Author: Richard Johnston

Oxygen transport between the lungs and the body depends on numerous complex factors. Ventilation and the alveolar-capillary surface area are of course important but a critical component is hemoglobin. Oxygen is poorly soluble in water (which is what blood is mostly made of) and the transportation of oxygen throughout the body would not happen without hemoglobin’s ability to absorb and release oxygen on demand. Although it is possible to measure the diffusing capacity of oxygen (DLO2) the process is technically difficult and not at all suited to routine clinical testing.

There are a number of gases that are able to diffuse across the alveolar-capillary membrane and can be used in a variety of physiological measurements but in order for a particular gas to act as a substitute for oxygen it must be able to interact with hemoglobin. Carbon monoxide (CO) has an affinity for hemoglobin approximately 220 times greater than oxygen and was the first gas used to measure diffusing capacity (DLCO). DLCO has been a routine test for well over 50 years and has been measured by single-breath, steady-state and rebreathing techniques.

Nitric Oxide (NO) has an affinity for hemoglobin about 400 times greater than carbon monoxide (it is generally an irreversible process since the end product is methemoglobin whereas hemoglobin’s binding with CO is more reversible) and for this reason it can also be used to measure diffusing capacity. DLNO can also be measured by single-breath, steady-state and rebreathing techniques. Because of its high affinity and the speed at which the binding of NO to hemoglobin occurs numerous researchers have assumed that DLNO is equivalent to DMNO (the membrane component of diffusing capacity). This is not really true, but it can be a useful fiction and in order to understand why it’s necessary to look at the basic physiology of diffusing capacity tests.

Roughton and Forster’s seminal 1957 paper showed that diffusion is the sum of two resistances. I’ve discussed this previously but specifically:

Where:

DMCO = membrane component

θCO = the rate at which CO binds to hemoglobin

Vc = pulmonary capillary blood volume

The first resistance (1/DMCO) is the resistance to the diffusion of CO through the alveolar-capillary membrane and blood plasma to the surface of the stagnant plasma boundary layer around a red blood cell. The second resistance refers to the diffusion rate of CO through the plasma boundary layer, then the wall and interior of the red blood cell and finally the rate of reaction with hemoglobin.

The same formula applies to DLNO:

θNO however, is relatively large and in fact when its value was initially calculated it came out close to infinity. For this reason, it has been assumed that the value on the right side of the equation [1/θNO x Vc] is exceedingly small and as a shortcut can be assumed to be zero. For this reason many researchers have assumed that DLNO is essentially equal to DMNO.

The diffusion rate of gases across the alveolar-capillary membrane is directly proportional to their solubility and inversely proportional to their molecular weight. For this reason, the difference in the membrane component of diffusion for CO and NO is:

Where:

α = solubility coefficient

MW = molecular weight

Which means that DMCO can be calculated by multiplying DMNO by 1.97. The reason this is important is that DMCO (and the pulmonary capillary blood volume) are usually calculated using a somewhat time-consuming multi-step process that requires that DLCO be at least measured at two different oxygen concentrations. By measuring DLCO and DLNO simultaneously, it is possible to calculate DMCO and then Vc:

with a single maneuver.

As usual however, things are never that simple. In particular, the assumption that any physiological process occurs infinitely fast is not something that correlates well with reality. Careful followup lab research has shown that θNO is actually much lower than expected, with a value of around 4.5. So why is there such a discrepancy?

First, the original researchers verified their DLNO findings by measuring DMCO via the traditional multi-step technique. The calculation of DMCO is quite sensitive to the value of 1/θCO that is used to calculate it (a well known and continuing problem). The DLNO researchers used Roughton and Forster’s original 1957 value which is known to be flawed (and was re-calculated by Forster in 1987). When DLNO is compared to DMCO using Forster’s updated 1/θCO value, a non-infinite θNO is found and is actually close to the 4.5 value derived from benchtop measurements.

Second, DLNO is essentially insensitive to the arterial oxygen concentration. NO binds directly with oxygenated hemoglobin to form methemoglobin. CO on the other hand competes with oxygen for binding sites on hemoglobin and its binding rate is therefore inversely proportional to arterial PO2.

Third, DLNO is relatively insensitive to pulmonary capillary blood volume which is partly because of how it binds to hemoglobin but also due to the details of the DLNO test. NO at high concentrations is toxic because of its rapid conversion to NO2. For this reason, an NO concentration of 40-45 ppm is usually used for the inspired gas mixture (and is considered reasonably safe because smokers inhale higher NO concentrations from cigarettes). This very small concentration of NO means that only tiny amounts of hemoglobin are involved in the uptake of NO and for this reason NO uptake is unchanged over a very broad range of hemoglobin concentrations and pulmonary capillary blood volumes.

Finally, even though NO’s reaction rate with hemoglobin is not infinitely fast, it is still substantially faster than that for CO. This means that the DMNO/DLNO ratio is substantially larger than the DMCO/DLCO ratio and that DLNO can in some circumstances be considered to be a reasonable substitute for DMNO (and DMCO). But reasonable substitute in this case means conceptually more than as a measurable property. The mathematical relationship between DMNO and DMCO depends greatly on which θCO and θNO constants are used, and there are at least seven different sets of constants for CO as well as several sets for NO. Unfortunately, this problem calls into question the results and conclusions of many research studies.

The value of DLNO is that it is primarily sensitive to the lung’s functional surface area and relatively insensitive to PaO2, hemoglobin concentration and pulmonary capillary blood volume. For this reason, a number of researchers have proposed using the DLNO/DLCO ratio rather than trying to use DLNO to estimate DMCO and Vc.

Since the DLNO/DLCO ratio combines diffusing capacity for two different gases with different physiological properties, it has the potential to be more informative than just DLCO or DLNO alone. DLNO, Vc and the DLNO/DLCO ratio have been studied and have provided insights into emphysema, pulmonary hypertension, diffuse interstitial disease, cystic fibrosis, obesity, systemic sclerosis, hepatopulmonary syndrome and the effects of methotrexate, bleomycin, exercise, and high altitude. Notably, the DLNO/DLCO ratio tends to rise when lung disease is present primarily because DLCO usually decreases more than DLNO. Interestingly DLNO/DLCO decreases during exercise and in some patients with sarcoid, and it’s predicted to decrease in the early stages of CHF (a confounding problem however, is that the DLNO/DLCO ratio decreases when DLCO and DLNO are measured below TLC so test quality is an important factor).

A key question however, has to be whether DLNO and the DLNO/DLCO ratio are clinically relevant. The answer is that although they can provide useful physiological information, it isn’t at all clear that DLNO significantly improves either the diagnosis or the monitoring of lung diseases at this time. There is a great deal of overlap in DLNO/DLCO ratios between dissimilar lung diseases and there are no longitudinal studies that would show changes in DLNO and the DLNO/DLCO ratio over time. The potential is certainly there but DLNO measurement techniques, normal ranges and derived values need to be standardized and there needs to be clear clinical guidelines in its use.

Note: For those who are feeling clinically adventurous Medisoft has two PFT systems (Hypair Compact, BodyBox 5500) that offer DLNO testing as an option.

The nitric oxide diffusing capacity (DLNO) can be measured using much the same techniques, equipment and mathematics that are used for DLCO testing. Initial research appeared to show that DLNO could be used to quickly and easily derive DMCO and Vc. Many researchers still follow this convention despite the fact that this has since been shown to be incorrect. The DLNO measurement however, is dominated by the membrane component of conductance and for this reason is more sensitive to the lung’s functional surface area than is DLCO, while DLCO is more sensitive to hemoglobin and the pulmonary capillary blood volume. These characteristics suggest that differences in DLCO and DLNO have the potential to provide useful diagnostic information.

UPDATE:  Standards for DLNO testing were released in the February 2017 issue of the European Respiratory Journal.  This is discussed in 2017 ERS DLNO Standards.

References:

Borland CRR, Higenbottam TW. A simultaneous single breath measurement of pulmonary diffusing capacity with nitric oxide and carbon monoxide. Eur Respir J 1989; 2: 56-63.

Borland C, Mist B, Zammit M, Vuylsteke A. Steady-state measurement of NO and CO lung diffusing capacity on moderate exercise in men. J Appl Physiol 2001; 90: 538-544.

Borland CDR, Dunningham H, Bottrill F, Vuylsteke A, Yilmaz C, Dane DM, Hsia CCW. Significant blood resistance to nitric oxide transfer in the lung. J Appl Physiol 2010; 108: 1052-1060.

Degano B, Mittaine M, Guenard H, Rami J, Garcia G, Kamar N, Bureau C, Peron JM, Rostaing L, Riviere D. Nitric oxide and carbon monoxide lung transfer in patients with advanced liver cirrhosis. J Appl Physiol 2009; 107: 139-143.

Farha S, Laskowski D, George D, Park MM, Tang WHW, Dweik RA, Erzurum SC. Loss of alveolar membrane diffusing capacity and pulmonary capillary blood volume in pulmonary arterial hypertension. Resp Research 2013; 4:6

Glenet SN, De Bisschop C, Vargas F, Guenard HJP. Deciphering the nitric oxide to carbon monoxide lung transfer ratio: physiological implications. J Physiol 2007 582.2: 767-775.

Hughes JMB, van der Lee I. The TL,NO/TL,CO ration in pulmonary test interpretation. Eur Respir J 2013; 41: 453-461.

Martinot JB, Mule M, de Bisschop C, Overbeek MJ, Le-Dong NN, Naeije R, Guenard H. Lung membrane conductance and capillary volume derived from the NO and CO transfer in high-altitude newcomers. J Appl Physiol 2013; 115: 157-166.

Meyer M, Piiper J. Nitric oxide (NO), a new test gas for study of alveolar-capillary diffusion. Eur Respir J 1989; 2: 494-496.

Meyer M, Schuster KD, Schulz H, Mohr M, Piiper J. Pulmonary diffusing capacities for nitric oxide and carbon monoxide determined by rebreathing in dogs. J Appl Physiol 1990; 68(6): 2344-2357.

Perillo IB, Hyde RW, Olszowka AJ, Pietropaoli AP, Frasier LM, Torres, A, Perkins PT, Forster RE, Utell MJ, Frmpton MW. Chemiluminescent measurements of nitric oxide pulmonary diffusing capacity and alveolar production in humans. J Appl Physiol 2001; 91: 1931-1940.

Roughton FJW, Forster RE. Relative importance of diffusion and chemical reaction rates in determining the rate of exchange of gases in the human lung, with special reference to true diffusing capacity of the pulmonary membrane and volume of blood in lung capillaries. J Appl

Physiol 1957; 11: 290 –302.

