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Once again we’ve had some staff turnover. Rightly or wrongly, the pattern we follow in staffing the lab is to hire people with a science degree and then train them ourselves. Our hires are usually interested in a career in medicine but often haven’t decided what specifically interests them. We look for individuals with people skills on top of their education and ask for a minimum of a year’s commitment with the requirement that they get their CPFT certification by the end of the year. Sometimes our staff only stays a year, sometimes a couple years, and most of the time when they leave they go back to college for a more advanced degree and become nurses or physician assistants and occasionally even physicians (a couple of our pulmonary fellows were former PFT lab alumni).

We do this mostly because it’s very hard to find anybody with prior experience in pulmonary function testing. I’d like to say this is a recent occurrence but realistically it’s been this way for decades. One of the reasons for this is that there are no college level courses on pulmonary function testing. Although the training programs for respiratory therapists often include some course work on PFTs this is almost always a one semester lecture course with no hands-on training (when it is included at all).

Another reason is that trained individuals often do not stay in this field. This is partly because there isn’t much of a career path since the most you can usually aspire to is being a lab manager but even then I know of many small PFT labs where the manager is somebody outside the field such as a nurse or administrator with no experience in pulmonary function testing so often that isn’t even an option. Another reason though, is that the PFT Lab pay scale, although adequate, is often noticeably less than other allied health professions such as radiology techs, ultrasound techs and sleep lab techs.

Anyway, the downside of this hiring pattern is that it seems like we’re always hiring and training new staff (however untrue that may actually be). We do have a fairly good training program however, so new staff usually come up to speed and become reasonably productive in a short period of time. Even so, it takes at least a year before a new technician is reasonably proficient not just in performing the tests, but in understanding the common testing problems and errors. This is at least one reason why I spend much of my time reviewing raw test data and sending annoying emails to the lab staff.

It also means that we frequently revisit basic testing issues.

Recently, a report with a full panel of tests (spirometry, lung volumes, DLCO) came across my desk. The patient had had a full panel a half a year ago and when I compared the results between the two sets of tests there had been no significant change in FVC, FEV1 and DLCO but the TLC was over a liter higher than it had been last time.

	Jan, 2017		June, 2016
	Observed:	%Predicted:	Observed:	%Predicted:
FVC:	2.04	85%	2.38	97%
FEV1:	0.58	32%	0.62	34%
FEV1/FVC:	28	38%	26	36%
TLC:	7.27	152%	6.10	126%
FRC:	6.16	222%	4.83	174%
DLCO:	8.12	51%	8.91	55%

Lung volumes had been measured by plethysmograph both times and when I looked at the raw test data for both visits, the VTG loops and the SVC maneuvers all appeared to have good quality. Then I looked at the VTG panting frequency however, I immediately saw what was most likely the reason for the change in TLC:

	Jan, 2017	June, 2016
	Observed:	Observed:
VTG (L):	6.21	4.89
VTG Frequency (pants/min):	111	28

So how does the VTG panting frequency affect the TLC?

To be able to explain this you first need to review how lung volumes are measured in a plethysmograph. When a subject sits inside a plethysmograph and the mouthpiece shutter closes, they are supposed to pant (expand and contract their lungs). During this panting maneuver, when the air inside the lungs is compressed, the air inside the plethysmograph is rarified and when the lungs expand, the air inside the plethysmograph is compressed. In both instances, Boyle’s law:

Pressure¹ x Volume¹ = Pressure² x Volume²

shows that the change in volume and pressure are proportionally related to each other. What this specifically means is that the change in pressure in any given lung is related to its change in volume and for this reason for the same change in pressure a large lung requires a large change in volume and a small lung only requires a small change in volume:

For the air inside the plethysmograph, a small change in lung volume causes a small change in plethysmograph pressure and a large change in lung volume causes a large change in plethysmograph pressure.

When lung pressure and plethysmograph pressure are plotted against each other, the slope of the line is then proportional to lung volume.

One assumption that this technique makes is that the pressure measured at a subject’s mouth is the same as the pressure inside the lungs. Although mostly true this ignores one small fact and that is while the lungs are compressible (and expandable) the upper airway and mouth are not. What this means is that while the lungs are being compressed (or expanded) air has to move into (or out of) the upper airway and mouth before the pressure measured at the mouth equals the pressure inside the lung.

In most instances the amount of air that has to move is small and this occurs so quickly that panting frequency doesn’t really matter all that much and this effect can be ignored. When there is a great deal of airway obstruction however, airway resistance is high and this can substantially slow the movement of air from the lungs into and out of the mouth.

When this happens, the pressure measured at the mouth will be less than the pressure inside the lungs and the slope of mouth vs plethysmograph pressure will be skewed in a way that causes lung volume to be overestimated:

The degree of mismatch between lung pressure and the pressure measured at the mouth depends on the amount of airway resistance and the panting frequency. When airway resistance is high, the panting frequency needs to be low enough for there to be enough time for the pressure in the mouth and the lungs to equalize. It is for this reason that the ATS/ERS standards for plethysmographic lung volume measurements recommend a panting frequency between 30 pants/minute (0.5 Hz) and 60 pants/minute (1.0 hz).

Note: This is also the reason that the subject’s hands are supposed to be placed firmly against their cheeks during the panting maneuver. If the subject’s cheeks are allowed to balloon inwards and outwards during panting then this can also cause mouth pressure to be underestimated relative to lung pressure. I mention this because I’ve talked to a couple patients who had their lung volumes measured in a plethysmograph without being asked to hold their hands against their cheeks (although thankfully not in my lab).

So the VTG panting frequency matters, and in this instance the patient’s change in TLC was most likely related to a change in panting frequency from 28 pants/minute to 111 pants/minute. Although it was a newer staff member that performed this testing I like to spread the pain around equally so I took it as a “teaching moment” and sent an annoying email about this issue to all the lab’s staff and not just that technician.

Accurate lung volume measurement is harder than it looks. There are potential errors in all methods and these errors are often more subtle than they are for spirometry or diffusing capacity. Plethysmographic lung volumes are considered to be the “gold standard”. This is probably because they are supposed to be able to measure “trapped” air that cannot be measured by helium dilution or nitrogen washout. It’s far from clear to me that this is always true and at least one study has shown that the TLC measured by helium dilution more closely approximated that measured by CAT scan volumetry in patients with COPD than did plethysmography. Another study showed that TLC by plethysmography overestimated TLC from CAT scan volumetry in patients with COPD and that the degree of error was related to the severity of airway obstruction.

What is clear however, is that details matter and that plethysmography is as prone to error from poor technique as any other method of measuring lung volumes. So, remember to set your plethysmograph frequency dial to between 0.5 and 1.0 Hz for the highest fidelity in your lung volume measurements.

References:

Bohadana AB, Peslin R, Hannhart B, Tesulescu D. Influence of panting frequency of plethysmographic measurements of thoracic gas volume. J Appl Physiol 1982; 52(3): 739-747.

Borg BM, Thompson BR. The measurement of lung volumes using body plethysmography: a comparison of methodologies. Respir Care 2012; 57(7): 1076-1083.

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

Coates AL, Peslin R, Rodenstein D, Stocks J. ERS/ATS workshop report series. Measurement of lung volumes by plethysmograph. Eur Respir J 1997; 10: 1415-1427.

Criee CP, Sorichter S, Smith HJ et al. Body plethysmography – its principles and clinical use. Respir Med 2011; 105: 959-971.

Garfield JL, Marchetti N, Gaughan JP, Steiner RM, Criner GJ. Total lung capacity by plethysmography and high-resolution computer tomography in COPD. Int J COPD 2012; 7: 119-126.

Nigro CA, Dibur E, Lima S, Giavedoni S, Prieto EJ, Rhodius EE. Overestimation of thoracic gas volume during the airway resistance maneuver. A potential error in the diagnosis of air trapping. Medicina 2004; 64: 31-35.

O’Donnell CR, Bankier AA, Stiebellehner L, Reilly JJ, Brown R, Loring SH. Comparison of plethysmographic and helium dilution lung volumes: which is best for COPD? Chest 2010; 137(5): 1108-1115.

Rodenstein DO, Stanescu DC, Francis C. Demonstration of failure of body plethysmography in airway obstruction. J Appl Physiol 1982; 52(4): 949-954.

Rodenstein DO, Stanescu DC. Frequency dependence of plethysmographic volume in healthy and asthmatic subjects. J Appl Physiol 1983; 54(1): 159-165.

Sue D. Measurement of lung volumes in patients with obstructive lung disease. Ann Amer Thor Soc 2013; 10(5): 525-530.

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

The ATS/ERS standard for spirometry recommends reporting the highest FEV1 and the highest FVC even when they come from different tests. Our lab software allows us to do this, but only with some annoying limitations. One of the bigger limitations has to do with how expiratory time is reported. In particular, expiratory time is lumped in with a number of other values like Peak Flow (PEF) and FEF25-75. As importantly, the flow-volume loop and volume-time curve can only come from a single effort.

Our lab software defaults to choosing a single effort with the highest combined FVC+FEV1. The technician performing the tests will override this when other spirometry efforts have a larger FVC or a better FEV1 (which is chosen not just if it is higher but also on the basis of peak flow, back-extrapolation and other quality indicators). The usual order for this is to first choose a spirometry effort with the “best” FEV1, then if there is a different effort with a larger FVC that FVC is selected for reporting. When things are done this way what happens is that the expiratory time, flow-volume loop and volume-time curve that come from the effort selected for its FEV1 are reported. This means is that the expiratory time and volume-time curve often don’t match the reported FVC.

