volume guidelines state that “The TLC is the mean of the three largest sums of technically acceptable FRC values and linked IC maneuvers.” The system was averaging the FRC measurements but instead of averaging FRC + IC it was selecting the largest IC from all of the SVC measurements that had been made. This means that the reported TLC was calculated from (mean FRC) + largest IC.

Note:  If the calculation started with RV = FRC – ERV the ATS/ERS statements explicitly say that both the FRC and ERV are to be averaged.

The largest IC may or may not be the correct value to use. FRC is a dynamic value and changes as compliance, posture, ventilation and muscle tone change. FRC, IC and ERV can undergo noticeable changes without there being any change in TLC and RV. This is the reason that the ATS/ERS guidelines emphasize “linked” maneuvers. It is true that the largest IC could be a reflection of the best quality SVC maneuver but there is no guarantee this is the case.

Strictly speaking the actual difference between the FVC and SVC was less than 0.2 liter. The TLC and RV calculated using the FVC rather than the SVC are therefore likely near what they would have been with a more optimal SVC. The problem is that because the VC, IC and ERV came from different maneuvers there is no way to say whether the TLC and RV were accurate, overestimated or underestimated.

An additional concern with these lung volumes is that none of the staff from the PFT Lab where the lung volume tests were performed were aware that the test system software was automatically substituting FVC for SVC. Since the SVC was not present on the report the only way to determine how different it was from the FVC was to review the raw test data.

Neither was anyone aware that the largest IC was being added to the average FRC to calculate TLC but this was also not evident on the report and it took me a fair amount of digging in the raw test data to determine this was happening. These facts may well be in the test system’s manual but this was not evident from a quick review.

There is no particularly good answer to this problem. There are good reasons to use the largest VC, both when calculating the FEV1/VC ratio and when calculating lung volumes. Other than stating that it is acceptable to use an FVC in lung volume measurements however, the ATS/ERS guidelines do not address how to use an FVC and instead speak only of linked FRC, IC and ERV measurements. Because of this limitation in the ATS/ERS guideline individual manufacturers are left to decide for themselves whether or not a larger FVC should be substituted for a smaller SVC, and then to decide how to properly calculate TLC and RV.

When a manufacturer claims to meet ATS standards users however, have every reason to expect that calculations are performed accurately and that a minute inspection of the calculation algorithms is unnecessary. In this case the manufacturer can accurately claim that they are meeting the ATS/ERS guidelines when they substitute FVC for SVC although I would point out that using the largest IC is not an appropriate interpretation of the guidelines.

My preference would be that because using FVC instead of SVC has the potential to introduce more error into the calculation of TLC and RV it should not be used. I am biased however, because I am used to judging lung volume test quality based on the “real” SVC and find this more difficult when a larger FVC is automatically substituted. Realistically however, this approach is just as likely to introduce errors into the calculation of TLC and RV it’s just that I think the errors are easier to detect.

References:

Brusasco V, Crapo R, Viegi G. ATS/ERS task force: Standardisation of lung function testing. Standardisation of the measurement of lung volumes. Eur Respir J 2005; 26: 511-522.

PFT Blog by Richard Johnston is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

I was reviewing a PFT recently and noticed that the FEV1 was severely reduced and that the FRC and RV were both elevated. This is a pattern we associate with obstructive gas trapping but I’ve also been reviewing textbooks on pulmonary function interpretation and have found that there isn’t any kind of a universal definition for this.

Hyperinflation and gas trapping are used somewhat interchangeably but the distinction is that gas trapping causes hyperinflation. Gas trapping occurs to some extent in everybody but usually at lung volumes below FRC. The lung volume at which gas trapping occurs rises with age and with obstructive lung disease. Hyperinflation is usually considered to be an increase in FRC but FRC is a dynamic lung volume and there is a range in the response to increased gas trapping. The normal progression from mild to very severe COPD goes something like this:

	FEV1:	FVC:	FRC:	RV:	TLC:	RV/TLC:
Mild	↓	–	–	–	–	–
Moderate	↓↓	↓	–	↑	–	↑
Severe	↓↓↓	↓↓	↑	↑↑	–	↑↑
Very Severe	↓↓↓↓	↓↓↓	↑↑	↑↑↑	↑	↑↑↑

Gas trapping and hyperinflation have significant consequences for an individual’s exercise capacity and level of dyspnea. It is an important clinical finding but from a PFT point of view when is it clearly present?