Sivova N, et al. Relevance of partitioning DLCO to detect pulmonary hypertension in systemic sclerosis. PLOS ONE 2013; 8(10): e78001.

Tamhane RM, Johnson RL, Hsia CCW. Pulmonary membrane diffusing capacity and capillary blood volume measured during exercise from nitric oxide uptake. Chest 2001; 120: 1850-1856.

van der Lee O, Zanen P, Grutters JC, Snijder RJ, van den Bosch JMM. Diffusing capacity for nitric oxide and carbon monoxide in patients with diffuse parenchymal lung disease and pulmonary arterial hypertension. Chest 2006; 129: 378-383.

van der Lee I, Zanen P, Stigter N, van der Bosch J, Lammers JWJ. Diffusing capacity for nitric oxide: reference values and dependence of alveolar volume. Respiratory Medicine 2007; 10: 1579-1584.

van der Lee I, Gietema HA, Zanen P, van Klaveren RJ, Prokop M, Lammers JWJ, van den Bosch JMM. Nitric oxide diffusing capacity versus spirometry in the early diagnosis of emphysema in smokers. Respiratory Medicine 2009; 103: 1892-1897.

Viart-Ferber C, Couraud S, Gormand F, Pacheco Y. Combined lung transfer of NO and CO in patients reveicing methotrexate or bleomycin therapy compared to normal subjects. Physiol J 2013; Article ID 539076.

Wheatley CM, Foxx-Lupo WT, Cassuto NA, Wong EC, Daines CL, Morgan WJ, Snyder EM. Impaired lung diffusing capacity for nitric oxide and alveolar-capillary membrane conductance results in oxygen desaturation during exercise patients with cystic fibrosis. J Cystic Fibrosi 2011; 10: 45-53.

Zavorsky GS, Quiron KB, Massarelli PS, Lands LC. The relationship between single-breath diffusion capacity of the lung for nitric oxide and carbon monoxide during various exercise intensities. Chest 2004; 125: 1019-1027.

Zavorsky GS, Kim DJ, McGregor ER, Starling JM, Gavard JA. Pulmonary diffusing capacity during exercise in morbid obesity. Obesity 2008; 16: 2431-2438.

Zavorsky GS. No red cell resistance to NO? I think not! J Appl Physiol 2010; 108: 1027-1029.

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

Recently I was trying to explain the effect of altitude on blood oxygenation to somebody with IPF. They had observed that their oxygen saturation was fairly normal at sea level but that they needed to use their supplemental O2 when they went up to 2000 feet and didn’t understand why such a low altitude made that much of a difference. I don’t think I did very well with the explanation since at the time I was limited to only text and I much prefer pulling out diagrams and waving my hands in the air.

The place to start is with the alveolar air equation.

Where:

PAO2 = partial pressure of O2 in the alveoli

FiO2 = fractional concentration of O2

P_B = barometric pressure

P_H20 = partial pressure of water vapor in the alveoli

PaCO2 = partial pressure of CO2 in the arteries

RER = respiratory exchange ratio (VCO2/VO2)

When normal values are plugged into the alveolar air equation it looks like this:

An important point is that when air is inhaled into the lung oxygen is diluted by the water vapor and carbon dioxide that are already there. The partial pressure of oxygen will vary with atmospheric pressure but the partial pressure of water vapor and carbon dioxide are relatively fixed values. Atmospheric pressure of course decreases with altitude.

For the same reason, the partial pressure of oxygen in air and the alveoli also decreases as altitude increases.

But because water vapor and carbon dioxide are relatively constant, the partial pressure of alveolar oxygen decreases faster than the partial pressure of O2 in air.

This means that although the atmospheric pressure at 2000 feet is 7% less than at sea level, alveolar PO2 is 11% less.

However, not every individual’s arterial PCO2 and respiratory exchange ratio are “normal” and differences can either increase or decrease the alveolar PO2. For example, an elevated PaCO2 decreases PAO2 while a reduced PaCO2 increases PAO2.

The respiratory exchange ratio is affected both by diet and activity. A high protein diet tends to decrease RER while a high carbohydrate diet or activity tends to increase RER.

The alveolar air equation only addresses the oxygen concentration in the alveoli. To be of any use oxygen needs to get into the bloodstream. Although diffusing capacity is a measurement of gas exchange efficiency it is not possible to take the DLCO and PAO2, and then predict arterial PO2 (PaO2) with any accuracy. Nor is it possible to measure the arterial oxygen saturation (SaO2) with a pulse oximeter and then calculate PaO2. This is because pulse oximeter accuracy is only +/- 3% and blood pH also affects the oxygen dissociation curve.

PaO2 must therefore be measured from an arterial blood sample. When this is done you can calculate the difference between alveolar and arterial PO2 (known alternately as the A-a gradient or PAaO2). The A-a gradient rises with age and at sea level the normal value is approximately:

Results from several studies however, indicate that the A-a gradient decreases with altitude. The decrease is small, only 0.02 mm Hg per mm Hg decrease in atmospheric pressure which is roughly 1 mm Hg per 2000 foot increase in altitude.

Using these formulas and ostensibly normal values for a 60 year old, PAO2, PaO2 and SaO2 would be:

Altitude (ft):	PAO2:	A-a Gradient:	PaO2:	SaO2:
0	101.8	19.0	82.8	96.0%
2000	90.7	18.0	72.7	94.6%
4000	80.0	17.0	63.0	89.7%
6000	70.1	16.0	54.1	87.8%
8000	60.7	15.0	45.7	81.5%
10000	52.1	14.0	38.1	72.0%

But the oxygen saturation values at the higher altitudes seem excessively low and this is because one of the adaptations to altitude is an increase in ventilation. This causes PaCO2 to decrease and pH to increase. The decrease in PaCO2 increases PAO2. The increase in pH shifts the oxygen dissociation curve leftwards which means that the SaO2 for a given PaO2 also increases. At 10,000 feet with a PaCO2 of 30 and pH of 7.50 (much more extreme values such as pH of 7.60 and PaCO2 of 20 have been measured in mountain climbers at extreme altitudes), PAO2 would be 64, PaO2 would be 50, and SaO2 would be 92%.

Even a modest change in PaCO2 to 35 without any corresponding change in pH makes a significant change in oxygenation.

Altitude (ft):	PAO2:	A-a Gradient:	PaO2:	SaO2:
0	107.8	19.0	88.8	98.0%
2000	96.7	18.0	78.7	95.6%
4000	86.0	17.0	69.0	93.8%
6000	76.1	16.0	60.1	90.9%
8000	66.7	15.0	51.7	86.3%
10000	58.0	14.0	44.0	79.6%

Airplanes that travel at 30,000 to 40,000 feet are usually pressurized to an equivalent altitude of 6000 to 8000 feet and the lower limit of normal for the SaO2 of airplane travelers is usually considered to be between 89% and 91%.

Everybody’s arterial oxygen decreases as altitude increases. The decrease in the availability of oxygen with increasing altitude is due to the decrease in atmospheric pressure but is also influenced by the relatively constant amounts of water vapor and carbon dioxide in the lung. Alveolar O2 therefore decreases faster than would be expected for a simple change in atmospheric pressure. Increased ventilation is a compensatory mechanism that causes changes in PaCO2 and pH and makes oxygen more available. Lung disease tends to decrease the efficiency of gas exchange which increases the A-a gradient and may also limit an individual’s ability to increase ventilation and compensate for hypoxia. For these reasons sometimes only modest changes in altitude are enough to make a significant change in SaO2.

References:

Crapo RO, Jensen RL, Hegewald M, Tashkin DP. Arterial blood gas reference values for sea level and an altitude of 1,400 meters. Am J Respir Crit Care Med 1999; 160: 1525-1531

Ruppel GL. Manual of pulmonary function testing, 8^th edition, 2003.

Vincent J, Hellot MF, Vargas E, Gautier H, Pasquis P, Lefrancois R. Pulmonary gas exchange, diffusing capacity in natives and newcomers at high altitude. Repir Physiol 1978; 34: 219-231.

Wagner PD, Gale GE, Moon RE, Torre-Bueno JR, Stolp BW, Saltzman HA. Pulmonary gas exchange in humans exercising at sea level and simulated altitude. J Appl Physiol 1986; 61: 260-270.

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

My lab is in the final stages of a software update that will allow for electronic signing of our reports. This has been a long and slow process partly because the release date of the software got pushed back several times but mostly because a wide variety of different hospital departments and sub-departments have had to be involved.

In all the years that I’ve had computers in the pulmonary function lab I’ve never gone through a software update that was either as easy as expected or occurred within the original schedule. This includes the time when all we had was a single IBM PC/AT with a 40 megabyte hard drive, no network and the only people that cared we were going through an update was ourselves. Since we now have a dozen networked PCs located in two different building on-campus as well as three off-site locations using an IS-managed SQL server and HL7 interface I didn’t have any expectations for a speedy update and so far I have not been disappointed.

This time because the update revolves around electronic signing the hospital’s Health Information Management (HIM, i.e. Medical Records) department has been significantly involved. Among other things this has led to HIM reviewing all of our reports and requiring changes to bring them up to hospital standards. To some extent this make sense since, for example, they require that patient identification be exactly the same on all reports from all departments (same fields, same locations).

However, they also questioned some of the terminology used on our test reports. We’ve used the default test names that were in our report format editor (yes, we’re that lazy) and until they were brought to our attention I never really thought how odd some of them were. In particular, some of the terms used for the diffusing capacity didn’t make a lot of sense. For example, DLCO corrected for hemoglobin was DsbHb and DLCO/VA was reported as D/Vasbhb. To some extent I understand where these names came from but the reality is that they are in part holdovers from the past, in part they come from a need to keep names short so they fit in what space is usually available on reports, and in some cases they were probably created by programmers who hadn’t the slightest idea what the correct nomenclature should have been.

Note: Dsb likely comes from a time when you needed to differentiate between the results of different types of DLCO tests (steady-state and single-breath). Since there hasn’t been a test system built for at least 40 years that could perform a steady-state DLCO, the need to make this distinction is long since past.

We explained what the acronyms meant, agreed that they probably needed to be updated and included a list of ATS/ERS accepted acronyms. HIM however, decided that they didn’t meet their standards and took it upon themselves to “fix” them without our help. Here is what they “fixed”:

Old:	New:
Dsb	DLCO/SB
DsbHb	DLCOcorr
VAsb	VA/SB
Vinsp	VI
D/VAsbHb	DL/VA/SB/Hgb

They said their decisions were based on PubMed and Fishman’s Pulmonary Diseases and Disorders, 4^th Edition, 2007. Being somewhat snide I’d say it was more likely that somebody Googled it (or if I was feeling particularly snide I would have said they Binged it) and took the first listing that came up.