I always take a look at the raw test data whenever a spirometry report comes across my desk with an expiratory time less than 6 seconds or the technician noted that the spirometry effort is a composite. What I often find is that even though the reported expiratory time may be low, the FVC actually comes from an effort with an adequate expiratory time. Although I can select the right expiratory time the problem is that doing so also selects the PEF and the PEF from the effort with the highest FVC is often significantly less than the effort from the best FEV1. The same problem applies to selecting the volume-time curve since the associated flow-volume loop often doesn’t match the effort with the best FEV1 and best PEF. For these reasons I only select the correct expiratory time and volume-time curve when it doesn’t really affect the flow-volume loop and PEF.

However, I’ve always assumed that the expiratory time from the effort with the highest FVC was probably the most correct expiratory time. Yesterday however, this spirometry effort came across my desk:

	Blue	Red
FVC:	2.53	2.54
FEV1:	2.19	2.13
FEV1/FVC:	86	84
PEF:	6.94	5.07
Exp. Time:	3.05	5.09

The expiratory time from the effort with the highest FVC was about 2 seconds longer than the effort with the best FEV1, but the difference in FVC from the two efforts was only 0.01 L. Strictly speaking the effort with the highest FVC does have the longest expiratory time but should this expiratory time be considered correct?

In one sense it really doesn’t matter in this case because even though the expiratory time from the largest FVC is longer, it is still under 6 seconds and that means it’s still probably a suboptimal test effort. But what if the effort the FEV1 came from was 5 seconds long and the effort the FVC came from was 7 seconds long and the difference was still only 0.01 L?

What if there were two spirometry efforts with the same FVC and FEV1 and one had an expiratory time of 5 seconds and the other 7 seconds? Would it be acceptable to select the spirometry test that was 7 seconds long because it met the ATS/ERS criteria or should the test with the shorter expiratory time be selected because it better reflects the patient’s effort and ability?

The answer has to be the shorter expiratory time because the longer time is falsely elevated.

But part of the problem is that there is no official definition of expiratory time in the ATS/ERS spirometry standards. Most test systems use an inspiratory flow or volume that’s above some arbitrary threshold as the end of exhalation or when the technician performing the test ends it manually. This is a probably a reasonable rule-of-thumb approach but it also means that expiratory time has a fairly high level of uncertainty.

At least once or twice in the past researchers have put forward the notion that measuring the expiratory time at 98% of the vital capacity would be a way to standardize expiratory time. This idea never gained any traction but it was also proposed before the ATS/ERS included expiratory time as a quality indication for spirometry. Perhaps it’s time to resurrect this notion or something like it (I’d vote for 95% of the FVC).

We take it for granted that expiratory time should be a good indication of test quality (and it probably is) but given the uncertainty of the expiratory time measurement I’m not sure how to prove that. In addition although a 6 second expiratory time seems to be reasonably correct it is still an arbitrary length of time. If expiratory time is going to be used as a quality indicator shouldn’t it also acknowledge that expiratory time generally increases with age?

Note: Even though the fact that expiratory time increases with age is something we all “know” to be true, I don’t think I’ve ever seen this studied. Nor do any of the spirometry reference equations include predicted expiratory time. Given this is the case, how do we know what an acceptable expiratory time really is?

I’m not saying that expiratory time isn’t useful as an indication of test quality but I do think it’s clear that we need a better definition of how to measure expiratory time and a better definition of what constitutes an acceptable expiratory time.

This is getting a bit far off track however, since the more immediate problem is that I can’t always get our lab software to report the expiratory time for the largest FVC, at least not without compromising other reported values. I also can’t get the volume-time curve to always come from the spirometry effort with the largest FVC for much the same reasons. Admittedly it’s just my opinion the flow-volume loop and PEF should be associated with the FEV1, and the expiratory time and the volume-time curve with the FVC; it’s not in the ATS/ERS standards but doesn’t it make sense to do it this way?

Note: Selecting FVC and FEV1 from different test efforts does leave somewhat of a quandary about which effort the FEF25-75% (not that I believe it’s of any real use) and the FEF50% and other similar measurements should come from. It’s not an issue for me since I don’t think that any of these measurements are particularly useful when assessing spirometry. It’s an interesting problem however, since all of these measurements depend on both expiratory volume and expiratory flow rates and the criteria for selecting the “best” FEV1 and FVC aren’t necessarily the same criteria for the “best” FEF50%.

The fact that our lab software doesn’t let me mix-and-match the reported values better is due partly to decisions our equipment manufacturer made while designing and writing the software but maybe also in larger part because the ATS/ERS spirometry standards don’t address or even particularly acknowledge this issue. I don’t disagree that the “best” FEV1 and FVC should be selected from different spirometry efforts whenever necessary, but this has left the way that other measurements are selected as indeterminate. Hopefully a better definition for expiratory time and how results other than the FVC and FEV1 should be selected and grouped will be addressed whenever the ERS/ATS releases the next set of spirometry standards.

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

One of the more significant changes that appeared in the 2017 ERS/ATS DLCO standards was the requirement that rapid-response gas analyzer (RGA) systems calculate VA using a mass balance approach. This is actually more straightforward than it sounds but it does raise several issues that weren’t fully addressed in the 2017 standards.

Up until this time VA has been calculated from the inspired volume and by the amount of dilution of the tracer gas in the exhaled alveolar sample. Specifically:

 

Which is described by:

Where:

VI = inspired volume

Vd = Anatomical and Machine deadspace

Fi_trace = Inspired tracer gas concentration

FA_trace = Exhaled tracer gas concentration

The basic concept behind the mass balance approach to measuring VA is relatively simple and is described in the 2017 standard as:

“…the tracer gas left in the lung at end exhalation is equal to all of the tracer gas inhaled minus the tracer gas exhaled.”

In a flow-based RGA system, after breath-hold the subject exhales to RV and the exhaled volume is integrated from the flow signal. The gas analyzer signal, which is delayed by transit and analyzer response time, is aligned with the flow signal and the exhaled tracer gas volume is integrated from the aligned signals.

End exhalation lung volume (V_EE) is calculated using the average of the tracer gas concentration during the last 250 ml of exhaled gas and the volume of tracer gas volume that remains retained in the lung. Alveolar volume is then calculated as:

Note: Vd_Anatomical is now measured using the Fowler technique rather than being calculated from body weight or height.

In individuals with normal lungs the DLCO test gas mixture is usually homogenously mixed throughout the lung. When the exhaled DLCO gases are displayed this is usually seen as a flat tracer gas concentration.

For these individuals there will likely be little difference in the VA measured by alveolar sample concentrations and the VA measured by mass balance. In individuals with airway obstruction there is often a significant level of ventilation inhomogeneity. When this occurs it is usually seen as a sloping tracer gas line.

For these individuals the VA measured by mass balance will be higher than the VA measured by dilution. Since the way in which the CO concentration is measured (i.e. an alveolar sample) has not changed, this will lead to a higher value for DLCO. This is mentioned in the 2017 standards where they indicate that:

“The resulting DLCO measurements in COPD cases are some 8 to 15% higher.”

The standard also notes that ventilation inhomogeneity also occurs as part of aging that elderly individuals with normal lungs may also have a higher DLCO when VA is calculated by mass balance. Although not directly stated as such the 2017 standard implied that the normal DLCO reference values for elderly individuals may no longer be representative and that new studies will be required for all age groups.

The justification for calculating VA by mass balance is that it leads to a VA that will more closely approximates an individual’s actual TLC and that reproducibility will be improved. DLCO is calculated however, using the average CO concentration from the alveolar sample, not from the entire exhalation, and this makes the assumption that the CO uptake within the rest of the lung will be the same. Although this is likely to be reasonably true in individuals with normal lungs, it’s not clear how well this applies to patients with lung diseases.

One of the studies cited for the mass balance calculation of VA, Horstman et al, showed a series of graphs of DLCO/VA versus lung volume for subjects with normal lungs and subjects with COPD. The graphs for the normal subject showed a slight increase in DLCO/VA at exhaled volumes beyond the alveolar volume, whereas COPD patients showed a slight decrease. This at least implies that DLCO is homogeneous enough for the alveolar CO sample to be reasonably representative. The most notable finding however, was that the increase in DLCO seen in COPD patients was almost exactly proportional to the increase in VA measured by the mass balance approach.

Note: DLCO/VA (aka KCO, which is not the diffusing capacity per liter of alveolar volume despite being stated as such in the article) normally rises when measured at at lung volumes below TLC but in this study DLCO/VA (KCO) was measured at intervals during exhalation from an inhalation that was to TLC.

Some experimentation by myself along vaguely similar lines showed that changing the DLCO washout volume for a patient with very severe COPD (FEV1 33% of predicted) actually made little difference in DLCO:

	Washout 0.75 L	Washout 1.50 L
DLCO:	10.75	10.84
VA:	4.95	5.31
BHT:	10.86	13.11

Despite all this I have several issues that are not exactly objections, but are at least significant questions about the change in the way VA is calculated.