Hyperinflation can’t be considered to be present when there just is a reduced FEV1 and FVC can be reduced along with FEV1 for reasons that have nothing to do with airway obstruction. This means that lung volumes need to be measured in order to assess the presence of hyperinflation.

I used to think that spirometry and DLCO tests were hard and that lung volumes were easy. In retrospect this had a lot more to do with how hard it was to get a patient to perform the tests correctly and not how easy it was to assess test quality. All lung volume measurements more or less start by measuring FRC and without sufficient care (regardless of whether the technique is helium dilution, nitrogen washout or plethysmography) it is relatively easy to overestimate (and harder but not impossible to underestimate) FRC.

The best way to verify that lung volume measurements are accurate is when they are reproducible. Interestingly, the ATS/ERS standards on lung volumes only discusses repeatability for plethysmographic FRC (+/- 5%) and not for helium dilution or nitrogen washout results. I do not think this is the correct approach since there are a number of reasons why FRC can vary from test to test without affecting the TLC and RV. For this reason we primarily look at TLC and RV when assessing reproducibility and try to make sure they are within 5%.

Even though it is my lab’s policy that lung volumes be measured at least twice there are many reasons (some good, some bad) why we aren’t always able to get two lung volume tests with acceptable quality. In these instances we have to rely on quality indicators when selecting a specific set of results but without repeatability there is always a level of uncertainty. For this reason I would be hesitant about the presence of hyperinflation when only a single set of lung volume measurements are available.

Assuming that good quality lung volume measurements are available however, is gas trapping present if the RV/TLC ratio is elevated? I’ve seen several research studies from around forty years ago where an elevated RV/TLC ratio was called the “emphysema index”. The RV/TLC ratio hasn’t been called this in a while and the phrase is now applied to specific radiological CT findings but it is clear that an elevated RV/TLC ratio has been considered a symptom of COPD for quite a while.

The RV/TLC ratio cannot be taken as a sole indication of hyperinflation because there is at least one instance (and probably more) where an elevated RV/TLC ratio is not a symptom of COPD at all. When restrictive lung disease is caused by neuromuscular weakness FRC tends to be normal but TLC is reduced and RV is elevated because the individual lacks the strength to sufficiently inhale or exhale. In these cases the RV/TLC ratio will be elevated but this has nothing to do with airway obstruction.

In fact, even though the RV/TLC ratio has been a standard element of PFT reports for as far back as I can remember there I times I wonder why it is reported at all. It’s not at all clear to me that the RV/TLC ratio is any more informative than just the RV and in addition I haven’t seen an elevated RV/TLC ratio used as part of an interpretation in decades.

So, is gas trapping present when the RV is elevated? Maybe. My problem with this is that the RV is frequently increased when SVC test quality is suboptimal. When I review results, I always compare the FVC and SVC. This is usually in order to make sure the largest VC is used to calculate the FEV1/VC ratio but it can also pinpoint problems with lung volume measurements. I expect the SVC to be at least as large as the FVC but when it is significantly less I am not surprised to see an elevated RV.

Interestingly, the ATS/ERS statements on lung volumes say nothing about using a larger FVC in place of a smaller SVC in order to determine RV and TLC. This is not all that surprising given that IC and ERV are a critical part of the calculation. Depending on whether the ERV or the IC part of the SVC maneuver is performed first then:

RV = FRC – ERV and TLC = RV + SVC

or

TLC = FRC + IC and RV = TLC – SVC.