The fact is that over the history of pulmonary function testing many researchers and educators in different times and different places have used different terms for the same thing. The profusion of test names that occurred in the early 1950’s is in large part why the British Thoracic Society convened a special meeting in 1956 to standardize terminology. That hasn’t prevented a certain amount of originality and ingenuity (not to mention stubbornness and laziness) from creeping into our nomenclature over the years, however.

The ATS/ERS statements on standardization that were published in 2005 each include an identical list of accepted acronyms. The ones that in particular apply to DLCO are:

DL,CO	Diffusing capacity
DM	Membrane diffusing capacity
Hb	Hemoglobin
VA	Alveolar volume
VI	Inspired volume
DL,CO/VA	KCO

Note: Interestingly, the ATS/ERS does not have any terminology for hemoglobin-adjusted DLCO values. I suspect this is because the ATS/ERS recommends that the predicted DLCO be adjusted for hemoglobin, not the observed. No lab or manufacturer I know of follows this recommendation and it is the observed value for hemoglobin that is almost universally adjusted instead. That leaves it up to users and manufacturers to come up with acceptable terms and that means we end up with acronyms like DLCOcorr, DLCOHb and DLCOadj.

The terminology for spirometry and lung volumes is fairly standard world-wide and you won’t see any notable differences between glossaries in these areas. The notation used for gas pressures and concentrations is also reasonably well standardized although there does seem to be a lack of consensus about the use of commas and subscripts. Specifically, depending on which glossary you look at the fractional concentration of oxygen can be expressed as:

FiO2

FIO2

Fi,O2

Fi_O2

The least amount of consensus can be found in diffusing capacity. Depending on the glossary results can be expressed as:

DCO

DLCO

DlCO

DL,CO

DL_CO

Dl_CO

Except for those who say that diffusing capacity should really be called transfer factor and insist that the proper terminology is actually:

TLCO

TL,CO

TL_CO

There are good arguments for and against any particular style of terminology. I understand the appeal of using subscripts and commas to make precise (although occasionally somewhat esoteric) distinctions but at the same time results have to be printed on paper or viewed on a computer screen and the space required to display a term and its readability are just as important, if not more so (I’d say Down With All Subscripts! but that’s somewhat redundant, isn’t it?). Precision is important but there is also a limit as to how far we have to carry it. For example, we already accept that some values are reported as being corrected for BTPS and some for STPD and that it isn’t necessary to include this information in our terminology.

The fact is that we can read all the variations of a single acronym or term and although we sometimes have to shift mental gears we know what they mean. For this reason my suggestion would be that for any term there should be a precise “scientific” version that should be used in journal articles and textbooks (we can let the researchers and educators argue over subscripts and commas) and a simplified “readable” version meant for reports.

In the meantime though, when it comes to arguing with HIM, we’ll use the terminology lists from the ATS/ERS standardization articles. I don’t agree with all of what’s on these lists, and we’ll still have to argue about which term to use for hemoglobin-adjusted DLCO but it’s got to be better than having DL/VA/SB/Hgb on a report.

Each profession has its own language and learning the words and what they mean is a key part of understanding that field. For a variety of reasons pulmonary function terminology has a certain amount of variability that has the potential to be occasionally misleading or at least difficult to understand. I don’t think we’re quite at the point where we need to convene a special meeting of the ATS/ERS to lock down terminology, but I’d like to see all pulmonary function terminology addressed and updated in the next set of standards.

A final point is that the amount of time we need in order to prepare for a software update has gotten completely out of hand. We’ve been having meetings of one kind or another with ourselves, the manufacturer, and the different hospital departments and sub-departments just about every two weeks for the last eight months. And we’re still not ready to go live with the update.

This problem is not unique to my hospital either since I’ve heard similar complaints from other institutions around the country. I realize that the hospital environment is completely different from what it was 25 or 30 years ago when every department pretty much went its own way. I also realize that this “simple” software update impacts more departments than just ourselves. But the real reason this process has taken so long is that both hospitals and manufacturers continue to re-invent the wheel and this means that every time we want to go through an update we have to start from scratch. None of us, and that includes labs, hospitals and manufacturers, can afford the drain on resources this kind of process is taking. It is long past the time that standards (technical, procedural and legal) were developed and adhered to by everybody concerned.

References:

Brusasco V, Crapo R, Viegi G. ATS/ERS Task force: Standardisation of pulmonary function testing. Standardisation of spirometry. Eur Respir J 2005; 26: 319-338.

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

Brusasco V, Crapo R, Viegi G. ATS/ERS Task force: Standardisation of pulmonary function testing. Standardisation of the single-breath determination of carbon monoxide uptake in the lung. Eur Respir J 2005; 26: 720-735.

Cotes JE, Chinn DJ, Miller MR. Lung Function, Sixth Edition, Blackwell, 2006.

Ruppel GL. Manual of pulmonary function testing, Eighth edition, Mosby, 2003.

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

There are at least a half dozen companies that use an ultrasonic flowmeter in their spirometer. The first patent for an ultrasonic flowmeter was made in the 1970’s but it wasn’t until the 1990’s that the first ultrasonic spirometers came to market. The basic idea is fairly simple and that is to measure the transit time of ultrasonic pulses through flowing gas. Pulses that travel in the same direction the gas is flowing will take less time to travel a given distance, while pulses traveling against the direction of gas flow take a longer time.

This particular measurement process is called time-of-flight (as opposed to doppler shift) and has a relatively flat flow/signal curve and frequency response. An early design of this kind of flowmeter had the ultrasonic transducers sitting in the flow of gas, but this both impedes the flow of gas and is hard to clean. A transverse design was developed that put the transducers outside the path of gas flow and this configuration has been used in all ultrasonic spirometers.

The transit time of an ultrasonic pulse depends on the distance between the two transducers, the angle of the pulses relative to the direction of gas flow, and the speed of sound. When gas is flowing as shown in the diagram, the transit time from transducer A to transducer B is:

and from B to A is:

Where:

D = distance between transducer A and B

S = speed of sound

V = gas velocity

cos(C) = cosign of the angle between the pulses and gas flow

One problem with these formulas is their dependence on the speed of sound which can be affected by gas temperature, gas composition and gas pressure. Fortunately these formulas can be rearranged and simplified to:

where:

Δt = the difference in A-B transit times

t_avg = the average transit time

and when this is done, the measurement of velocity is insensitive to the speed of sound.

An important point is that ultrasonic flowmeters measure the average gas velocity between transducers, not the gas flow rate. In order to derive flow rate not only must the geometrical cross-sectional area of the flowmeter must accounted for, but the flow profile through the flowmeter as well.

Because of shear effects near the wall of any tube that gas flows through the velocity of gas is lower near the edge and in the center. Some spirometer manufacturers maximize the central area the ultrasonic pulses travel through by having a rectangular cross-section instead of circular.

Although ultrasonic flowmeters are theoretically linear over a very broad range of flows, like other types of flowmeters they can be affected by resistance and turbulence. This limits how small (or large) they can be and at least one manufacturer sells a range of different sized ultrasonic flowmeters for small and large animal research.

For an ultrasonic flowmeter to work correctly the ultrasonic transducers need to be carefully matched in terms of their transmit/receive frequency. Ultrasonic transducers tend to be sensitive to temperature and their resonant frequencies can change when temperature changes. For this reason some ultrasonic spirometers are heated, not for BTPS correction but in order to maintain a constant transducer temperature.

One factor that limits the sampling frequency (number of measurements per second) is reflections and echoes. These do not necessarily interfere with the measurement of transit time since the primary pulse is the first pulse received and for this reason secondary pulses can be ignored, but enough time has to pass for echoes to die down before another pulse can be transmitted. Even so, sampling frequencies are usually over 100 hz which is more than sufficient to accurately measure changes in expiratory flow.

Finally, a pulse is not a single acoustic wave but a series of them, usually over a period of 200-300 microseconds, with a characteristic rise and fall time. This means that the accurate measurement of pulse timing depends on recognition of the entire pulse envelope rather than an individual wave. Fortunately, this kind of electronic pattern recognition was developed decades ago for sonar and radar.

Several studies have shown that ultrasonic spirometers compared well with existing test systems, and that they are both accurate and stable, even when calibration was intermittent and separated by relatively large time intervals. Routine calibration is still recommended however if for no other reason than insuring that the equipment is operating correctly.

Some manufacturers line the interior of the flowmeter with plastic (that is also transparent to the ultrasonic frequency used by the device) so they can be sterilized, but do recommend the use of standard barrier filters. Others use a disposable mouthpiece insert that keeps the keeps the interior of the flowmeter clean.

Interestingly, ultrasonic flowmeters are found mostly in simple spirometry systems. After a fair amount of search I have been able to find only three test systems capable of measuring lung volumes and DLCO (which also interestingly enough use an ultrasonic molar mass gas analyzer, but that’s a completely different subject) and two plethysmographs that use an ultrasonic flowmeter but no exercise test systems. The reasons for this are unclear. There doesn’t appear to be any technical reason why ultrasonic flowmeters can’t be used in sophisticated lab test systems although it’s remotely possible that there are some acoustical interactions with the valves and tubing needed for more complex systems that is undocumented. On the other hand the patents for ultrasonic flowmeters are held by only a small number of companies that just may not be interested in that segment of the pulmonary function testing market.

Ultrasonic flowmeters appear to be well suited to inspiratory and expiratory flow measurements since they appear to be linear, accurate, stable and mostly insensitive to temperature, humidity and gas composition. For these reasons they seem to be well suited for office spirometry and this also appears to be their primary market.

References:

Buess C, Pietsch P, Guggenbuhl W, Koller EA. Design and construction of a pulsed ultrasonic air flowmeter. IEEE Trans Biomed Eng 1986; 33(8): 768-774.

Mortimer KM, Fallot A, Balmes JR, Tager IB. Evaluating the sue of a portable spirometer is a study of pediatric asthma. Chest 2003; 123: 1899-1907.

Skloot GS, Edwards NT, Enright PL. Four-year calibration stability of the EasyOne portable spirometer. Respir Care 2010; 55(7): 873-877.

Walters JAE, Wood-Baker R, Walls J, Johns DP. Stability of the EasyOne ultrasonic spirometer for use in general practice. Respirology 2006; 11: 306-310.