First, there is a conceptual issue. The VA measured by dilution has been characterized as the lung volume “seen” by the DLCO test while the VA measured by mass balance could be said to contain some “hidden” lung volume. This is not the first time that VA has been measured by indirect methods. In fact the original paper by Ogilvie et al in 1957, which set the standards for the single-breath DLCO, found that when VA was compared to TLC that the result was:

“…useless in all but extreme circumstances”

And recommended that VA be calculated in in a two-step process. Specifically, RV was measured either by helium dilution or N2 washout and VA was then calculated from:

VA = VI + RV

This approach towards measuring VA was criticized relatively quickly, partly because of the extra time required for the process but also because it was generally decided that VA measured by dilution was the “effective volume” and that adjusting VA to TLC was an inappropriate extrapolation. The method of calculating VA from VI and RV was sidelined and has been rarely used since that time.

Any difference in DLCO between the two techniques is primarily related to the difference in VA volumes. So is DLCO is more correct when calculated with the “effective” volume determined by dilution or when VA is measured by mass balance? I think this is a valid question because the mass balance VA is measured using the tracer gas concentration from the entire exhalation while exhaled CO is still measured using a standard alveolar sample. The answer has to be whether the extra volume participates in the same level of gas exchange as the rest of the lung and I can see arguments both for and against this point.

Realistically however, the same question can be applied to the DLCO calculated with an “effective” volume where a small alveolar sample is used to represent the entire lung. Since Horstman et al measured DLCO using most of the exhaled CO concentration instead of just an alveolar sample this question could have been avoided and overall DLCO accuracy improved (at least potentially) if this had been included in the 2017 standard, but since this option was not discussed it’s not possible to say why it wasn’t considered.

Next, the mass balance VA requires an accurate alignment of flow and gas analyzer signals. Although the 2017 standards specify the analyzer response time there were no specifications for sample transit time (lag time) nor were there recommendations about how it should be measured. In addition the possible error from misaligned signals has not been characterized. I bring this up because the transit time calibration on my lab’s DLCO systems routinely changes by between 20 and 40 milliseconds from one calibration to another, even when they are performed back to back. A small misalignment in signals probably won’t reduce accuracy by all that much, but at the moment it’s hard to say what actually constitutes a small misalignment and what constitutes a significant one.

Finally, the CH4 concentration near the end of exhalation is used to calculate the V_EE and this assumes that the tracer gas concentration is homogeneously distributed through this volume. The CH4 curve from a patient with COPD however, shows a steady decrease in tracer gas throughout exhalation and if this is extrapolated it implies that the CH4 concentration within the V_EE is less than that it is at end-exhalation. This in turn implies that under these circumstances the V_EE is being underestimated.

Moreover, the accuracy of the V_EE and mass balance VA is to some extent dependent on a full exhalation to RV following the breath-hold. The 2017 standards however, do not include any quality indicators for exhalation past acquiring the alveolar sample. It’s unclear what effect a suboptimal exhalation will have on V_EE and the mass balance VA.

The changes involved in the 2017 DLCO standards will provide the fodder for any number of technical and clinical research studies. The biggest changes in DLCO will likely be seen in lung disorders with some degree of ventilation inhomogeneity but since it has not been studied across the full range of obstructive and restrictive lung disorders it’s not possible to predict where differences in DLCO may appear. In particular, because ventilation inhomogeneity normally increases with age, new reference equations will be needed sooner rather than later.

I have no significant objections towards measuring VA by mass balance. It’s relatively straightforward and at least as valid an approach as measuring VA by dilution. Since it requires the proper operation of a number of mechanical, electronic and software systems I will however, retain some reservations about the accuracy of this approach until some of the possible errors are better characterized.

The new 2017 standards do not make “classical” DLCO systems obsolete and most labs are unlikely to be able to implement its recommendations on VA immediately. Many of us will have to wait until our current testing systems are replaced before having to deal with the new aspects of the 2017 standards, and capital budgets being what they are, that is probably years away. Although my lab’s equipment already have RGAs, we will need a fairly significant software update before we measure VA by mass balance and since our equipment vendor is not particularly noted for the rapidity at which it updates its software I suspect we will also have a prolonged wait.

What the new standard does is to provide a road map for the future. At some point we will have to deal with the fact that some patients will have noticeable change in their DLCO. Given that for most of us this will be a while in the future, there will probably be time for at least some of the technical and clinical research to catch up before we have to take that step.

References:

Graham BL, et al. 2017 ERS/ATS standards for the single-breath carbon monoxide uptake in the lung. Eur Respir J 2017; 49: 1600016.

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

Mortin JW, Osborne LG. A clinical review of the single breath method of measuring the diffusing capacity of the lungs. Chest 1965; 48: 44-54.

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

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

The new ERS/ATS standards for DLCO testing were published in the January issue of the European Respiratory Journal. The article was published as open access and can be downloaded from the ERJ website.

The biggest difference between the new standards and those from 2005 is that they are now primarily oriented towards Rapid-response Gas Analyzers (RGA). The authors explicitly state that the new standards do not make older systems that use discrete alveolar sampling and slower gas analyzers obsolete, but many of the new suggestions and requirements for labs and manufacturers require systems with a RGA.

The differences between the 2017 and 2005 standards that I’ve been able to find include:

♦ Flow accuracy was not specified in the 2005 standard but is now required to be ± 2% over a range of ± 10 L/sec.

♦ Volume accuracy is now required to be ± 2.5% (± 75 ml) instead of ± 3.5%. Notably the 2005 standard included a ± 0.5% error in the calibrating syringe. The accuracy of the 3-liter syringe is now stated separately. In the 2005 standard volume accuracy was over an 8-liter range. No volume range is specified in the 2017 standard.

♦ RGA response time (analyzer rise time) had not previously been specified but is now required to be ≤150 milliseconds. Sample transit time was discussed but no specific recommendations were made. Sample transport issues such as Taylor dispersion, gas viscosity and turbulence at gas fittings was also discussed and although it was suggested that manufacturers attempt to minimize these effects no specific recommendations were made.

♦ Analyzer linearity for both RGA and discrete sample systems has been relaxed to ± 1.0% in the 2017 standards from ± 0.5% in the 2005 standards.

♦ CO analyzer accuracy for both RGA and discrete sample systems is now specified as ≤10 ppm (which is ±0.3% of 0.3% CO). It was previously specified as ± 0.0015% (which is ± 0.5% of 0.3% CO).

♦ Interference from CO2 and water vapor for both RGA and discrete sample systems is now specified as ≤10 ppm error in CO (when CO2 and water vapor are ≤5%). Interference was recognized as a problem in the 2005 standard but error limits were not specified.

♦ Digital sampling rate was not discussed or specified in the 2005 standards. It is now specified as a minimum of ≥100 hz with a resolution of 14 bits. A 1000 hz sampling rate is recommended.

♦ Analyzer drift is specified in the 2017 standard as ≤ 10 ppm for CO and 0.5% of full scale for the tracer gas over 30 seconds. The 2005 standard specified drift as 0.5% of full scale over 30 seconds and did not differentiate between CO and tracer gases. The 2017 standards recommends that manufacturers provide a test mode to test drift.

♦ Barometric pressure sensor accuracy is now required to be within ±2.5%. This was not previously specified.

♦ Manufacturers of RGA systems are now required to include the following features:

• Monitor and report end-expiratory tracer gas and carbon monoxide concentrations and to alert the operator if the washout from previous testing is incomplete.
• Compensation for end-expiratory gas concentrations prior to test gas inhalation in the calculation of VA and DLCO.
• Ensure proper alignment of gas concentration signals and the flow signal (although notably specifications for this are not included).
• Measure anatomic dead-space using the Fowler method.
• Display a graph of exhaled gas concentration versus volume (not time) to confirm the point of dead-space washout and to report the amount of manual adjustment if this was done.
• Measure VA using all of the tracer gas data from the entire maneuver in the mass balance equation.
• Report the DLCO adjusted for the change in PAO2 due to barometric pressure.

♦ Further recommended (but not required) RGA options include:

• Ability to input simulated digital test data and compute DLCO, VA, TLC and Vb with ± 2% accuracy expected.
• Report the DLCO adjusted for change in PAO2 due to PACO2 with ± 2% accuracy.

♦ The maximum inspiratory pressure for demand valves has been reduced to <9 cmH2O from <10 cm H2O.

♦ Machine deadspace for adult testing has decreased to 200 ml from 350 ml. There was a further recommendation that machine deadspace should be smaller for children and patients with a VC <2.0 L but no specific requirements were made.

♦ Daily volume calibration must now be performed three time with a 3-liter syringe with using varying flow rates between 0.5 and 12.0 L/sec (injection times 0.5 – 6.0 seconds). Accuracy was not previously specified and now must be <2.5% error.

♦ Timer accuracy was specified in the 2005 standards. There are no timer specifications in the 2017 standards.

♦ Flow sensor zeroing prior to testing is now required.

♦ Gas analyzer linearity must now be checked monthly. The 2005 standards specified every three months. Manufacturers are urged to automate this process.

♦ A monthly calibration syringe leak test is now required.

♦ Both biological and calibration syringe QC testing are now required weekly. Previously either biological or calibration syringe QC were to be preformed weekly.