IC and ERV are not measured from an FVC maneuver but only from an SVC maneuver. If the SVC is suboptimal, there is no way to know whether the IC or the ERV is correct or whether they are suboptimal as well. Depending on the calculation order replacing a suboptimal SVC with a larger FVC can lead to either to over- or under-estimating the RV and the TLC.

Having an SVC that is larger than an FVC is no guarantee it’s accurate since for this kind of comparison the FVC needs to be reasonably accurate as well. There are always some individuals that can’t seem to exhale longer than two seconds, if that. For these people, an SVC that is only slightly larger than what is clearly a suboptimal FVC is still a suboptimal SVC.

So what about when both FRC and RV are elevated? I think this is a reasonably clear signal for gas trapping and hyperinflation and is pretty much the standard my lab uses. Obstructive gas trapping occurs because of expiratory flow limitation and when it causes FRC to move a higher volume the FRC is then on a less efficient portion of the lung’s pressure-volume curve. This increases the work of breathing and reduces an individual’s ability to increase ventilation. To me, this has to be the definition of clinically relevant hyperinflation.

Finally, should hyperinflation be considered to be present only when TLC, FRC and RV are elevated? Hyperinflation is certainly present when this is the case but I think this misses the point somewhat. TLC does not have to be elevated for clinically relevant gas trapping and hyperinflation to be present. I’d also point out that elevated TLCs are not as common as the used to be or at least I certainly don’t see them as often as I used to. This is a good thing and I believe it is occurring because of earlier recognition and intervention of COPD as well as better medications. I would think that requiring the TLC to be elevated as well as FRC and RV as the definition of hyperinflation would be too limiting.

One problem with all of this is that lung volumes can only assess resting hyperinflation which is a consequence of relatively advanced airway obstruction. Gas trapping can occur during exercise because of expiratory flow limitation and increased ventilatory demands. When this happens FRC increases. We monitor this during our CPETs by having the patient perform an IC maneuver every two minutes during exercise. The IC lets us track the patient’s End-Expiratory Lung Volume (EELV) which is a surrogate for FRC. When IC decreases this is an indication that FRC is increasing and a sign of dynamic hyperinflation. An individual however, can have dynamic hyperinflation and still have a normal resting FRC.

As useful as CPETs are, performing one solely to determine whether dynamic hyperinflation is occurring may be overkill. I’ve seen at least one test system intended for 6-minute walk tests that is able to measure IC which may be an interesting solution for this. Also, back in the 1970’s, before we had such new-fangled things like flow-volume loops we would place a patient on a closed-circuit spirometer and after they had settled into normal tidal breathing we’d have them take a deep inspiration:

Individuals with COPD would take several tidal breaths after the deep breath to return to their prior FRC baseline. This was a qualitative test in that there were no numbers you could get from it, just the observation that their FRC baseline shifted. I’m not sure how well this correlates with resting or dynamic hyperinflation but it was a simple test. Unfortunately I don’t know of any test systems today that would allow this test to be performed.

Hyperinflation is a clinically important finding and the earlier it is discovered the better prognosis a patient will likely have. Dynamic hyperinflation likely occurs earlier in the progression from mild to severe COPD than does resting hyperinflation but requires specialized testing to confirm its presence. Determining that resting hyperinflation is present requires attention to lung volume test quality and repeatability. Although an elevated RV is frequently a consequence of airway obstruction, and may be an early stage of hyperinflation, it is not by itself a clear sign of resting hyperinflation. Resting hyperinflation is clearly present when an individual has an increased FRC and RV, and this fact should be noted in an interpretation.

References:

Brusascoi V, Crapo R, Viegi G. ATS/ERS Task force: Standardisation of lung function testing. Standardisation of the measurement of lung volumes. Eur Respi J 2005; 26: 511-522.

PFT Blog by Richard Johnston is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Two PFT reports came across my desk recently and comparing them got me to thinking about Peak Expiratory Flow (PEF). The FEV1 from both tests were mildly reduced with an FEV1/FVC ratio that was moderately reduced and an FVC that was within normal limits.