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

Sooner or later we all get lucky and find ourselves able to replace older equipment. When you have equipment that’s so old it can’t be repaired (either because the manufacturer no longer supports it or because the manufacturer no longer exists), you’d think this would be a no-brainer but money is always in short supply. I’ve often had to try to keep equipment running long past its expected life time and was only allowed to replace it when it finally broke beyond all hope of repair.

One of the reasons to perform biological QC is so that you can recognize changes in the equipment that don’t appear during a calibration. It also a useful (and recommended) way to assess new test equipment. So what happens when you finally get that new test system and your results are substantially different from what they were before?

I was recently contacted by the manager of an employee health service that had replaced their 18 year old spirometer with a brand-new one. When using their new spirometer they had found their biological QC results coming out noticeably lower (-9%) than they had gotten from their old spirometer and I was asked if I could help them determine why.

My first question was whether or not they were using the same 3 liter syringe to calibrate the different spirometers. Once I found out this was the case I then asked them to use the 3 liter syringe in test mode. The results from this were actually very informative. The old spirometer showed an average FVC of 3.24 liters and the new spirometer showed an average FVC of 3.06 liters.

Both spirometers were flow-based systems although the older one used a pneumotach and the newer one used an ultrasonic sensor. I did not expect the FVC for either spirometer to be exactly 3 liters and this is because the spirometer software always performs a temperature correction on the results. The results showed that the older spirometer was applying a correction factor of 1.08 and the newer spirometer was using 1.02 which is approximately a 6% difference.

Spirometer results need to be corrected for temperature because exhaled air cools as it leaves the body and when it does it contracts. This fact was recognized quite early and Hutchinison’s 1846 spirometer included a thermometer for this reason. The early correction factors were actually too simplistic since they didn’t take into account how much water vapor contributed to the change in volume. This wasn’t recognized until about half a century later and the formula for BTPS derived. Specifically:

where:

V_ATP = volume at ambient temperature and pressure

P_B = barometric pressure

P_H2O = partial pressure of water vapor

t = spirometer temperature

37 = body temperature

P_H20 in turn can be estimated from:

This worked well when spirometers were all volume-displacement water-seal types with a lot of thermal mass and when all that was measured was the vital capacity (remember, the FEV1 didn’t exist before 1950). Even so, with repeated spirometry efforts spirometer temperature has been shown to increase up to 4 degrees C, which means the temperature of the spirometer itself needs to be monitored, not just room temperature.

Temperature correction for flow sensors is much more complicated. This is partly because they tend to have a lot less thermal mass, but also because exhaled air flows through them relatively rapidly and doesn’t have much time to be as affected by their temperature. Like a volume-displacement spirometer however, a flow-sensor’s temperature rises with repeated spirometry efforts and this can affect results if it is not corrected for. Exhaled air temperature however, also changes throughout exhalation so a single correction factor is actually too simplistic.

Measuring air temperature during exhalation (dynamic correction) would seem to be a good idea but is actually quite difficult. In particular the thermal mass and response time of a temperature sensor needs to be carefully characterized and these factors change over time. For this reason, there are almost no flow-based spirometry systems that are capable of measuring exhaled air temperature and most manufacturers make assumptions about it instead.

The ATS/ERS 2005 statement on spirometry does discuss some of the issues involved in BTPS and temperature correction, but it does not present any clear solutions nor are there any precise specifications. This means that temperature correction is left up to the equipment manufacturers.

There isn’t anything necessarily wrong with this, since the manufacturers are the ones who should know their equipment best. The manufacturer of the older spirometer went out of business at least a decade ago however, and any manual that came with that system has long since disappeared, so exactly how temperature correction is applied is unknown. I did some digging on the website for the manufacturer of the new spirometer and found that a correction factor of 1.02 is applied to exhaled air regardless of room temperature or sensor temperature. This may be more or less correct but it also seems to be an overly simple response to a complex problem.

So what, if anything, can be done about the discrepancy in spirometry results from the two systems?

About two-thirds of the difference appears to be associated with the difference in temperature correction factors. This is hard-wired into each system’s software and cannot be adjusted. Even if it was possible to adjust the temperature correction factor for the new spirometer to match the old spirometer this isn’t the right way to fix the problem. And that’s only if you assume it actually is a problem. It is a problem in the sense that new results don’t match old results, but it’s also possible that the newer results are more accurate and if that’s the case, it isn’t a problem.

The remaining difference (~3%) is within ATS/ERS specifications. The older spirometer was manufactured in 1997 and uses a pneumotach. Pneumotachs are well understood and characterized but that’s not the same as saying they are 100% accurate. Pneumotachs rely on analog circuitry which is subject to drift and the flow signal needs to be corrected in software for alinearity. Ultrasonic flow sensors are primarily a digital technology and, theoretically at least, are less likely to drift and more likely to be linear across a wide range of flows. Other than that it isn’t possible to say which of the two systems is more accurate.

Since temperature correction can have a significant effect on test results one interesting question this brings up is how temperature correction was applied in the studies that generate the reference equations we use. Most labs that I know use the NHANESIII spirometry reference equations. When I went to the original research paper (Hankinson et al, 1999) I found that the specifications for the volume-displacement spirometry systems used in the study were located in an earlier paper (Hankinson et al, 1991). Neither paper however, explained how temperature correction had been performed other than to state that spirometry was performed according to the 1994 ATS standards. The language in the ATS 1994 statement on spirometry regarding BTPS correction is essentially identical to the 2005 ATS/ERS statement, and other than saying that temperature correction is a good idea, there are no requirements or specifications. The earlier paper (Hankinson et al, 1991) also stated that the spirometers had been “independently tested” and referred to another research paper (Nelson et al, 1990) but that article specifically stated that BTPS correction was not tested.

So was the NHANESIII spirometry data corrected for BTPS? Probably yes, but exactly how temperature was measured and how a temperature correction was applied is not clear in any way. Does this mean the NHANESIII reference equations are inaccurate? Probably not, or at least not any more than any other set of reference equations, but I will admit I have some reservations about them I didn’t have before.

The effect that temperature has on measuring exhaled volume has been known and understood for a long time, but applying it is both technically difficult and inconsistently performed. Since an error in measuring (or estimating) spirometer temperature of 1 degree centigrade causes an error of approximately 0.5% in measured volume it is easy to say that the ATS/ERS spirometry standard should be more precise about how temperature correction should be performed. Given our limited understanding (after all this time!) of the temperature characteristics of flow sensors and volume-displacement spirometers this isn’t realistic. Even if the equipment side of temperature correction was better understood the BTPS calculation assumes that patient body temperature is 37 degrees centigrade; that inhaled air has been warmed to that temperature before being exhaled; and that exhaled air is a consistent temperature. These assumptions are usually not true and this means that temperature factors will always cause a certain amount of error in our test results and that both the amount and direction of this error is unknown.

Over the years I’ve gone through numerous changes in equipment and reference equations. Each time this has occurred there has been a discontinuity (sometimes small, sometimes large) between newer and older test results. There is no easy way to reconcile these differences and usually the best you can do is to keep moving forward and put them behind you. I’d like to think that we improve every time this happens and to some extent I suppose we do, but when I dig into basic problems like temperature correction all too often I find that not much has really changed.

Kudos to the manager of the employee health service that contacted me for doing the QC, paying attention to the results and for worrying about them.

References:

American Thoracic Society. Standardization of spirometry. 1994 Update. Am J Resp Crit Care Med 1995; 152: 1107-1136.

Brusasco V, Crapo R, Viegi G. ATS/ERS task force: Standardisation of lung function testing. Standarisation of spirometry. Eur Respir J 2005; 26: 319-338.

Cotes JE, Leathart GL. Lung Function. Assessment and application in medicine. 6^Th Edition. Blackwell Scientific Publications, 1993.

Gilliland FD, Linn W, Rappaport E, Avol E, Gong H, Peters J. Effect of spirometer temperature on FEV1 in a longitudinal epidemiological study. Occup Environ Med 1999; 56: 718-720.

Hankinson JL, Viola JO. Dynamic BTPS correction for spirometric data. J Appl Physiol 1983; 55(4): 1354-1360.

Hankinson JL, Bang KM. Acceptability and reproducibility criteria of the American Thoracic Society as observed in a sample of the general population. Am Rev Resp Dis 1991; 143: 516-521.

Hankinson JL, Viola JO, Petsonk EL, Ebeling TR. BTPS correction for ceramic flow sensor. Chest 1994; 105(5): 1481-1486.

Hankinson JL, Odencrantz JR, Fedan KL. Spirometric reference values from a sample of the the general U.S. population. Am J Respir Crit Care Med 1999; 159: 179-187.

Johnson LR, Enright, PL, Voelker HT, Tashkin DP. Volume spirometers need automated internal temperature sensors. Am J Respir Crit Care Med 1994; 150: 1575-1580.

Linn WS, Solomon JC, Gong H, Avol EL, Peters JM. Temperature standardization of multiple spirometers. J Occup Environ Med 1998; 40: 148-152

Madan I, Bright P, Miller MR. Expired air temperature at the mouth during a maximal forced expiratory maneuver. Eur Respir J 1993; 6: 1556-1562.

Nelson SB, Gardner RM, Crapo RO, Jensen RL. Performance of contemporary spirometers. Chest 1990; 97: 288-297.

Zawadski DK, Lenner KA, McFadden Jr. ER. Comparison of intraairway temperatures in normal ans asthmatic subjectes after hyperpnea with hot, cold and ambient air. Am Rev Resp Dis 1988; 138: 1553-1558.

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

A lab manager recently emailed me and asked my opinion about whether it was okay to use generic mouthpiece filters on their test systems. They had asked the same question of their equipment manufacturer and received the following statement (parts of which have been redacted by me):

“The [model number] PFT system was designed/tested/certified using the [manufacturer’s] filter. While other “off-label” filters may fit our devices, they have never been tested or approved for use by [the manufacturer]. The precision and accuracy of our devices could be compromised by using different type filters. It is our recommendation that you continue to use the [manufacturer’s] approved filters with your PFT equipment.”

Since I doubt the manufacturer has tested their equipment with any other mouthpiece filters than those they sell this is in some ways a true statement. Having said that, it is also a statement designed to sow fear, uncertainty and doubt (FUD) in the minds of their customers about a subject that is relatively straightforward.