♦ Previous calibration syringe QC required the measured inspired volume (VI) to be “~3.30 L”. 2017 standards require accuracy to be ± 300 ml of VI * {STPD to BTPS conversion factor}. [Please note that there is a typo in the paragraph specifying this on page 8, line 8 in the 2017 standards where VA was substituted for VI].

♦ Changes in biological QC requiring action have been relaxed to a >12% change or >3 ml/min/mmHg (whichever is larger) from a simple >10% change. The 2017 standards also state that a mean of 6 prior tests should be used for this while the 2005 standards merely stated “from previous values”. Manufacturers were urged to developed automated QC processes.

♦ Calibration and QC logs can now be kept in a digital file folder.

♦ It was recommended that deep breaths during the pre-test tidal breathing period should be avoided in the 2005 standards but this was not included in the 2017 standards.

♦ The maximum acceptable time for exhalation to RV has been increased from 6 seconds to 12 seconds.

♦ Target VI has changed from ≥85% of the patient’s largest VC to ≥90%. The 2017 standards state however, that a VI of ≥85% of the patient’s largest VC is acceptable if the VA is within 200 ml or 5% (whichever is larger) of the patient’s highest VA from acceptable DLCO maneuvers.

♦ The 2017 standards now recommend that with RGA systems the exhalation following breath-holding should continue to RV in order to calculate VA using a mass-balance equation. Total expiratory time for discrete sample systems (washout and sample collection time) is still ≤4 seconds but is specified as ≤12 seconds in RGA systems.

♦ The DLCO test gas mixture is now required to contain 21% O2. The 2005 standards discussed a range of FIO2’s from 0.17 to 0.21 but only recommended that “inspired oxygen partial pressure values similar to the reference set used in the interpretation” be used.

♦ The required interval between tests (4 minutes minimum, 10 minutes for patients with severe obstruction) now includes the recommendation that the tracer gas concentration at end-exhalation (prior to the inhalation of the test gas mixture) should be ≤ 2% of the inspired concentration.

♦ The 2017 standards now recommend that the end-exhalation concentrations of CO (prior to inhalation of the test gas mixture) be used to adjust DLCO tests for CO back-pressure, to calculate COHb and to compensate for the effects of water vapor and CO2 on gas analyzers.

♦ The 2017 standards discuss the effect that prior testing (spirometry, bronchodilators and N2 washouts) have on DLCO and states that:

• bronchodilators are unlikely to affect DLCO and may therefore be used prior to DLCO testing
• prior spirometry efforts may affect DLCO but this has not been proven and therefore makes no recommendations against performing spirometry prior to DLCO testing
• sufficient time for alveolar O2 levels to return to normal is needed (2 times O2 wash-in time) after performing an N2 washout test. The standard recommends against performing N2 washout tests before DLCO testing but did not make this a requirement.

♦ The 2017 standards recommend that RGA systems calculate VA using mass-balance equations and this is discussed in detail (pages 17-19). This was not previously discussed nor was it an option.

♦ The equation for calculating anatomical deadspace using height (equation 20, page 16) is different from the one suggested in the 2005 standard (equation 10, page 728) but appears to be a restatement rather than being completely different.

♦ The 2017 standards discuss the measurement of anatomical dead space using the Fowler technique in detail. This was not previously discussed.

♦ The 2017 standards discuss flow and gas analyzer signal alignment in detail. This was not previously discussed.

♦ The 2017 standards discuss KCO with significantly more detail than in the 2005 standards. In particular although KCO is calculated from DLCO/VA it should be reported as KCO and not DLCO/VA.

♦ The 2017 standards discuss measuring the Phase III slope during exhalation as an index of ventilation inhomogeneity but does not specifically recommend it (probably a good idea since Phase III slopes during a single-breath N2 washout are usually obtained with low and constant expiratory flow rates which aren’t necessarily congruent with the expiratory flow rates during a DLCO maneuver and the differences between the manner in which these slopes are measured has not been studied).

♦ Repeatability between DLCO tests is now 2.0 ml/min/mmhg compared to 3.0 ml/min/mmHg in the previous standards.

♦ The 2017 standards include a suggested scoring/grading system for test quality based on inspired volume, breath-holding time and sample collection time (Table 3, page 22).

♦ Although the 2017 standards discusses the use of expired CO2 to estimate PAO2 it does not specifically recommend this.

♦ The 2017 standards have a new equation (38, page 24) used to correct DLCO for end-exhalation CO.

♦ The 2017 standards have new equations for altitude and barometric pressure correction (40 & 41, page 25) that are not a restatement of the previous equation (16, page 730).

♦ The 2017 standards include equations (42 & 43, page 25) to estimate barometric pressure at altitude that were not in the previous standards.

♦ The 2005 standards included equations to correct DLCO for alveolar volume (19 & 20, page 730) that are not discussed and not included in the 2017 standards.

♦ The DLCO results that are reported (Table 4, page 26) are now required to include:

• DLCO adjusted for barometric pressure
• DLCO LLN and/or Z-score
• VA LLN and/or Z-score
• KCO (instead of DLCO/VA)
• KCO LLN and/or Z-score
• Barometric pressure
• Average Breath-hold time
• Fowler anatomical dead space (RGA systems only)
• Single-breath TLC (RGA systems only)
• Test quality grade for acceptable maneuvers
• Reference values source
• Graphs of full maneuver.
• Graphs of exhaled gas concentrations versus volume (RGA systems only).

♦ The 2017 standards do not recommend any specific reference equations but note that many of the equations in use predate the 2005 standards. A short list (Table 5, page 27) of studies that were performed using the 2005 standards was included but it should be noted that the majority of the listed studies are pediatric and not adult.

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Overall however, I am pleased that new DLCO standards have finally been released and that they are as comprehensive and forward looking as they are. I am pleased to see that many issues I had raised in previous blog postings have been addressed. I am also pleased that the bar has been raised on technical specifications, including calibration and quality control, and that care that has been taken make the standards as applicable to both old and new test systems.

There are two issues, however that I feel the need to comment on.

One of the biggest new recommendations is for patients on RGA systems to exhale to RV following the breath-hold period and that VA should be calculated with a mass-balance equation using the tracer gas concentrations that occur during the entire exhalation. DLCO is calculated however, using the CO gas concentrations from just the alveolar sample. Although the VA derived using mass balance will more likely approximate TLC, particularly when airway obstruction is present, other than the fact that this would raise the measured DLCO in patients with COPD the overall validity of this approach was not discussed.

I am still hard-pressed to understand why the 2017 standards continue to recommend that hemoglobin correction be performed on the predicted DLCO and not the observed DLCO, particular since the observed DLCO is corrected for PAO2, altitude and end-exhalation back pressures. The logic of this approach not only seems backwards but makes the comparison of trended DLCO results difficult. I read section of the new standards on hemoglobin correction carefully but no particular justification for this was put forward.

In the past I would have taken the release of the new DLCO standards as a sign that new standards for spirometry, lung volumes, methacholine challenge testing(?) and interpretation would also be released soon. The release of the previous standards in 2005 was troubled by confidentiality issues (early release of standards by insiders to some manufacturers) and this time around the ERS and ATS are playing their cards close to their vest. We can only wait and hope.

References:

MacIntyre N, et al. Series ATS/ERS task force: Standardisation of lung function testing. Standardisation of the single-breath determination of carbon monoxide uptake in the lung. Eur Respir J 2005; 26: 720-735.

Graham BL, et al. 2017 ERS/ATS standards fir single-breath carbon monoxide uptake in the lung. Eur Respir J 2017; 49: 1600016

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

It’s a tradition to come up with New Year’s resolution in order to improve ourselves. How about some resolutions to improve our labs?

1. Review and update the procedure manual

When was the last time you reviewed your procedure manual? Procedure manuals should be reviewed by the lab manager and medical director annually. It’s time to re-read the ATS/ERS guidelines and then review and update your procedure manual. Both your old staff and your new staff need to know what to do and how to do it. Your procedure manual is also going to be the first thing that anybody looks at if your lab is ever inspected.

2. Biological QC

Daily calibrations (and you’re doing daily calibrations and keeping a log of them, aren’t you?) are not enough to make sure our test systems are operating correctly. Regular (weekly, bi-weekly or monthly) biological quality control on ourselves with a Levey-Jennings chart is still the best way to do this. Don’t put it off. Biological QC is not an option; it’s a minimum requirement for any medical lab.

3. Staff certification

The staff certification requirements differ widely from state to state. Regardless of what your state mandates it is time for all PFT labs to require CPFT certification as a minimum for all staff members and RPFT certification for supervisors. In the same manner the staff in medical offices and clinics that only perform spirometry should be required to get an AARC spirometry certificate or a NIOSH certificate. Respect is not a given; it has to be earned. Nobody is going to help the PFT profession but us and it’s time to pull ourselves up by our own bootstraps.

4. Make better use of what you already have

We all want new equipment but aren’t likely to get it anytime soon. Make better use of what you already have by performing simple tests that improve patient diagnostics. Upright & Supine spirometry only needs a place for a patient to lie down. Hypoxic Altitude Simulation Tests (HAST) only needs a tank of 15% O2, some disposable supplies and a pulse oximeter. Perform SVC as well as FVC testing during routine spirometry to get the highest VC. 6-minute walk testing only needs corridor space, a stopwatch and a pulse oximeter.  Waste not, want not.  Your patients and physicians will thank you.