	Observed:	%Predicted:
FVC (L):	3.72	96%
FEV1 (L)	2.17	78%
FEV1/FVC (%):	58	80%
PEF (L/sec):	2.97	41%

	Observed:	%Predicted:
FVC (L):	2.46	88%
FEV1 (L)	1.66	75%
FEV1/FVC (%):	67	83%
PEF (L/sec):	7.65	128%

Both tests also showed mild airway obstruction but despite this the Peak Flows were quite different. One test had a PEF that was moderately to severely reduced and the other had a PEF that was elevated. It’s fascinating that two such completely different flow-volume loops are so numerically similar.

In another sense, though, how can these two different spirometry efforts both be labeled as mild airway obstruction? Or more importantly, they both may be mild obstruction but isn’t the quality of the obstruction different?

Unfortunately for this thought PEF is not part of any spirometry interpretation algorithm I am familiar with. The only research I was able to find linking PEF to a particular form of airway obstruction was performed over 40 years ago. It suggested that the FEV1/PEF ratio (ml/LPM) could be used as a way to assess the presence of upper airway obstruction. This research was performed at a time when flow-volume loops were less commonly available and ratios in the FEV1/PEF above 8 were suggested as way to flag patients for further workup. Flow-volumes are now routine, so the value of this ratio, particularly since poor test effort can also produce elevated FEV1/PEF ratios, looks to be limited and in any case this ratio is not routinely reported by any spirometry test system anyway.

Even though PEF is not used as part of any differential diagnoses it has found many other purposes.

PEF has been routinely used to monitor asthmatics and to detect occupational asthma for decades but this is primarily through comparing trends. Even so it’s unclear to me how good a reduced or elevated PEF by itself is in detecting or ruling out airway obstruction. There are numerous studies that come down on both sides of this but I think that part of the problem is that many of the studies have used Peak Flow meters, not the PEF obtained from a spirometry effort. Peak flow meters have limited accuracy and depending on how they are constructed they may be more or less sensitive to different aspects of Peak Flow itself.

Note: There are relatively easy ways to “fool” a peak flow meter depending on how an individual performs the peak flow maneuver. I have personally known some asthmatics who have deliberately raised their results in order to avoid being put on prednisone and some who have lowered their results in order to show how bad off they “really” were. Moreover, peak flow meters are often handed to patients without any training and even when they were trying their best, their peak flow maneuvers (at best learned from the product inserts) were often not correct.

Peak flow can be characterized by two values, Rise Time (RT) and Dwell Time (DT). These values are derived from a graph of flow-versus time. Rise Time is the length of time from the start of exhalation to 90% of the PEF. Dwell Time is how long expiratory flow stays above 90% (or 95%) of the PEF.

One study showed RT to vary from 23 to 168 milliseconds and DT to vary from 5 to 164 milliseconds in a large study group. Interestingly, both RT and DT tended to be shorter for individuals with airflow obstruction than those with normal lungs. This is likely a reflection of the lower peak flow these individuals usually attain as well as the inability to sustain high flow rates. The mechanical characteristics of any given Peak Flow meter likely affects how accurately they are able to register changes in peak flow for different patients which has implications for both individual use and group comparisons made with Peak Flow meters.

Spirometers are usually tested against the standard ATS flow-volume loop waveforms. The original 26 waveforms however, have RT’s from 50 to 184 milliseconds and DT’s from 34 to 254 milliseconds. Although most flow-based systems would meet the range of Rise and Dwell times mentioned above (it’s how they were measured after all), it does mean that the ATS waveforms may need to be updated.

Several studies have indicated PEF can be useful in assessing spirometry test quality but the guidelines for this aren’t as clear as I’d like. In particular the ATS/ERS statement on spirometry indicates that the “largest FVC and the largest FEV1 … should be recorded after examining the data from all of the usable curves, even if they do not come from the same curve” and does not mention Peak Flow at all. I think the disconnect lies in the difference in the definitions for “best quality FEV1” and “largest FEV1”.