The human respiratory tract is a potential source of particles in the 0.1 to 20 micron range, particularly when coughing but even to some extent during quiet breathing. Mouthpiece filters are barrier filters and intended to prevent these particles from getting into PFT equipment. Filter manufacturer’s claims are very similar and usually state a “Bacterial filtration efficiency: > 99.999% and Viral filtration efficiency: > 99.99%”. In one sense this statement is somewhat disingenuous because mouthpiece filters are not tested with bacteria or viruses (which have diameters as small as 0.03 microns) directly, but are instead tested with aerosols generated by a nebulizer.

A HEPA (High Efficiency Particle Absorption) filter is a true bacterial filter and to meet standards it must filter out 99.97% of all particles 0.3 microns or larger. Mouthpiece filters are not HEPA filters, partly because of cost but far more importantly because HEPA filters have a lot of resistance to air flow. A HEPA filter is a sieve mouthpiece with opening sizes that prevent particles above a specific size from passing through. Mouthpiece filters instead work by impaction and electrostatic attraction. Larger particles are captured by impacting or otherwise being intercepted by the filter fibers and the fibers usually also have an electrostatic charge that attracts smaller particles.

Nelson Labs (Utah), which does much of the mouthpiece filter testing in the USA, describes their Increased Bacterial Filtration Efficiency (BFE) test features as follows:

“The test is conducted using Staphylococcus aureus as the challenge organism. A liquid suspension of S. aureus is aerosolized using a nebulizer and delivered to the filtration medium at a constant flow rate of 30 liters per minute (LPM).

“The aerosol droplets are collected in all-glass impingers (AGIs) in parallel. The challenge is delivered for a 1-minute interval and sampling through the AGIs is conducted for 2 minutes to clear the aerosol chamber. The titer of the assay fluid is determined using standard plate count and/or membrane filtration techniques. The number of bacterial aerosol droplets contacting the filter medium is determined by conducting challenge controls without filter medium in the test system. Challenge controls are maintained a 1 x 10^6 colony forming units (CFU) with a mean particle size (MPS) of 3.0 +/- 0.3 microns. This allows filtration efficiencies to be reported up to >99.9999%”

Since any bacteria or viruses exhaled by the human respiratory tract are contained within liquid droplets this test does have a basis in fact, but what is being tested is the ability of mouthpiece filters to remove particles that are much larger than individual bacteria or viruses.

Mouthpiece filters come in a variety of shapes, sizes and there are probably differences in the actual filter material but the two factors that are most important are resistance and deadspace volume. The ATS/ERS standards for spirometry states that the total resistance of flow in a spirometer should not be greater than 1.5 cm H2O/L/sec. Since the flow resistance of PFT equipment is more-or-less fixed, in order to keep the overall system resistance low, the resistance of mouthpiece filters must be kept low as well.
In reviewing different manufacturer’s mouthpieces I’ve found a range of resistances from 0.08 cm H2O/L/sec to 0.75 cm H2O/L/sec, with most clustering around 0.45 cm H2O/L/sec. Resistance is not the same at all flow rates however, and in fact increases with increasing flow rates. For this reason resistance should be stated at the maximum flow specified in the ATS/ERS spirometry standards (14 L/sec). I’ve noticed that the lowest filter resistances also tended to be specified at flow rates well below 14 L/sec (in one case at 0.5 L/sec) and this is probably misleading.

I’ve found filter deadspaces ranging from 35 to 75 ml. I would have thought there would be a relationship between deadspace volume and filter resistance because the way to keep resistance low is by increasing surface area which in turn requires a larger volume. What I found instead was that that some filters with low deadspace had a low resistance and some filters with a larger deadspace also had a higher resistance. The differences in resistance and deadspace may be due to the choice of filter medium rather than surface area, but given the way in which resistance was often reported this isn’t as clear as it might be.

Filter mouthpieces can affect test results. A couple of studies showed slight but statistically significant decreases in FVC, FEV1 and SGaw when a mouthpiece filter was used compared to when it wasn’t. The differences were quite small however, and the studies concluded that any decrease in measured values was not clinically significant.

The most important question however, is whether mouthpiece filters actual prevent equipment contamination and the cross transmission of respiratory infections. More than one study has showed that without mouthpiece filters spirometers are capable of rapidly becoming contaminated. It is much less clear whether or not contaminated equipment is capable of cross-infecting patients but the potential is clearly there. Even if patients aren’t at risk there have been reports in the past of technicians who likely acquired infections (including tuberculosis) from contaminated equipment.

The evidence concerning the ability of mouthpiece filters to prevent equipment contamination is a bit more equivocal. Several studies have indicated there is no difference in contamination rates with or without filter mouthpieces but there are also several studies that showed no contamination when a filter was used compared to when it wasn’t. Strictly speaking there is no overwhelmingly clear evidence that mouthpiece filters prevent equipment contamination but comparison of these studies is difficult because of the different methodologies that were used.

This may also be in part because the Bacterial Filtration Efficiency test used to assess mouthpiece filters has some significant limitations. The test is performed at a flow rate of 30 LPM which is only 0.5 L/sec. The peak flows obtained during spirometry are usually much higher than this and it is not clear that efficiency ratings obtained at a low flow rate extrapolates in any way to higher flow rates.

Nevertheless, all the standards for clinical, office and occupational spirometry that I’ve been able to find recommend the use of mouthpiece filters. My personal opinion is that even though mouthpiece filters may not completely prevent equipment contamination, they certainly reduce it. At least one study has showed it was possible to prevent contamination and cross-infection without filter mouthpieces but this was only possible through regular and diligent cleaning and disinfection that had a cost in technician time and machine down-time well above what would have been spent on filters.

Finally, one additional reason to use filter mouthpieces other than preventing contamination is that when they are upstream of flow sensors they act as diffusers and should act to improve flow laminarization. This may improve the accuracy of flow sensors but this is a personal observation and to my knowledge is not something that has been studied. Even so, it is probably a best practice to calibrate spirometer and flow sensors using the same filter that is being used for patient testing.

Manufacturer “approved” filters are usually more expensive than “off-label” and most equipment manufacturers have good reasons to want to sell their “approved” filters. Their manuals and websites often contains language that implies that their equipment works better with their “approved” filters but since I’ve seen no information from any manufacturer that explains why “off label” filters should not be used with their equipment this is mostly FUD. Interestingly, details concerning the resistance or deadspace of “approved” filters is often hard to find (when it is available at all). In addition, I’ve noticed some misleading information such as a claim that filters were 100% effective (not possible for even HEPA filters) or that resistance was 0.10 cm H2O at 0.5 L/sec (what was it at 14 L/sec?). One final point is that I doubt whether any PFT equipment manufacturer actually manufactures their “approved” mouthpiece filters and it is far more likely that they are manufactured by the same companies that make the “off label” filters.

So, rather than FUD, mouthpiece filters should instead be evaluated on:

• Does it fit the equipment?
• Has their efficiency been tested?
• Has their resistance been measured at (or at least near) 14 L/sec?
• Deadspace.
• Can the filter be used for routine spirometry without any additional adaptors?
• Can the filter accommodate more than one size of flanged rubber mouthpiece?
• Is the price (and shipping costs) right?

Mouthpiece filters may differ from one another in resistance, deadspace volume and filter material but most of them have similar BFE filtration capabilities. Any differences that occur when “off label” filters are used are far more likely to affect patient test results due to differences in resistance and deadspace than they are to affect any manufacturer’s test equipment. I have used filter mouthpieces for as long as they have been available. Admittedly there have been periods where I have used manufacturer-approved filters but those times were either when they were priced competitively or for one short interval, where I couldn’t find any “off label” filters that fit our equipment. Most of the time however, I have used “off label” filters and see no reason for any other PFT lab not to do the same.

 

References:

Bracci M, Strafella E, Croce N, Staffolani S, Carducci A, Verani M, Valentino M, Santarelli L. Risk of bacterial cross infection associated with inspiration through flow-based spirometers. Am J Infect Control 2011; 39(1): 50-55.

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.

Burgos F, Torres A, Gonzalez J, Puig de la Bellacasa J, Rodriguez-Roisin R, Roca J. Bacterial colonization as a potential source of nosocomial respiratory infections in two types of spirometer. Eur Respir J 1996; 9: 2612-2617.

Canakis AM, Ho B, Ho S, Kovach D, Matlow A, Coates AL. Do in-line respiratory filter protect patients? A comparison of bacterial removal efficiency of six filters. Pediatric Pulmonology 2002; 34(5): 336-341.

Clausen JL. Lung volume equipment and infection control. Eur Respir J 1997; 10: 1928-1932.

Fuso L, Accardo D, Bevignani G, Ferrante E, Della Corte A, Pistelli R. The effects of a filter at the mouth on pulmonary function tests. Eur Respir J 1995; 8: 314-317.

Hiebert T, Miles J, Okeson GC. Contaminated aerosol recovery from pulmonary function testing equipment. Am J Resp Crit Care Med 1999; 159: 610-612.

Johns DP, Ingram C, Booth H, Williams TJ, Walters EH. Effect of a microaerosol barrier filter on the measurement of lung function. Chest 1995; 107: 1045-1048.

Kamps AWA, Vermeer K, Roorda RJ, Brand PLP. Effect of bacterial filters on spirometry measurements. Arch Dis Child 2001; 85: 346-347.

Kendrick AH, Johns DP, Leeming JP. Infection control of lung function equipment: a practical approach. Resp Med 2003; 97: 1163-1179.

Kirk YL, Kendall K, Ashworth HA, Hunter PR. Laboratory evaluation of a filter for the control of cross-infection during pulmonary function testing. J Hosp Infection 1992; 20(3): 193-198.

Leeming JP, Pryce-Roberts DM, Kendrick AH, Smith EC. The efficacy of filters used in respiratory function apparatus. J Hosp Infection 1995; 31(3): 205-210.

Normand H, Le Coutour X, Metges MA, Mouadil A. Evaluation of a screen pneumotachograph as an in-line filter. Eur Respir J 2007; 30: 358-363.

Rasam SA, Apte KK, Salvi SS. Infection control in the pulmonary function laboratory. Lung India 2015; 32(4): 359-366.

Side EA, Harrington G, Thien F, Walters EH, Johns DP. A cost-analysis of two approaches to infection control in a lung function laboratory. Aus & NZ Journal of Med 1999; 29(1): 9-14.

Unstead M, Stearn MD, Cramer D, Chadwick MV, Wilson R. An audit into the efficacy of single-use bacterial/viral filters for the prevention of equipment contamination during lung function assessment. Resp Med 2006; 100: 946-950.