5. Update your reference equations

The ATS/ERS specifically recommends reviewing and updating your reference equations at least every 10 years. How many labs are still using outdated reference equations from the 1970’s and 1980’s like Morris, Knudson or Crapo? It’s time to bite the bullet and update to NHANESIII or GLI. The fact that there will be discrepancies between the old and the new percent predicteds and that the interpreting physicians will have to re-learn what’s normal is not a valid excuse. You’re not helping your patients if you continue to use obsolete equations. Deal with it and move on.

Don’t break these resolutions. Make 2017 the year you’re going to keep them.

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

I’ve been reviewing the literature on PFT interpretation lately and in doing so I ran across one of the issues that’s bothered me for a while. Specifically, my lab has been tasked with following the 2005 ATS/ERS guidelines for interpretation and using this algorithm these results:

	Observed:	%Predicted:	LLN:	Predicted:
FVC:	2.83	120%	1.76	2.36
FEV1:	1.77	100%	1.26	1.76
FEV1/FVC:	63	84%	65	75

would be read as mild airway obstruction.

Although it’s seems odd to have to call a normal FEV1 as obstruction I’ve been mostly okay with this since my lab has a number of patients with asthma whose best FVC and FEV1 obtained at some point in the past were 120% of predicted or greater but whose FEV1 frequently declines to 90% or 100% of predicted. In these cases since prior studies showed a normal FEV1/FVC ratio then an interpretation of a mild OVD is probably correct even though the FEV1 itself is well above the LLN, and this is actually the situation for this example.

In other cases, however this is a lot less clear. For example:

	Observed:	%Predicted:	LLN:	Predicted:
FVC:	3.83	127%	2.35	3.01
FEV1:	2.53	110%	1.75	2.30
FEV1/FVC:	66	86%	67	77

In this case, the FEV1 is much further above the LLN, the flow-volume loop is fairly normal and there are no prior spirometry results.

Anyway, while doing a Google Scholar search I found a letter to the editor that Dr. Paul Enright had written shortly after the ATS/ERS interpretation guidelines had been published. In this letter he criticized the guidelines over several issues but in particular for the decision to change how a reduced FEV1/FVC ratio with a normal FEV1 was interpreted.

In the 1991 ATS guidelines on interpretation the recommendation was to interpret a reduced FEV1/FVC ratio and a normal FEV1 (or at least one that was ≧100% of predicted) as “May be a physiological variant” and this was dropped from the 2005 guidelines. What this phrase referred to was the concept of dysanaptic lung growth that had been first proposed by Jere Mead around 1980 and is thought to occur when the alveolar tissue growth in an individual’s lungs outpaced the growth of their airways. His thought was that this developmental pattern would lead to an elevated FVC but a normal-ish FEV1. Mead based his conclusions on the results of physiological testing but animal studies since that time have shown that dysanaptic lung growth can occur following exposure to such things as nicotine during gestation, post-pneumonectomy and exposure to hypoxia during the period of developmental growth following birth.

The condition of an elevated FVC and reduced FEV1/FVC ratio appears to have been only rarely studied, however. The single study I’ve been able to find was performed relatively recent and was limited to 40 individuals. It’s conclusions could be read as supporting the 2005 ATS/ERS guidelines, although it was published several years after them. Using questionnaires most of the individuals were assigned to asthma, rhinitis or COPD groups with only a small minority designated as asymptomatic. Each subject performed plethysmographic lung volumes, DLCO, methacholine challenge, single-breath N2 washout as well as pre- and post-BD spirometry. As part of the findings the asthma and COPD groups showed signs of gas trapping and early airway closure, and a small minority from all groups showed signs of airway hyperresponsiveness (a significant response to methacholine or bronchodilator).

Realistically however, although the study showed differences in RV/TLC ratio, DLCO and closing volume that were statistically significant between some of these groups, the differences were subtle and unlikely to be evident in routine PFT testing. As importantly, there was no longitudinal PFT data so it isn’t possible to say whether the reduced FEV1/FVC ratio was due to the progression of an underlying lung disorder or whether it had always been present.

I think that Dr. Enright’s criticism has a lot of validity. Whether or not an individual with a reduced FEV1/FVC ratio and elevated FVC is due to dysanaptic lung growth or instead due to an obstructive lung disorder can only be conjecture (particularly if they are otherwise asymptomatic) unless there is clear evidence that the FEV1/FVC ratio had been normal at some time. I would note that at my lab a number of these individuals are sent for pulmonary function testing not because of any symptoms but instead because their chest x-ray is “abnormal”. In a couple of instances I can say it was specifically because their lung was abnormally long with a flat diaphragm which was interpreted by the radiologist as a sign of COPD but in retrospect may instead be due to an above-normal FVC.

We mostly take it for granted that the development of alveolar tissue and the airways are always proportional, and that both of these are proportional to height (well, along with age, gender and ethnicity). To a reasonable approximation this is true, but having said that there are always outliers and Mead’s observation provides an explanation for one group of these.

One of the long-standing problems in interpreting pulmonary function tests is that there is a certain amount of overlap between normal and abnormal lung function. Although there is still some disagreement about the actual threshold, a reduced FEV1/FVC ratio has long been considered to be a particularly reliable signal for the presence of airway obstruction. In this instance however, when the FVC is elevated a reduced FEV1/FVC ratio could likely be, as stated in the 1991 ATS guidelines, “a physiological variant” instead of being due to airway obstruction.

One final thought is that I find it interesting that the concept of dysanaptic lung growth does not appear to have ever been applied to individuals with normal FVC’s and reduced FEV1’s. It’s not that I have any particular doubt that disproportionate lung growth can occur, but if it is present in individuals with elevated FVC’s why can’t it also be present in individuals with normal FVC’s? And how would we be able to know the difference?

References:

ATS. Lung function testing: selection of reference values and interpretative strategies. Am Rev Respir Dis 1991; 144: 1202-1218.

Barisione G, Crimi E, Bartolini S, Saporiti R, Copello F, Pellegrino R, Brusasco V. How to interpret reduced forced expiratory volume in 1 s (FEV1)/vital capacity ratio with normal FEV1. Eur Respir J 2009; 33(6): 1396-1402.

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

Enright P. Flawed interpretative strategies for lung function tests harm patients. Eur Respir J 2006; 27(6): 1322-1323.

Mead J. Dysanapsis in normal lungs assessed by the relationship between maximal flow, static recoil, and vital capacity. Am Rev Respir Dis 1980; 121: 339-342.

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

We’ve all run across the Fick equation for cardiac output at one time or another. There are very limited circumstances when we’d ever get to use it but at the same time it’s one of those simple but incredibly profound equations that’s also a foundation of pulmonary physiology.

The Fick equation is:

where:

VO2 = oxygen uptake

CvO2 = mixed venous oxygen content

CaO2 = arterial oxygen content

And what it describes is:

It’s a mass-balance equation that basically says that what goes in must come out, but how do you get from oxygen uptake to cardiac output?

The key part to this is oxygen content. The most common form of the oxygen content calculation is:

O2 Content (ml/decaliter) = (Hgb x 1.36 x SaO2) + (0.0031 x PaO2)

Where:

Hgb = hemoglobin (grams/decaliter)

SaO2 = fractional oxygen saturation

PaO2 = partial pressure of O2 (mmHg)

If normal arterial values were plugged in, it would look like:

O2 Content (ml/decaliter) = (14.6 x 1.36 x 0.98) + (0.0031 x 100)

which calculates to 19.76 ml/decaliter.

The constants in this equation are based on the fact that hemoglobin in expressed in grams/decaliter but oxygen uptake is usually expressed in L/min or ml/min so in order to be compatible in the Fick equation it is usually modified as:

O2 Content (ml/L) = 10 x ((Hgb x 1.36 x SaO2) + (0.0031 x PaO2))

or

O2 Content (L/L) = 0.01 x ((Hgb x 1.36 x SaO2)+(0.0031 x PaO2))

Note: One fascinating point the O2 content equation shows is that the amount of oxygen in blood is almost the same as it is in air. Without hemoglobin or a molecule similar to it the amount that would be in suspension is described by the second part of the equation (0.0031 x PaO2) which is only about 1.6% of the total amount. If we didn’t have hemoglobin then neither we nor any other animal could maintain any kind of a high-energy metabolism.

The difference between mixed venous and arterial O2 content indicates the amount of “space” that’s available for oxygen. For example, at rest mixed venous blood would nominally contain:

CvO2 = 10 x ((14.6 x 1.36 x 0.75) + (0.0031 x 40)) = 150 ml

and for arterial blood is:

CaO2 = 10 x ((14.6 x 1.36 x 0.98) + (0.0031 x 100)) = 198 ml

Therefore, for every liter of blood, the amount of space available for oxygen is:

198 ml – 150 ml = 48 ml

At rest, oxygen uptake is nominally 250 ml, so for the above a-v O2 content difference, this amount of oxygen would need:

250/48 = 5208 ml

of blood. Since VO2 is expressed in ml/min this means that cardiac output would have to be 5208 ml/min or 5.208 L/min.