A forced vital capacity maneuver is supposed to be performed with maximal effort. A maximal expiratory effort will compress airways and narrow them, which increases the resistance to air flow. A submaximal effort will not compress airways as much and can produce higher expiratory flow rates for longer periods of time. For these reasons maximal efforts tend to have the highest PEF but can also have a lower FEV1 than a submaximal effort. Strictly speaking therefore, the selection an FEV1 should use the best PEF as one of the guidelines. In my PFT Lab the largest FEV1 doesn’t have to come from the effort with the highest PEF but it should come from an effort where the PEF is within about 5% of the best PEF. This means that we occasionally report an FEV1 that is not the largest a patient produced, but it is also reasonable assurance that the FEV1 came from an effort with maximal effort.

Having said that the ATS/ERS spirometry statement doesn’t say that PEF should be used to assess test quality, it does indicate that it should be used to assess the repeatability of spirometry efforts. Specifically, the two highest PEFs from a series of spirometry efforts should be within 0.67 L/sec (40 LPM) of each other. This means that when this criteria is met a reported FEV1 will likely come from an effort with a reasonably good PEF. In my PFT Lab we still have to manually “eyeball” the results however, to assure repeatability because our test system’s software does not provide an assessment of PEF repeatability in the same way it does for FVC and FEV1 by visually flagging the results.

Numerous investigators have shown that PEF can increase following an inhaled bronchodilators . Despite this the ATS/ERS statement on interpretation does not discuss PEF and limits the assessment of bronchodilator response to just FVC and FEV1. One reason for this is may be that PEF is more effort dependent than FEV1 and post-BD changes aren’t as reliable an indicator of bronchodilation. Another may be that clinically significant bronchodilation that is reflected by changes in FVC and FEV1 may not be reflected by equally significant changes in PEF. Since there is still widespread debate about what a significant response to bronchodilator actually is and since there can be clinically significant post-BD changes in FRC, IC, PIF and FIV1 without significant change in FVC and FEV1 I’d say the door is still open on this issue.

As with all other PFT values, there is always the question about what’s normal. I have been able to find 17 usable reference equations for males and 13 usable reference equations for females (some published equations produced results that did not match that of the study despite careful proofreading). More so than any of the other PFT values like FVC, FEV1, TLC and DLCO, there is a much wider range of “normal” PEF. For a 175 cm male, the range from the highest and lowest predicted PEF was approximately 7 L/sec. This was relatively independent of age and is a minimum of 50% of the maximum predicted PEF. For a 165 cm female the absolute difference for between the highest and lowest predicted was smaller, about 3 L/sec, but this is also relatively independent of age and also about 50% of the maximum predicted PEF.

Interestingly height appears to have less of an effect on any predicted PEF than it does for FVC, FEV1, TLC and DLCO.

There also appears to be ethnicity based differences in PEF that are similar to those in FEV1. I have been unable to find any systematic comparison of PEF and ethnicity however, and these studies date over a 40 year period. PEF is likely more sensitive to the technology used to measure it than is FEV1 (specifically, PEF is likely underestimated in volume-displacement spirometers) and I would hesitate to draw any conclusions before this aspect is taken into consideration.

I still feel that PEF is saying something when it comes to differentiating between different forms of airway obstruction. That shouldn’t be surprising since it’s well known that the flow-volume loop has distinct contours for different lung diseases and PEF is a significant aspect of these contours. PEF is dependent on maximal patient effort however, and that limits its ability to be a reliable indicator. The exceptionally wide range of normal values also makes it difficult for an initial and isolated measurement of PEF to be used to assess airway obstruction. Despite its limited ability to assess lung function PEF can and should routinely be used to assess the quality and repeatability of spirometry results.