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

While reviewing a CPET I noticed the patient had a low PETCO2 throughout exercise and an elevated Ve-VCO2 slope. In addition the patient’s minute ventilation was on the high side (75% of predicted) at peak exercise. This is something you might expect to see in association with pulmonary vascular disease but the subject had a normal DLCO; normal spirometry; their oxygen saturation was normal at all times; and they had a normal maximum VO2 and a normal VO2 at anaerobic threshold. Since there didn’t seem to be any clinical reason for the low PETCO2 I had to wonder whether it was due to hyperventilation syndrome (HVS).

Hyperventilation syndrome is something that everybody “knows” about but is still somewhat ill-defined and this is at least partly because it is most often diagnosed solely by patient-reported symptoms. My lab does not have any diagnostic criteria for hyperventilation syndrome and for this reason I decided to review the literature on the subject.

Hyperventilation syndrome is usually suspected when a patient has rapid, shallow breathing with an irregular breathing frequency and with frequent sigh breaths. Common complaints are dizziness, dry mouth, tingling sensations in the hands and feet and often in combination with chest pain. These symptoms may raise the suspicion that a patient has hyperventilation syndrome and the classic way to diagnose HVS is has to have the patient perform a Hyperventilation Provocation Test (HVPT). During this test a patient voluntarily hyperventilates for three minutes and is then asked whether they felt the symptoms they had been complaining of occurred while they were hyperventilating.

The causes of HVS are considered to be primarily psychosomatic and the majority of articles written on the subject primarily explore this aspect. There are surprisingly few articles on the physiology of HVS and for this reason the physiological causes and consequences of HVS are poorly understood. Of note, I reviewed a couple dozen textbooks on pulmonary function testing and pulmonary diseases that I have on hand and found hyperventilation syndrome to be mentioned in only one (Cotes) where it merited one relatively small paragraph.

A starting point has to be that hyperventilation is ventilation in excess of metabolic requirements. More specifically carbon dioxide is eliminated at a faster rate than it is produced and when this occurs both PaCO2 and PETCO2 are reduced. Inclusion criteria for a number of HVS studies were a PaCO2 that was 30 or less with metabolic compensation (normal pH) or a PETCO2 that was 30 or less over a prolonged period of quiet breathing. This cannot be the sole criteria however, since a reduced PaCO2 is seen in some patients with asthma and a reduced PETCO2 can occur whenever there is significant ventilation-perfusion mismatching (high Vd/Vt) which can occur in emphysema, IPF and heart disease. Patients with HVS usually have normal spirometry, lung volume and DLCO test results however, so this fact could be used to rule out patients with other causes of a reduced PaCO2 or PETCO2.

Interestingly, although HVS could be considered to be caused by a reduced PaCO2 set point which would imply an increased sensitivity of to CO2 several studies have shown that subjects with HVS have a normal response to CO2. The evidence about the response to hypoxia in subjects with HVS is somewhat equivocal with one study indicating that it was normal and another stating that it was depressed except that when the hypoxic test gas mixture contained an elevated CO2 concentration that maintained PETCO2 at 40 mm Hg the hypoxic response was elevated.

Because ventilation is elevated relative to CO2 production in subjects with HVS both the Ve-VCO2 and Ve-VO2 slope tend to be elevated during a CPET. One study showed that a group of subjects with HVS had a Ve/VCO2 of 39.3 at AT versus 29.6 for a matched group of normal subjects. Interestingly, subjects with HVS had a higher incidence of sinus tachycardia and their ECG tended to show downward shifts in the ST-segment, T-wave flattening and these changes were not provoked or worsened by exercise.

Another test that shows a difference between normal subjects and those with HVS is the maximum volitional breath-hold time. This is pretty much what it sounds like; a subject takes a deep breath and the length of time it can be held is measured. Normal subjects tend to have a significantly longer breath-hold time when a breath of 100% oxygen is taken when compared to a breath of room air. Subjects with HVS tend to show no difference in breath-hold times when 100% oxygen is compared to room air, and their breath-holding times tended to be much less than normal subjects (mean 21 seconds versus mean 58 seconds). Although this is an interesting finding, volitional breath-holding is not a standardized test; there are no normal values I am aware of, and most importantly results would appear to depend greatly on patient motivation.

To summarize, the physiological diagnostic criteria for the hyperventilation syndrome would appear to be:

• PaCO2 <= 30 mm Hg
• PETCO2 <= 30 mm Hg
• Elevated Ve-VCO2 slope
• Elevated Ve-VO2 slope
• Elevated Ve/VCO2 at AT.

And in addition, individuals with HVS appear to have a:

• Normal CO2 response
• Reduced volitional breath-holding time

But since these findings can be found in many pulmonary and cardiovascular disorders they have to occur in the absence of any reason to suspect other lung diseases, so at the very least normal PFTs (spirometry, lung volumes and DLCO) and a normal SaO2 need to be present at the same time.

One problem with attempting to study HVS is that the measurement process itself seems to affect results. Specifically, studies have shown that just having a subject breath through a mouthpiece causes them to increase their respiratory rate and minute volume. Along these lines one study noted that when HVS subjects performed a CPET they tended to have a transient increase in Rq well above 1.0 either just before or at the onset of exercise.

Another problem with studying HVS is selecting subjects and there appears to be a wide range of differing inclusion criteria. For some studies a PaCO2 or PETCO2 of 30 or less had to be present at the time of the study, whereas for other studies the subjects only needed to have demonstrated a low PETCO2 at least once during the study period, and other studies only required that the subjects have the correct symptoms and a positive hyperventilation provocation test.

I’m not particularly qualified to criticize but I think that the general belief that HVS is a psychosomatic disorder has limited the physiological research of HVS. Reading what research is available it’s not clear that the categorization of HVS is completely correct since more than one researcher had subjects with chronic hyperventilation without any apparent psychosomatic disorders. It’s also not overly clear to me whether HVS is the same entity when hyperventilation is transitory (rare episodes), episodic (occurs somewhat often) or chronic (constant). I think that despite a clear association of HVS with anxiety and panic disorders there are a number of questions that remain to be answered.

Hyperventilation syndrome should be suspected when a patient complains of shortness of breath, palpitations, dizziness and chest pain; makes frequent sigh breaths; and is associated with anxiety. The classical approach of using symptoms and a hyperventilation provocation test has been criticized by numerous investigators because the rate of false positives is relatively high. Objective physiological factors would appear to include a PaCO2 or PETCO2 that is 30 mm Hg or less and an elevated Ve-VCO2 slope with normal pulmonary function tests and SaO2. HVS can be episodic however, and not all of these factors may be present at the time of testing. When hyperventilation syndrome is already suspected the presence of these factors can be used as an additional confirmation.

There are however, very few physiological studies on HVS and there are numerous discrepancies between them in terms of subject selection and methodology. For these reasons a definitive physiological diagnosis of HVS does not seem possible and at best these factors can only provide a possible confirmation of an existing suspicion.

Notably, the patient whose CPET results got me interested in reviewing the literature on HVS had all of these factors (as well as the elevated Rq during the baseline period and beginning of testing). The physician who ordered the CPET already suspected a pyschosomatic cause for the patient’s shortness of breath and I am able to say that the overall pattern of the results are consistent with that suspicion.

References:

Bass C, Gardner WN. Respiratory and psychiatric abnormalities in chronic symptomatic hyperventilation. Brit Med J 1985; 290: 1387-1390.

Chin K, Hirai M, Kuriyama T, Kita H, Nakamura T, Shimizu K, Kuno K, Ohi M. Hopoxaemia in patients with hyperventilation syndrome. Q J Med 1997; 90: 477-485.

Cotes JE. Chinn DJ, Miller MR. Lung function. Physiology, measurement and application in medicine. Sixth edition, Blackwell Publishing, 2006.

Gardner WN. The pathophysiology of hyperventilation disorders. Chest 1996; 109: 516-534.

Han JN, Stegen K, Simkens K, Cauberghs M, Schepers R, Van den Bergh O, Clement J, Van de Woestijne KP. Unsteadiness of breathing in patients with hyperventilation syndrome and anxiety disorders. Eur Respir J 1997; 10: 167-176.

Hormbrey J, Jacobi MS, Patil CP, Saunders KB. CO2 response and pattern of breathing in patients with symptomatic hyperventilation, compared to asthmatic and normal subjects. Eur Respir J 1988; 1: 846-852.

Hornsveld H, Garssen B. Hyperventilation syndrome: an elegant but scientifically untenable concept. Netherlands J Med 1997; 50: 13-20.

Howell JBL. The hyperventilation syndrome: a syndrome under threat? Thorax 1997; 52: S30-S34.

Jack S, Rossiter HB, Person MG, Ward SA, Warburton CJ, Whipp BJ. Ventilatory responses to inhaled carbon dioxide, hypoxia and exercise in idiopathic hyperventilation. Amer J Respir Crit Care Med 2004; 170: 118-125.

Kinnula VL, Sovijarvi ARA. Hyperventilation during exercise: independence on exercise-induced bronchoconstriction in mild asthma. Resp Med 1996; 90: 145-151.

Vansteenkiste J, Rochette F, Demedts M. Diagnostic tests of hyperventilation syndrome. Eur Respir J 1991; 4: 393-399.

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

Once again my lab was questioned by a research study’s primary investigator and study coordinator about why our lung volume results came out significantly lower than another lab’s. In order to be part of this study a subject has to have an RV that is greater than 150% of predicted. The RV we had obtained on a subject referred to the study was over a liter less than the results they had brought with them from another lab and for this reason the patient no longer qualified.

When I reviewed the subject’s test data from my lab it was clear to me that our test quality was good and more than met the ATS/ERS reproducibility criteria. We were given a copy of the subject’s report from the other lab and at first glance, the results look very typical for emphysema. Specifically the report showed very severe airway obstruction, a normal TLC, an elevated FRC and RV consistent with hyperinflation and a severely reduced DLCO. Our results however, showed a mixed defect with severe obstruction and a mildly reduced TLC.

Getting accurate lung volume measurements is hard. Regardless of which measurement technique you use, in most instances any errors tend to cause lung volumes to be overestimated. When very severe airway obstruction is present unless you are careful about panting frequency, plethysmography will often overestimate FRC and TLC, and that may be what happened in this case.

But this isn’t about test quality or the reasons why I believe my lab is better than most others. Although the report was from a nearby hospital with a reputation for the quality of its patient care, when I started reviewing it I immediately started to see math errors among the predicted values. I’ve run across these kind of errors before but this report was from a different equipment manufacturer than last time and this means that these kind of errors are probably far more common than I ever would have expected.