During exercise, oxygen uptake can increase many times above its resting value. Cardiac output increases also, but not as much and the reason for this is that the a-v O2 content difference increases. At rest mixed-venous blood has a PO2 of approximately 40 but during exercise it easily decrease to 30 mmHg (with oxygen saturation of 54%) or even lower. When this happens O2 content of mixed venous blood is:

CvO2 = 10 x ((14.6 x 1.36 x 0.54) + (0.0031 x 30)) = 108 ml

Assuming that the arterial oxygen content remains the same, then the a-v O2 content difference would be 90 ml and for an O2 uptake of 1500 ml/min (a six-old increase) cardiac output would be:

1500/90 = 16.67 L/min

which is only 3.2 times as great. This means there is a relationship between oxygen uptake and cardiac output, but without knowing the a-v O2 content difference the exact relationship has to be unknown.

As useful as it might be to measure cardiac output during exercise, unfortunately for us (and probably fortunately for our patients) mixed-venous blood can only be obtained from a catheter whose tip is placed in the pulmonary artery or in the vena cava just outside the right ventricle. This type of cathetrization is more than just a bit invasive and is therefore usually only performed under the controlled circumstances of the ICU and cardiac cath labs.

The most important point shown by the Fick equation is that oxygen uptake has a very limited ability to increase without a somewhat corresponding increase in cardiac output. Interestingly, although the converse is mostly true:

there are circumstances where the a-v O2 content difference can be decreased and when this happens, cardiac output can be elevated but O2 uptake can be normal. One example of this is mitochondrial myopathies where, due to a decreased O2 uptake by body tissue, the mixed-venous PO2 can be as high as 70 (with an oxygen saturation of 93.8%). Under these conditions the mixed-venous O2 content would be:

CvO2 = 10 x ((14.6 x 1.36 x 0.938) + (0.0031 x 70)) = 188 ml

and cardiac output could be as high as:

250/(198-188) = 25.0 L/min

at rest. But this is an unusual circumstance which is unlikely to be seen for most individuals.

The most important point is that there is a connection between cardiac output, oxygen uptake and the O2 content of blood. These are all core components of pulmonary physiology and the Fick equation eloquently describes their relationship.

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

I was recently contacted by the manager of a lab that was having problems with their N2 washout lung volumes. Specifically, their N2 washout lung volumes (FRC in particular) were coming out low and everyone being tested on the system looked like they had restriction. The system has been checked by the manufacturer’s service techs several times and they’d replaced the tubing, the O2 tank and a number of parts. Service first asked them to wait between tests and then not to bother. Most lately they’ve been asked to calibrate the system before each test. Despite all this, their system continues to under-estimate lung volumes.

We’ve all had seemingly intractable problems with our test systems at one time or another. Sometimes they’re problems that can only be fixed by replacing major components, such as a gas analyzer or a motherboard. Sometimes they turn out to be something simple that nobody noticed despite looking straight at it numerous times. Experience and good technical support helps, but for every test system there has to be at least a couple of problems that are either uncommon, difficult to diagnose or are happening for the first time. When this happens it’s best to go back to basics and try to see what it is that’s most likely to explain the symptoms.

N2 washout lung volume measurements measure the amount of nitrogen residing in the lung and use this to estimate the volume of the entire lung. Closed circuit lung volume measurements using nitrogen were first attempted in 1932 by Christie. Christie’s approach used a known volume of oxygen to dilute the nitrogen in the lung but accuracy was limited at least in part because the amount of oxygen in the closed circuit was constantly changing due to the subject’s oxygen uptake. In 1940 Darling et al demonstrated an open circuit technique that is the basis for current N2 washout tests. In this approach the nitrogen in a subject’s lung was washed out with 100% O2 and their exhaled air was collected in a Tissot spirometer. After a certain amount of time (nominally 7 minutes) the exhaled volume and the N2 concentration in the Tissot spirometer was measured. The amount of nitrogen that had been exhaled is then calculated using simple math and the subject’s FRC is estimated from that.

Although relatively straightforward, this approach to measuring lung volumes was both time-consuming and cumbersome. Sometime around the 1980’s rapid response O2 analyzers became available and it was realized that everything in exhaled air that wasn’t O2 (or CO2) had to be N2 (or argon). This meant it wasn’t necessary to measure exhaled nitrogen, just exhaled O2. It also meant that N2 washout systems would only need to consist of an O2 source, flow sensor and an O2 analyzer.

Although it greatly simplifies the equipment requirements, this approach requires that the flow and gas analyzer signals be matched and then integrated in order for the volume of N2 washed out with each breath to be accurately measured. An advantage though, is that since the nitrogen concentration (or rather O2 concentration) of each breath is being monitored, it is possible to stop the test when a target N2 concentration is reached, and on my lab’s N2 washout systems this is 2%.

So what are the failure modes for N2 washout?

Like all gas dilution tests, the most common problem is a system leak of some kind. An inspiratory leak will bring in excess nitrogen and a large enough leak will be relatively obvious since it will never be possible to reach the target N2 concentration. A smaller leak however, will only prolong a test and then cause FRC to be overestimated. Since the problem in question is a reduced FRC, not an elevated one, an inpiratory leak (even one involving the patient) is an unlikely culprit.

An expiratory leak on the other hand could cause the system to underestimate the exhaled volume and this would cause FRC to be underestimated. However, for this to happen in a flow-based system, the leak would have to occur before the flow sensor and since an inspiratory leak has been ruled out it would have to be a one-way leak. This isn’t necessarily impossible, but tidal breathing is usually monitored during the N2 washout and an expiratory leak (or an inspiratory leak) would cause noticeable drift.

What if airflow somehow bypassed the flow sensor during both inspiration and expiration? This could cause the expiratory volume to underestimated and if the amount of bypass was equal for both inspiration and expiration the tidal breathing would not drift by much. A problem with this is that one additional clue is that the SVC volume matched the FVC volume so if any expiratory flow is bypassing the flow sensor it has to be a tiny amount. Inspiratory and expiratory flow could also be underestimated due to a calibration error but the fact that SVC matches the FVC, and that both were usually normal, pretty much rules this out as well.

Assuming there’s nothing wrong with the gas analyzer the exhaled N2 could also be underestimated due to a calibration error. Because the N2 concentration is derived from an O2 analyzer, the O2 signal would have to be more biased towards higher values than it should be in order for N2 to be under-estimated. O2 analyzers used for N2 washout are usually calibrated with room air and 100% O2. If the 100% O2 calibration was being contaminated with room air this would cause the O2 concentration to be overestimated (and derived N2 concentration to be underestimated) during the test. Although test systems usually display gas concentrations in some way during the test, this is usually as just the end-exhalation N2 concentration data points and not the entire waveform. Since a symptom of this type of analyzer calibration error would be an O2 concentration above 100% (or derived N2 concentration below 0%) during inhalation this would not necessarily be an obvious problem. One way to determine this was happening would be to inspect the measured gas concentrations while the gas sample line was placed in room air and 100% O2 while disconnected from the testing manifold.

Note: The opposite problem would happen if the room air calibration was being contaminated with O2. If this occurred the O2 concentration would be under-estimated and the derived N2 concentration overestimated.

The gas sample line transit time and O2 analyzer rise time are needed to match the flow and gas analyzer signals and if they are incorrect (and I suspect it doesn’t matter all that much whether they are incorrect in the + or – directions) then the exhaled N2 volume will be underestimated (or under some circumstances possibly overestimated). Transit time and rise time are usually determined by rapidly switching the calibration gas on and off, usually with a solenoid valve or its equivalent. A sticking solenoid valve that was slow to open and close even by a small amount could elevate the measured transit time and this would cause the flow and gas analyzer waveforms to be matched incorrectly. This would be difficult to detect and might only show up by comparing the calibrated transit and rise times over time. Differences of a few 10’s of milliseconds are unlikely to make a significant difference, but differences above 100 or 200 milliseconds could be an indication that transit and rise time are being calibrated incorrectly.

Finally, there could also be leak from the oxygen source used during the N2 washout into the sample line. This would also bias the measured O2 concentrations upwards (and derived N2 concentrations downwards). Conversely, excess room air in the sample line would cause the N2 volume to be overestimated. Whether this could happen at all would depend a lot on the arrangement of the breathing manifold and would be remotely possible in some and impossible in others. This would not be an obvious problem but it would disappear when the manifold was replaced.

To summarize:

FRC Underestimated:

Possible causes:	Symptoms:
Exhalation Leak	SVC ≠ FVC, tidal volume drift
Flow sensor mis-calibration	SVC < FVC or SVC & FVC decreased
Room air contamination 100% O2 calibration	O2 >100% or N2 <0% during inhalation
Incorrect Transit/Rise time	Transit/Rise > 100-200 msec compared to older calibrations
O2 leak into sample line	Disappears when manifold is replaced

FRC Overestimated:

Possible causes:	Symptoms:
Inhalation Leak	SVC ≠ FVC, tidal volume drift
Flow sensor mis-calibration	SVC > FVC or SVC & FVC elevated
100% O2 contamination room air calibration	O2 < 100% or N2 > 0% during inhalation
Incorrect Transit/Rise time	Transit/Rise > 100-200 msec compared to older calibrations
Room air leak into sample line	Disappears when manifold is replaced

I passed most of these suggestions back to the manager that asked about troubleshooting their N2 washout in a somewhat abbreviated form and have taken the opportunity to expand on them here. I haven’t yet heard back whether any of them are correct and it will interesting to see if one of them is the cause of their FRC measurements error or whether it turns out to be something completely different.