Male Peak Flow Reference Equations

Reference:	Equation:
[A] Saudi	(17.274-(1.243 x age)+(3.471 x height))/60
[B] White	EXP(-4.548+(1.2965 x LN(height))+(0.0066 x age)-(0.000106 x age^2))
[C] Black	-2.041+(0.07552 x age)-(0.001414 x age^2)+(0.0616 x height)
[C] White	-3.244+(0.13976 x age)-(0.002077 x age^2)+(0.0637 x height)
[D] Iranian	(0.07759 x height) – (0.0435 x age) – 13.69
[E] White	(-30.15 + (30.63 x age) – (0.723 x age ^2) + (0.00521 x age^3) + (height x 1.46))/60
[F] Black	2.2257-(0.04082 x age)+(0.00027333 x height^2)
[F] Hispanic	0.087+(0.0658 x age)-(0.001195 x age^2)+(0.00030243 x height^2)
[F] White	1.0523+(0.08272 x age)-(0.001301 x age^2)+(0.00024962 x height^2)
[G] White	(0.000342 x age^2)+(0.0169 x age)+(0.0885 x height)-5.8
[H] White	(0.094 x height)-(0.035 x age)-5.993
[I] White	EXP(-3.76+(1.17 x LN(height))+(0.00706 x age)-(0.00011 x age^2))
[J] Black	-0.1545-(0.0532 x age)+(0.0625 x height)
[K] Black	-0.814-(0.038 x age)+(5.429 x (height/100))
[L] Filipino	6.872+(0.0692 x weight)-(0.0527 x age)
[M] White	(5.317 x (height/100))-(0.062 x age)+3.884
[N] Brazilian	2.7183^(LN(height x 0.83)-LN(age x 0.114)-1.43)

Female Peak Flow Reference Equations:

Reference:	Equation:
[A] Saudi	((4.076 x height)-(0.499 x age)-226.648)/60
[C] Black	-2.185+(0.07535 x age)-(0.00117 x age^2)+(0.0507 x height)
[C] White	-1.457+(0.06296 x age)-(0.001084 x age^2)+(0.0474 x height)
[D] Iranian	(0.06402 x heightp)-(0.039 x age)-1.607
[E] White	(198.07+(3.07 x age)-(0.0477 x age^2)+(1.42 x heightp))/60
[F] Black	-1.3597+(0.03458 x age)-(0.000847 x age^2)+(0.00019746 x height^2)
[F] Hispanic	0.2401+(0.06174 x age)-(0.001023 x age^2)+(0.00022203 x height^2)
[F] White	0.9267+(0.06929 x age)-(0.001031 x age^2)+(0.00018623 x height^2)
[H] White	(0.049 x height)-(0.025 x age)-0.735
[I] White	EXP(-4.794+(1.316 x LN(heightp))+(0.00926 x age)-(0.000143 x age^2))
[K] Black	-4.453-(0.038 x age)+(6.695 x (height/100))
[L] Filipino	-7.463+(0.0874 x height)
[M] White	(4.087 x (height/100))-(0.05 x age)+2.945

Reference Equation Study Characteristics:

Reference:	Ethnicity:	#Female:	Female Ages:	#Male:	Male Ages:
[A]	Saudi	292	18-65	175	18-65
[B]	White	4908	25-60	4743	18-60
[C]	White	1224	18-65	2844	18-65
[C]	Black	383	18-65	591	18-65
[D]	Iranian	1110	21-80	1302	21-80
[E]	White	199	14-64	202	14-64
[F]	White	927	21-80	476	21-80
[F]	Black	772	21-80	422	21-80
[F]	Hispanic	872	21-80	506	21-80
[G]	White			270	20-70
[H]	White	321	20-79	128	25-79
[I]	White	7009	18-80	4565	18-80
[J]	Black	117	18-47	143	18-47
[K]	Black	205	18-90	206	18-85
[L]	Filipino	153	16-68	130	17-78
[M]	White	96	18 to >70	83	18 to >70
[N]	Brazilian	270	25-75	373	20-75

References:

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[B] Brandli O, Schindler Ch, Kunzli N, Keller, R, Perruchoud AP. Lung function in healthy never smoking adults: reference values and lower limits of normal of a Swiss population. Thorax 1996; 51: 277-283

Brusasco V, Crapo R, Viegi G. ATS/ERS Task Force: Standardisation of Lung Function Testing. Standardisation of Spirometry. Eur Respir J 2005; 26: 319-338.