	Predicted:	Pre-BD:	%Predicted:	Post-BD:	Post %Pred:	%Change:
FVC:	2.80	0.91	32%	1.01	36%	+12%
FEV1:	2.14	0.49	23%	0.42	19%	-15%
FEV1/FVC:	77	54		41
PEF:	5.55	1.86	33%	2.31	42%	+25%
FIVC:	2.60	0.95	36%	1.06	41%	+11%
TLC:	4.44	4.62	104%
FRC:	2.54	3.68	145%
RV:	1.85	3.63	197%
SVC:	2.26	0.99	44%
IC:		0.94
ERV:		0.07
DLCO:	21.2	4.60	21%
VA:		2.17
DL/VA:	3.70	2.11	57%

What first caught my eye was that the predicted TLC, RV and SVC did not add up correctly. Specifically, the predicted TLC was not equal to the predicted RV plus the predicted SVC, or if you want to put it another way, the predicted TLC minus the predicted RV did not equal the predicted SVC. Next I noticed that the predicted SVC, FVC and FIVC were all different. Finally I noticed that the observed IC and ERV did not add up to the observed SVC.

The reference equations were not specified on the report so I did some sleuthing and using the patient’s demographic information found that the spirometry equations came from Hankinson et al (NHANESIII) study and the lung volumes were from Stocks and Quanjer (ERS).

It’s not clear to me however, where the predicted SVC came from since it did not match the SVC that would have been derived from the ERS reference equations (2.59 L) and also did not match any of the other reference equations I have on hand. Along the same lines I am not sure why the predicted FIVC is smaller than the predicted FVC (or where it came from). I am unaware of any particular guideline that would indicate that FIVC should be smaller than the FVC, and would note that the primary ATS/ERS recommendation for SVC is for it to be an inspiratory maneuver.

When I checked the math of the observed data I also found a number of simple math errors that are probably due to truncating and rounding digits. The reason it’s hard to be sure it is that kind of error rather than a true math error is that I’ve found that raw test data is commonly stored with more numerals after the decimal point than what shows up on a report. Specifically, an FVC could be stored as 5.32857 in the database but would either be truncated or rounded and then appear in a report as 5.32 or 5.33. I understand that these extra digits happen because of multiplication and division but I don’t necessarily agree with them. First, test equipment isn’t accurate to a single milliliter, let alone fractions of a milliliter so why is it stored with so many digits? More importantly, that when math is performed on the raw data it then involves hidden digits. For example, the IC is 0.94 L and the ERV is 0.07 L. Added together that is 1.01 L but the report showed the SVC to be 0.99 L. My guess is that in this instance the IC and ERV were truncated for the report but that when added, the result was rounded.

It’s not clear who is responsible for all of these math errors. It appears to me that the observed results are reported with a mix of truncation and rounding. Although these errors aren’t large and they probably don’t make a significant difference when results are reviewed they are nevertheless present and this is the responsibility of the equipment manufacturer. But for the predicted values I know that it’s possible for a user to select a set of reference equations (like NHANESIII or ERS) and then modify an individual component (such as SVC) so this could be the responsibility of the end user instead of the manufacturer.

There are no ATS/ERS guidelines about normalizing reference values when reference equations from different sources are mixed and matched. I also haven’t seen any particular consensus about how this should be handled from the different equipment manufacturers either.

For example, in my lab’s test systems the predicted RV is derived from the ERS equations but the predicted SVC is actually the FVC from NHANESIII. The software then re-calculates the predicted TLC from predicted RV + predicted SVC. This means that everything adds up but it also means that the predicted TLC, IC and ERV are different than it would have been from the original ERS TLC equation. This is a solution of some kind but why is this okay? As importantly, why is it the TLC that is adjusted and not the RV?

I’ve also seen results from another lab where the predicted TLC and RV came from the ERS equations and the SVC came from the NHANESIII reference equations but they were sort of shoved in together and TLC – RV did not equal SVC. This is also a solution of some kind, but the predicted and percent predicted numbers never add up and why is this okay?

In this report’s case the TLC and RV came from the ERS equations but the SVC (and FIVC) did not come from any known source. I’m most concerned that the lung volume subdivisions didn’t come even close to adding up but in the absence of ATS/ERS guidance I can’t quite say it is wrong. Confusing, yes, but not necessarily wrong.

My personal opinion is that none of us would use the FVC from one set of reference equations and the FEV1 from a different one. Why then is it okay to shoehorn the predicted FVC from NHANESIII into the predicted TLC and RV from ERS? For me the simplest answer would be that we should not mix and match reference equations. This would mean that the predicted SVC would not be equal to the predicted FVC but since they (and the predicted DLCO as well) come from different study populations this is okay.

If the fact that the vital capacity taken from different reference populations can be different is a concern then all of the reference equations (spirometry, lung volumes and DLCO) can be taken from the same study and this is the other answer. The number of studies where all three types of testing was performed on their study population is small (Gutierrez et al, Marsh et al) but it can be done.

Over the years I haven’t had the opportunity to review all that many reports from other PFT Labs and up until recently I wouldn’t have thought to check the math in the predicted values. In the last four months however, I’ve seen reports from two different labs with significant – and different – math errors. This says to me that this problem is probably very common.

There appears to be a strong belief that the predicted SVC should be the same as the predicted FVC (although the SVC in this report flies against this). Part of this is based on the fact that studies like NHANESIII have a very large study population and use more sophisticated statistical analysis that did the ERS study (or any other lung volume study for that matter) and that this makes the NHANESIII FVC “better” than the ERS SVC. Part of it is based on the thought that a vital capacity is a vital capacity and that all the vital capacities on a report should therefore be the same. Trying to merge vital capacities from different reference equations seems to create more problems than it solves, however.

Reference equations are often viewed as an arcane and mysterious subject area and for this reason many labs are reluctant to “tamper” with the default settings of their test system software (after all, surely the manufacturer knows best, don’t they?). Since there is only minimal official guidance and no particular consensus on using reference equations many labs may also be reluctant to make any changes, particularly since that means they’d have to decide for themselves what’s the best approach. But if your reports have math errors, you have a problem and doing nothing is still making a decision.

So, have you checked the math on your reports lately?

References:

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.

Marsh S, Aldington S, Williams M, Weatherall M, Shirtcliffe P, McNaughton A, Pritchard A, Beaseley R. Complete reference ranges for pulmonary function tests from a single New Zealand population. New Zealand Med J 2006; 119: N1244.

Stocks J, Quanjer PH. Reference values for residual volume, function residual capacity and total lung capacity. Eur Respir J 1995; 8: 492-506.

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

Last week I was discussing the use of DL/VA to differentiate between the different causes of gas exchange defects with a physician. DL/VA is DLCO divided by the alveolar volume (VA). It is an often misunderstood value and the most frequent misconception is that it is a way to determine the amount of diffusing capacity per unit of lung volume (and therefore a way to “adjust” DLCO for lung volume). This is not the case because dividing DLCO by VA actually cancels VA out of the DLCO calculation and for this reason it is actually an index of the rate at which carbon monoxide disappears during breath-holding.

[Note: The value calculated from DLCO/VA is related to Krogh’s constant, K, and for this reason DL/VA is also known as KCO. The term DL/VA is misleading since the presence of ‘VA’ implies that DL/VA is related to a lung volume when in fact there is no volume involved. The use of the term DL/VA is probably a major contributor to the confusion surrounding this subject and for this reason it really should be banned and KCO substituted instead.]

I’ve written on this subject previously but based on several conversations I’ve had since then I don’t think the basic concepts are as clear as they should be.

When you know the volume of the lung that you’re measuring, then knowing the breath-holding time and the inspired and expired carbon monoxide concentrations allows you to calculate DLCO in ml/min/mmHg.  When you remove the volume of the lung from the equation however (which is what happens when you divide DLCO by VA), all you can measure is how quickly carbon monoxide decreases during breath-holding (KCO). 

A low KCO can be due to decreased perfusion, a thickened alveolar-capillary membrane or an increased volume relative to the surface area.

A high KCO can be due to increased perfusion, a thinner alveolar-capillary membrane or by a decreased volume relative to the surface area. Because it is not possible to determine the reason for either a low or a high KCO this places a significant limitation on its usefulness.

This doesn’t mean that KCO cannot be used to interpret DLCO results, but its limitations need to recognized and the first of these is that the rules for using it are somewhat different for restrictive and obstructive lung diseases.

KCO is probably most useful for assessing restrictive lung diseases and much that has been written about KCO is in reference to them. The basic idea is that for an otherwise normal lung when the TLC is reduced DLCO also decreases, but does not decrease as fast as lung volume decreases. Part of the reason for this is that surface area does not decrease at the same rate as lung volume. This by itself would be a simple reason for KCO to increase as lung volume decreases but the complete picture is a bit more complicated.

The lung reaches its maximum surface area near TLC, and this is also when DLCO is at its maximum. At this time the alveolar membrane is stretched and at its thinnest which reduces the resistance to the transport of gases across the membrane. Simultaneously however, the pulmonary capillaries are also stretched and narrowed and the pulmonary capillary blood volume is at its lowest.

As lung volume decreases towards FRC, the alveolar membrane thickens which increases the resistance to gas transport but this is more than counterbalanced by an increase in pulmonary capillary blood volume. When factored in with a decrease in alveolar volume (which decreases the amount of CO available to be transferred), the rate at which CO decreases during breath-holding (for which KCO is an index) increases.

This means that when TLC is reduced but the lung tissue is normal, which would be the case with neuromuscular diseases or chest wall diseases, then KCO should be increased. There is no particular consensus about what constitutes an elevated KCO however, and although the amount of increase is somewhat dependent on the decrease in TLC, it is not predictable on an individual basis. For this reason, in my lab a KCO has to be at least 120 percent of predicted to be considered elevated (and I usually like it to be above 130% to be sufficiently confident).

Interstitial involvement in restrictive lung disease is often complicated and there can be multiple reasons for a decrease in DLCO. Scarring and a loss of elasticity causes the lung to become stiffer and harder to expand which decreases TLC. The alveolar membrane can thicken which increases the resistance to the transfer of gases. And probably most commonly there is destruction of the alveolar-capillary bed which decreases the pulmonary capillary blood volume and the functional alveolar-capillary surface area.

This means that when TLC is reduced and there is interstitial involvement, a normal KCO (in terms of percent predicted) is actually abnormal. A normal KCO can be taken as an indication that the interstitial disease is not as severe as it would considered to be if the KCO was reduced, but it is still abnormal.