There are other errors that may be very specific to particular testing systems. A general approach however, is to consider what could be causing the N2 volume to either be underestimated or overestimated depending on whether the FRC is routinely coming out low or high. In order to do this, we all need to have a good understanding of the technical aspects of the N2 washout test and the equipment.

Many of these possible errors are not obvious either during an N2 washout test or the calibration of the test equipment. This is why regular biological QC is important and why, if you’re not routinely performing it, you should be.

References:

Christie RV. The lung volume and its subdivisions. I. Methods of measurement. J Clin Invest 1932; 11: 1099-1118.

Darling RC, Cournand A, Richards DW. Studies on the intrapulmonary mixture of gases. III. An open circuit method for measuring residual air. J Clin Invest 1940; 19(4): 609-618.

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

Cigarette smoking raises the probability that an individual will get lung cancer, chronic bronchitis and/or emphysema (among many other things). Nicotine is addictive and smokers often need significant motivation in order to quit. Lung age is a tool that was designed to give smokers an additional incentive to do this. The concept is fairly simple and that is by reformulating an FEV1 reference equation it is possible to take an individual’s actual FEV1 and estimate the age of their lungs (ELA). Because cigarette smoking can cause airway obstruction it tends to mimic premature lung aging which means that when a smoker’s FEV1 is used to calculate an ELA it can be significantly greater than their real or chronological lung age (CLA).

This idea was first proposed by Morris and Temple in 1985. Using Morris et al’s 1971 spirometry reference equations they studied the effect of calculating an estimated lung age (ELA) using observed FVC, FEV1 and FEF25-75 values both singly and in combinations and found that the FEV1 had the lowest standard error. The ELA calculation based on Morris et al’s FEV1 reference equations has achieved a degree of popularity and is available on at least one personal spirometer (Pulmolife, sold by Carefusion, MDSpiro and Vitalograph) and as an on-line calculator from a couple different websites (Chestx-ray.com and Lung Foundation of Australia).

Interestingly, the effectiveness of ELA towards quitting smoking has been studied only a handful of times. One often-quoted study of smoking cessation (Parkes et al) saw double the quit rate (13.6% vs 6.4%) when ELA was used as an intervention but the study’s methodology has since been criticized and it’s results have not been duplicated.

As importantly, the Morris and Temple’s lung age calculation is based on a single reference equation and there has been no attempt to adjust it for ethnicity. Significant discrepancies between the Morris and Temple ELA and an ELA equation derived from a study relevant to a local population were first pointed out in a paper by Newbury et al in 2010. In particular many smokers who had an ELA greater than their CLA using an equation based on the local population had an ELA that was less than CLA when using the Morris and Temple equation.

In a later paper Newbury et al compared the Morris and Temple ELA equation with a number of equations derived from the most commonly used FEV1 reference equations and continued to find significant discrepancies. This has been seconded by the study of Ben Saad et al which found that none of the ELA equations were relevant for a North African population.

The fact is that significant discrepancies exist between all ELA reference equations and this is because they act to magnify small differences in FEV1. The normal decline in FEV1 per year (very approximately 0.025 L/year) is small relative to the FEV1 volume which in turn means that the differences in predicted FEV1 from even the most commonly used reference equations within the same ethnicity can be equal to decades in ELA.

It is at least partly for this reason that Hansen et al proposed using the FEV1/FVC and FEV1/FEV6 ratio rather than the FEV1 to calculate the difference between ELA and CLA. Hansen et al based their ELA equations on the NHANESIII data set but indicated their belief that FEV1/FVC and FEV1/FEV6 ratios are relatively universal. Although this approach appears to make sense it too has been criticized as circular reasoning because the equations were validated using the same data set they were derived from.

Although lung age appears to be a simple and effective way to present facts to a patient, the lung age calculation is overly prone to both over- and under-estimation. In a very real sense the ELA calculations magnifies the differences between reference equations. Given the breadth of the normal range this means that even when using the most appropriate reference equations many normal individuals will have an ELA that is elevated relative to their CLA and many individuals with airway obstruction will have a ELA less than their CLA.

Note: One of the most interesting aspects about ELA calculations is how they increase the apparent differences between spirometry reference equations. I’ve discussed the broad range of normal mean values in the available FEV1 and FEV1/FVC ratio reference equations previously but ELA calculations make this much more obvious. Developing and selecting reference equations is a chronic problem without any easily evident solution and ELA calculations makes this even more obvious.

In addition, FEV1 can be reduced in non-smokers due to causes as diverse as asthma, obesity, pulmonary fibrosis and neuromuscular diseases. Are these patients going to be told what their lung age is? And if not, how do you know what proportion of a smoker’s lung age is due to causes other than smoking? For that matter, given the normal scatter in FEV1 the likelihood that any individual’s ELA is less than their CLA (and vice versa) before they even start smoking is 50% so without having a baseline FEV1 on hand, ELA is always going to be speculative.

ELA is an interesting concept but for all these reasons I believe that far too often it will be misleading and should not be used. I particularly disagree with the fact that the Morris and Temple ELA equation (without any correction for ethnicity!) is built into a number of spirometry systems.

So without ELA what role should pulmonary function labs play in getting smokers to quit?

Smoking is an addiction and no matter what technique has been used the number of successful quitters is small, usually on the order of 10%. Quitting smoking requires significant self-motivation and being confrontational is unlikely to improve an individual’s chances of succeeding. I’ve read that some pulmonologists will refuse to treat smokers with COPD who do not quit and although I understand some of the reasoning behind this I think it is more likely to make the individual in question more hopeless, not more motivated. Being judgmental is not the role that anybody in a PFT lab should take (no matter what the medical disorder is and regardless of how self-inflicted it may or may not be). We have to be informational instead and that means that testing should be as accurate as we can make it and that test results should be discussed neutrally and not used as a scare tactic. As a reminder less than 20% of smokers will actually develop COPD and this is something we need to be honest about when discussing smoking with patients.

Given human nature, the possibility of future (and even current) health risks are probably not as much a motivation as the impact smoking has on an individual’s finances. Smoking is expensive and there are a large number of on-line calculators that show this cost in a variety of different ways (Google “cost of smoking calculator” to see). Presently, in the US the average cost of a pack of cigarettes is over $6, which means that for a 1 PPD smoker, the weekly cost of their habit is over $40 and annual cost is over $2200. If that isn’t a reason to quit, I’m not sure what is.

ELA Reference Equations:

Male:
Reference:	Equation:
[A]	ELA = %FVC + 50.7 – (33.3 × FEV1)
[B]	ELA = ((2.87 x height x 0.394) – (31.25 x FEV1) – 39.375
[C]	ELA = (1.56 x height) – (33.69 x FEV1) – 85.62
[D1]	ELA = (1.483 x height) – (34.483 x FEV1) – 85.8621
[D2]	ELA = (0.01303 – SQRT(0.0001697 + 0.000688 x (0.00014098 x height2 – FEV1 + 0.5536))) / -0.000344
[D3]	ELA = (2.081 + 0.5846 x height3 – FEV1) / 0.01599 x height
[D4]	ELA = (0.00183 + SQRT((-0.001832) – 4 x 0.00011 x (9.37674 – (2.10839 x Ln(height)) + Ln(FEV1)))) / (2 x 0.00011)
[E]	ELA = ((0.036 x height) – 1.178 – FEV1) / 0.028
[F]	ELA = 209.195 – 0.455 x Height – 11.521 x Observed FEV1 (L) – 0.602 x Observed FEV1/FVC (%) + 1.956 x Observed FEF50 (L/s)

Female:
Reference:	Equation:
[A]	ELA = (0.84 × %FVC)+ 50.2 – (40 × FEV1)
[B]	ELA = ((3.56 x height x 0.394) – (40 x FEV1) – 77.28
[C]	ELA = (1.33 x height) – (31.98 x FEV1) – 74.65
[D1]	ELA = (1.58 x height) – (40 x FEV1) – 104
[D2]	ELA = (0.00361 – SQRT(0.000013 + 0.000776*(0.00011496 x height2 – FEV1 + 0.4333)))/-0.000388
[D3]	ELA = (1.597 + 0.5552 x height3 – FEV1) / 0.01574 x height
[D4]	ELA = (0.00422 + SQRT((-0.004222) – (4 x 0.00015 x (Ln(FEV1) + 8.49717 – 1.90019*Ln(height))))) / (2 x 0.00015)
[E]	ELA = ((0.022 x height) – 0.005 – FEV1) / 0.022
[F]	ELA = 234.441 – 0.792 x Height – 7.295 x Observed FEV1 (L) – 0.610 x· Observed FEV1/FVC (%) + 0.301 x Observed PEF (L/s) + 2.647 x Observed FEF50 (L/s)

Note: Height is in cm.

References:

Ben Saad H, Elhraiech A, Mabrouk KH, Mdalla SB, Essghaier M, Maatoug C, Abdelghami A, Bouslah H, Charrada A, Rouatbi S. Estimated lung age in healthy North African adults cannot be predicted using reference equations derived from other populations. Egyptian J Chest Dis Tuberculosis 2013; 62: 789-804.

Hansen JE, Sun X-G, Wasserman K. Meeting Abstract. Use of %FEV1/FEV6 and increased lung age to persuade smokers to quit. Chest 2009; 136(4): 56S

Hansen JE, Sun X-G, Wasserman K. Calculating gambling odds and lung ages for smokers. Eur Respir J 2010; 35: 776-780.