Empey DW. Assessment of upper airways obstruction. Brit Med J 1972; 3: 503-505.

[C] Glindemeyer HW, Lefante JJ, McColloster C, Jones RN, Weill H. Blue-collar normative spirometric values for caucasian and African-American men and women aged 18 to 65. Am J Respir Crit Care Med 1995; 151: 412-422.

[D] Golshan M, Nematbakhsh M, Amra B, Crapo RO. Spirometric reference values for a large Middle Eastern population. Eur Respir J 2003; 22: 529-534.

[E] Gregg I, Nunn AJ. Peak Flow in normal subjects. Brit Med J 1973; 3: 282-284

[F] Hankinson JL, Odencrantz JR, Fedan, KB. Spirometric reference values from a sample of the general U.S. Population. Amer J Resp Crit Care 1999; 159: 179-187

[G] Hedenstrom H, Malmberg P, Fridriksson HV. Reference values for lung function tests in men: Regression equations with smoking variables. Upsala J Med Sci 1986; 91: 299-310

Hegewald MJ, Lefor MJ, Jensen RL, Crapo RO, Kritchevsky SB, Haggerty CL, Bauer DC, Satterfield S, Harris T. Peak expiratory flow is not a quality indicator for spirometry. Peak expiratory flow variability and FEV1 are poorly correlated in an elderly population. Chest 2007; 131: 1494-1499.

Krowka MJ, Enright PL, Rodarte JR, Hyatt RE. Effect of effort on measurement of Forced Expiratory Volume in one second. Am Rev Resp Dis 1987; 136: 829-833.

[H] Knudsen RJ, Slatin RC, Lebowitz MD, Burrows B. The maximal expiratory flow-volume curve. Normal standards, variability and effects of age. Am Rev Resp Dis 1976; 113: 587-601.

[H] Kuster SP, Kuster D, Schindler C, Rochat MK, Braun J, Held L, Brandli O. Reference equations for lung function screening of healthy never-smoking adults aged 18-80 years. Eur Respir J 2008; 31: 860-868.

[I] Mengesha YA, Mekonnen Y. Spirometric lung function tests in normal non-smoking Ethiopian men and women. Thorax 1985; 465-468.

Miller MR, Pedersen OF, Quanjer PH. The rise time and dwell time for peak expiratory flow in patients with and without airflow limitation. Am J Resp Crit Care Med 1998; 158: 23-27.

[J] Perfura-Yone EW, Kanko-Nguekam NF, Kengne AP, Balkissou AD, Noseda A, Kuaban C. Spirometric Reference Equations for semi-urban and urban Bantu Cameroonians. Open J Resp Dis 2013; 3: 164-174.

[K] Roa CC, Zaldivar CA, Salonga RC, Bobadilla J, Lansang MA, Reodica R, Balgos A, Blanco J, Tanchuco JQ. Normal standards for ventilatory function in adult Filipinos. Phillipine J Internal Med, 2013; 51(1): 1-6.

[L] Roberts CM, MacRae KD, Winning AJ, Adams L, Seed WA. Reference values and prediction equations for normal lung function in a non-smoking white urban population. Thorax 1991; 46: 643-650.

[M] Pereira CADC, Sato T, Rodrigues SC. New Reference Values for forced spirometry in white adults in Brazil. J Bras Pneumol 2007; 33: 397-406.

Thiaden HA, De Bock GH, Van Houwelingen JC, Dekker FW, De Waal MWM, Springer MP, Postma DS. Can peak expiratory flow measurements reliably identify the presence of airway obstruction and bronchodilator response as assessed by FEV1 in primary care patients presenting with a persistent cough. Thorax 1999; 54: 1055-1060.

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