KCO has a more limited value when assessing reduced DLCO results for obstructive lung disease. This is because the TLC is more or less normal in obstructive lung diseases and it is the DLCO, not the KCO, that is the primary way to differentiate between a primarily airways disease like asthma and one that also involves the lung tissue like emphysema. Strictly speaking, when TLC is normal and the DLCO is reduced, then KCO will also be reduced.

VA is a critical part of the DLCO equation however, so if VA is reduced because of a suboptimal inspired volume (i.e. inhalation to a lung volume below TLC), then DLCO may be underestimated. In this specific situation, if the lung itself is normal, then KCO should be elevated. When significant obstructive airways disease is present however, VA is often reduced because of ventilation inhomogeneity. This can be assessed by calculating the VA/TLC ratio from a DLCO test that was performed with acceptable quality (i.e. good inspired volume). A low VA/TLC ratio (less than 0.85) indicates that a significant ventilation inhomogeneity is likely present.

Does a low VA/TLC ratio make a difference when interpreting a low DLCO? Not really, but it brings up an interesting point and that is that the VA/TLC ratio indicates how much of the lung actually received the DLCO test gas mixture (at least for the purposes of the DLCO calculation). It also indicates that the DLCO result only applies to that fraction of the lung included within the VA/TLC ratio. Does that mean that the DLCO is underestimated when the VA/TLC ratio is low? The answer is maybe, but probably not by much.

It is important to remember that the VA is measured from an expiratory sample that is optimized for measuring DLCO, not VA. When an individual with significant ventilation inhomogeneity exhales, the tracer gas (and carbon monoxide) concentrations are highest at the beginning of the alveolar plateau and decrease throughout the remaining exhalation.

The calculated VA therefore depends on where the tracer gas is measured during exhalation.

To one degree or another a reduced VA/TLC ratio is an artifact of the DLCO measurement requirements. At least one study has indicated that when the entire exhalation is used to calculate DLCO both healthy patients and those with COPD have a somewhat higher DLCO (although I have reservations about the study’s methodology). For the COPD patients at least part of the improvement was due to an increase in the measured VA. But the fact is that for regular DLCO testing any “missing” fraction isn’t measured so it really isn’t possible to say what contribution it would have made to the overall DLCO.

In general a low KCO is usually seen in:

• Interstitial disease
• Pulmonary hypertension
• Hepatopulmonary syndrome
• Emphysema
• Bronchiolitis

An elevated KCO is usually seen in:

• Pneumonectomy
• Neuromuscular disease
• Chest wall disease
• Alveolar hemorrhage
• Asthma
• Obesity

More than one study has cast doubt on the ability of KCO to add anything meaningful to the assessment of DLCO results. Despite this KCO has the potential be useful but it must be remembered that it is only a measurement of how fast carbon monoxide disappears during breath-holding. KCO can be reduced or elevated due to differences in alveolar membrane thickness, pulmonary blood volume as well as lung volume but it cannot differentiate between these factors, and the best that anyone can do is to make an educated guess. Realistically, the diagnosis of a reduced DLCO cannot proceed in isolation and a complete assessment requires spirometry and lung volume measurements as well.

In addition, there is an implicit assumption is that DLCO was normal to begin with. This is not necessarily true and as an example DLCO is often elevated in obesity and asthma for reasons that are unclear but may include better perfusion of the lung apices and increased perfusion of the airways. These individuals have an elevated KCO to begin with and this may skew any changes that occur due to the progression of restrictive or obstructive lung disease.

Finally DLCO tests have to meet the ATS/ERS quality standards for the KCO to be of any use and what we consider to be normal or abnormal about DLCO, VA and KCO depends a lot on the reference equations we select.

References:

Aduen JF et al. Retrospective study of pulmonary function tests in patients presenting with isolated reductions in single-breath diffusion capacity: Implications for the diagnosis of combined obstructive and restrictive lung diease. Mayo Clin Proc 2007; 82(1): 48-54.

Cotes JE, Chinn DJ, Miller MR. Lung Function. Physiology, measurement and application in medicine. 2006, Blackwell Publishing.

Frans A, Nemery B, Veriter C, Lacquet L, Francis C. Effect of alveolar volume on the interpretation of single-breath DLCO. Respir Med 1997; 91: 263-273.

Hansen JE. Pulmonary function testing and interpretation. 2011, Jaypee Brothers Medical Publishers, Ltd,

Horstman MJM, Health B, Mertens FW, Schotborg D, Hoogsteden HC, Stam H. Comparison of total-breath and single-breath diffusing capacity if health volunteers and COPD patients. Chest 2007; 131: 237-244.

Hughes JMB, Pride NB. In defence of the carbon monoxide transfer coefficient KCO (TL/VA). Eur Respir J. 2001; 17: 168-174.

Hughes JMB, Pride NB. Examination of the carbon monoxide diffusing capacity (DLCO) in relation to its KCO and VA components. Amer J Respir Crit Care Med 2012; 186(2): 132-139.

Johnson DC. Importance of adjusting carbon monoxide diffusing capacity (DLCO) and carbon monoxide transfer coefficient (KCO) for alveolar volume, Respir Med 2000; 94: 28-37.

Kaminsky DA, Whitman T, Callas PW. DLCO versus DLCO/VA as predictors of pulmonary gas exchange. Respir Med 2007; 101: 989-994.

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

van der Lee I, Zanen P, van den Bosch JMM, Lammers JWJ. Pattern of diffusion disturbance related to clinical diagnosis: The KCO has no diagnostic value next to the DLCO. Respir Med 2006; 100: 101-109.

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

Oddly enough, I recently got a couple emails on the same day about the FEF25-75 and ended up corresponding for a while with the authors. FEF25-75 is a subject that somehow manages to keep resurrecting itself no matter how many stakes have gotten hammered into its heart. My opinion (expressed previously), and those of many others, is that the measurement of FEF25-75 is overly affected by FVC volume and expiratory time; that its reproducibility is poor; that its “normal” range is too broad to be meaningful; and that the FEF25-75 is usually only abnormal when the FEV1 is also below the LLN. Despite all this the FEF25-75 still continues to be used by many clinicians and researchers.

While discussing it however, one of the points that came up was how the “best” FEF25-75 should be selected. Given that it’s not clear to me exactly what the FEF25-75 is measuring, I am not sure there is such a thing as a “best” FEF25-75. Out of curiosity I reviewed a number of the older studies concerning FEF25-75 and although all the studies stated that their subjects performed multiple spirometry efforts I was interested to note that the FEF25-75 selection process was rarely, if ever, detailed. Of the exceptions, one stated the FEF25-75 was taken from the spirometry effort with the best FEV1 and another stated that the FEF25-75 was averaged from three efforts. The ATS/ERS statement on spirometry says that the FEF25-75:

“… is taken from the blow with the largest sum of FEV1 and FVC.”

This makes a certain amount of sense but because this statement is not referenced to any studies it should only be taken as a way to standardize the measurement of the FEF25-75 and not as a resolution about what constitutes the “best” FEF25-75. Even so it still leaves the door open to some varied interpretations. There are at least two situations where this is problematic. First, when two spirometry efforts have the same combined FVC + FEV1 value, and second, when an individual’s spirometry efforts are highly variable and the FVC and FEV1 have to be selected from separate efforts.

I didn’t have to go very far to find examples for both of these problems.

	Effort #1:	Effort #2:
FVC:	2.03	1.97
FEV1:	1.00	1.06
FEV1/FVC:	49	54
FEF25-75:	0.28	0.43

This is from an individual with severe airways obstruction and both spirometry efforts (which were far and away the patient’s best) have the same value for FVC+FEV1. The fact that FEF25-75 is sensitive to FVC should be quite clear, since the effort with the largest FVC has a FEF25-75 that is 35% smaller than the effort with the largest FEV1 even though the difference in FVC is only about 3%. In one sense it doesn’t matter which of these is the “best” FEF25-75 since the predicted value for this individual was 2.74 L/sec and both results are severely reduced. In another sense it matters a lot, since whenever the sum of the FEV1 and FVC are the same (or essentially the same) how do you decide which FEF25-75 to use? Best FEV1 or best FVC?

	Effort #1:	Effort #2:
FVC:	1.17	1.28
FEV1:	0.98	0.84
FEV/FVC:	84	66
FEF25-75:	0.84	0.48

In this particular instance, the patient had fairly variable efforts. The effort with the best FVC had a low FEV1 and the effort with the best FEV1 had a low FVC. Our standard practice is to combine the efforts and report the best FVC with the best FEV1. Although our software lets us select an FVC from one effort and an FEV1 from another (and will re-calculate the FEV1/FVC ratio accordingly) it only lets us choose the flow-based data (i.e. FEF25-75, MEF50, MIF50 etc) from one effort. So given the discrepancy in test quality, which FEF25-75 should be selected?

In addition, the ATS/ERS statement on interpretation says that the largest VC, regardless of the source, should be used to calculate the FEV1/FVC ratio. So a very related problem is when an SVC or IVC is actually used to re-calculate the FEV1/VC ratio. Since SVC and IVC maneuvers are not timed FEF25-75 cannot be calculated. This means that the only FEF25-75 that can be reported comes from the spirometry effort the FEV1 was taken from.

Finally, and this may not be fair, but what do you do with an FEF25-75 that is selected from the spirometry effort with the best FVC+FEV1 and the test quality is so poor the FEF25-75 is meaningless?

These issues also raises an important question about trending the FEF25-75 and using the changes from one set of tests to another as a guideline for therapy. I doubt that this has been studied specifically but I have to think at least some of the variation in FEF25-75 over time has more to do with the selection process than it does with any clinical changes.

The only standard for selecting an FEF25-75 from multiple efforts is based on FVC and FEV1. This makes a certain amount of sense but does not address the issue of what really constitutes the “best” FEF25-75. Since there is no particular consensus on what the FEF25-75 is really measuring I am not sure that there is such a thing as a “best” FEF25-75, but then I don’t think the FEF25-75 is worth reporting in the first place.

When the FEF25-75 was first reported over 40 years ago, its results were taken as a way to detect small airways disease. Since that time the FEF25-75 has been shown to be a highly variable measurement with relatively poor reproducibility that is markedly affected by FVC volume and expiratory time. The fact that selecting an FEF25-75 from multiple spirometry efforts is itself a variable and idiosyncratic process just adds one more reason not to use it.

References:

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.

Brusasco V, Crapo R, Viegi G. ATS/ERS Task force: standardisation of lung function testing. Interpretive strategies for lung function tests. Eur Respir J 2005; 26: 948-968.

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