Hansen JE. Letter to the Editor: Measuring the lung age of smokers. Primary Care Respir J 2010; 19(3): 286-287.

Hansen JE. Letter to the Editor: Lung age is a useful concept and calculation. Primary Care Respir J 2010; 19(4): 400-401.

[A] Ishida Y, Ichikawa YE, Fukakusa M, Kawatsu A, Masuda K. Novel equations better predict lung age: a retrospective analysis using two cohorts of participants with medical check-up examinations in Japan. Primary Care Respir J 2015; 25: 15011.

The ELA reference equations in [A] were derived from:

The Report of the Special Committee of Pulmonary Physiology of the Japanese Respiratory Society (JRS). Reference values for spirogram and blood gas analysis in non-smoking healthy adults in Japan. J Japan Respir Soc 2001; 39:1–17

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

[B] Morris JF, Temple W. Spirometric “lung age” estimation for motivating smoking cessation. Prev Med 1985; 14: 655-662.

[C] Newbury W, Newbury J, Briggs, Crockett A. Exploring the need to update lung age equations. Primary Care Respir J 2010; 19(3): 242-247.

[D] Newbury W, Lorimer M, Crockett A. Newer equations better predict lung age in smokers: a retrospective analysis using a cohort of randomly selected participants. Primary Care Respir J 2012; 21(2): 78-84.

The authors of [D] derived a series of lung age equations from:

[D1] Quanjer P, Tammeling G, Cotes J, Pedersen O, Peslin R, Yernault J-C. Lung volumes and forced ventilatory flows. Report Working Party Standardization of Lung Function Tests, European Community for Steel and Coal. Official Statement of the European Respiratory Society. Eur Respir J 1993; 6(Suppl 16): 5-40.

[D2] Hankinson J, Odencrantz J, Fedan K. Spirometric reference values from a sample of the general U.S. population. Am J Respir Crit Care Med 1999; 159: 179-87.

[D3] Gore C, Crockett A, Pederson D, Booth M, Bauman A, Owen N. Spirometric standards for healthy adult lifetime nonsmokers in Australia. Eur Respir J 1995; 8: 773-782.

[D4] Falaschetti E, Laiho J, Primatesta P, Purdon S. Prediction equations for normal and low lung function from the Health Survey for England. Eur Respir J 2004; 23: 456-463.

Parkes G, Greenhalgh T, Griffin M, Dent R. Effect on smoking quit rate of telling patients their lung age: the Step2Quit randomised controlled trial. Brit Med J 2008; 336(7644): 598-604.

Quanjer PH, Enright PL. Editorial: Should we use lung age? Primary Care Respir J 2010; 19(3): 197-199.

[E] Toda R et al. Validation of “lung age” measured by spirometry and handy electronic FEV1/FEV6 meter in pulmonary diseases. Inter Med 2009; 48: 513-521.

[F] Yamaguchi K, Omori H, Onoue A, Katoh T, Ogata Y, Kawashima H, Onizawa S, Tsuji T, Aoshiba K, Nagai A. Novel regression equations predicting lung age from varied spirometric parameters. Respir Physiol Neurobiol 2012; 183: 108–114.

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

Recently I’ve been trying to help somebody whose spirometry results changed drastically depending on where their tests were performed. When their spirometry was performed on an office spirometer their FVC was less than 60% of predicted and when they were performed in a PFT lab on a multi-purpose test system their FVC was closer to 90% of predicted. Part of the reason for this was that different predicted equations are being used in each location but even so there was about a 1.5 liter difference in FVC.

One important clue is that the reports from the office spirometer showed an expiratory time of around 2 to 2-1/2 seconds while the reports from the PFT lab showed expiratory times from 9 to 12 seconds. The reports from both locations however, only had flow-volume loops and reported expiratory time numerically. There were no volume-time curves so it isn’t possible to verify that the spirometry being performed at either location was measuring time correctly or to say much about test quality.

The shape of a flow-volume loop is often quite diagnostic and many lung disorders are associated with very distinct and specific contours. Volume-time curves, on the other hand, are very old-school and are the original way that spirometry was recorded. The contours of volume-time curves are not terribly diagnostic or distinctive and I suspect they are often included as a report option more because of tradition than any thing else. But volume-time curves are actually a critically important tool for assessing the quality of spirometry and one of the most important reasons for this is because there is no time in a flow-volume loop.

With this in mind, the following flow-volume loop came across my desk yesterday. The FVC, FEV1 and FEV1/FVC ratio were all normal and it was the best of the patient’s efforts.

The contour of this flow-volume loop is actually reasonably normal, except possibly for the little blip at the end.

That “little blip” however, was actually two expiratory pauses, one about a second long and one about 4 seconds long. Although the fact that expiratory flow was zero during these pauses does show up on the flow-volume loop, there is absolutely nothing in the flow-volume loop that indicates how long they occurred.

When the pauses are subtracted the total expiratory time in this spirometry effort was only about 2-1/2 seconds and it was performed by an individual that was about 60 years old. When somebody is in the 20’s and I see a short expiratory time I’m usually not terribly concerned that the FVC is being underestimated (unless of course the FVC is below normal and the expiratory time is really, really short) and that is because it is fairly normal for somebody in that age range to be able to completely exhale their FVC in a short time. Somebody in their 60’s? Not so much. So even though the reported expiratory time was about 7-1/2 seconds there’s a good chance that the FVC is actually underestimated but you wouldn’t know it if all you had was the flow-volume loop.

Volume-time curves have have not changed significantly since they were first introduced about 65 years ago but there’s hardly anybody left that even knows how to get spirometry results off of a volume-time curve. Keeping a volume-time curve in a report just for backwards compatibility doesn’t seem to make a lot of sense but if you view it as an aid to assessing test quality it actually makes very good sense. If we’re going to embrace volume-time curves for this purpose then it’s also probably time to update them as well.

In the first place I think that all of the test data, from the very beginning of the test to the very end of the test, should be shown.

But I also think that showing flow as well as volume may turn out to be useful (although I’ll be honest and say that’s not as clear as I’d like it to be). Flow-time curves were seriously considered at one time, but like volume-time curves their contour is not particularly diagnostic. When used to assess test quality however, it’s possible they may be able to add something. A Volume-Flow-Time (VFT) curve would look like this:

When all of the test information is displayed this way it’s notable that the tidal breath baseline at the beginning of the VT curve appears to be drifting and this is an indication that the patient or the test system was leaking air. The prolonged pauses during exhalation may therefore be at least partly due to a leak and for this reason the FVC is quite likely underestimated. And if the FVC is underestimated then the FEV1/FVC ratio is also probably overestimated and maybe this spirometry effort isn’t as normal as it appears to be.

It wasn’t possible to see this happening in the original volume-time curve however because our test system’s software always truncates everything up until 1 second before the beginning of the FVC exhalation (and some systems truncate everything up until the start of exhalation). This is unfortunately true both when reviewing a spirometry effort and when it is reported (all of the volume-time data is on the computer display during the test but as soon as the test ends the display goes into review mode and all of the extra data disappears). If you go back to the original flow-volume loop the tidal flow-volume loops appear to be drifting, but this could be from other causes and isn’t as clear as what the full VT curve shows.

Note: BTW, none of the flow-volume loops from the person I’ve been trying to help from either the office spirometry system or PFT lab system showed tidal flow-volume loops. Without tidal loops it isn’t possible for a flow-volume loop to show any drift (nor is it possible to show negative effort dependence or to give any idea what the patient’s IC and ERV were).

When I started doing pulmonary function testing in the early 1970’s the only way to record spirometry was with a volume-time curve of some kind (kymograph paper and a pen of one kind or another usually). At that time it was also the only way to measure FVC and FEV1 (manually with a ruler and a calculator). But keeping volume-time curves on a report just so that in a pinch we could still make measurements from them doesn’t make any sense. The contour of a volume-time curve is also not particularly diagnostic in any way so if these were the only reasons that a volume-time curve needed to be on a report I would agree that the space it’s taking up could be better used by something else. But a volume-time curve actually contains a wealth of information about test performance that is not present in a flow-volume loop or in the numerical results. Any spirometry report that does not include a volume-time curve is therefore missing critical information about test quality.

Since volume-time curves are no longer needed for their original purpose that also means the should be optimized for quality assessment. For this reason I’d like to see the next ATS/ERS spirometry standards make it a requirement for complete volume-time (or volume-flow-time?) curves to be included on spirometry reports.

As a final note, when I questioned the person I’ve been trying to help about the short expiratory times that always showed up when their spirometry was performed on an office spirometer I was told that their exhalation was always stopped early by the staff member performing the test. The person said that they told the staff member that they were still exhaling but were always told in return that the spirometer said that no air was coming out, so the exhalation didn’t need to continue. This says to me there is either a problem with the spirometer or with the training of the staff member performing the test and that this is most probably the reason for the different in FVC volumes. What was also interesting about this is that even though the expiratory time was reported, and was always between 2 and 2.5 seconds, the physician interpreting the test always wrote “moderate restriction” (from a spirometry result?) and never once commented on the short expiratory time. So it’s not only the staff member that probably needs better training, it’s the physician (a pulmonologist!) who needs it too.

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