Category: pftblog

I have been searching through Pulmonary Function videos on YouTube in order to find ones I thought would be useful for technician education. So far what I’ve found have been intended either for medical students or for patients and not, in my opinion, particularly suitable for training technicians. Lately I’ve been looking at videos about lung volumes and have seen a half dozen presenters describe lung volume subdivisions using the same graph we’ve come to know and love with varying degrees of effectiveness and obfuscation.

In a discussion of helium dilution lung volume measurements one of the presenters made an interesting statement and that was that “helium does not pass the alveolar-capillary barrier which means it stays inside the lungs during the test”. This is wrong on multiple levels. First, the alveolar-capillary membrane evolved for gas exchange and does not discriminate against individual gases so there is no barrier. Second, the reason that gases can be used as tracer gases or as probes of pulmonary circulation has entirely to do with gas solubility. Third, since it was a university-sponsored video with other egregious errors (for example did you know that lung volumes are measured in ml/kg?) what the heck are they teaching their medical students?

Gases can and will be absorbed by blood and tissue. The quantity of gas that can be absorbed is determined by the gas’s solubility and the Bunsen solubility coefficient is a measure of how much gas is absorbed (usually in milliliters of gas per milliliter of liquid) when the gas is at 1 atmosphere of pressure. When there is a multi-gas mixture, the quantity of gas absorbed for individual gas is calculated by:

The Bunsen Solubility of the common respiratory gases are as follows:

Gas:	Solubility in Blood:
Acetylene (C2H2)	0.739
Carbon Dioxide	0.515
Carbon Monoxide	0.0189
Dimethylether	9.0
Freon-22	0.673
Helium	0.0094
Methane	0.0468
Nitrogen	0.012
Nitrous Oxide (N2O)	0.412

The reason that helium (and to some extent methane) are useful as tracer gases is because of their low solubility. During a helium dilution FRC test, the helium concentration in the testing circuit usually starts around 7% plus or minus a bit. Since the normal human blood volume is around 5 liters, that means that the amount of helium absorbed into a subject’s blood during the test is going to be no more than:

 or 3.29 ml.

Some helium will also be absorbed by the lung itself but that will be an even smaller amount, so at a rough estimate, approximately 5 ml of helium will be absorbed during the test. That’s not zero, but it’s also less than 1 percent of the total amount of helium in the test gas circuit. It’s not that helium doesn’t pass the alveolar-capillary “barrier” as the presenter stated in the video but because it is so insoluble only a miniscule amount is absorbed. A proper FRC calculation will take this into account but even if it is ignored the amount of error will be negligible and probably less than the error bars for the helium analyzer and spirometer volume.

Methane has replaced helium for most single-breath DLCO tests. It’s more soluble than helium, but not by that much. Calculating the absorption of methane during a DLCO test is more complicated because it occurs over a shorter time period but since a normal resting cardiac output is roughly 5 liters/min and the breath-holding time for a DLCO test is nominally 10 seconds, that means that the amount of blood exposed to DLCO gas mixture is approximately 833 ml. The amount of methane absorbed is therefore:

or 0.116 ml, which is very approximately 0.7% of the total amount of methane inhaled. Again not zero, and again it should be accounted for, but again also negligible and likely less than the error bar of the gas analyzer.

Nitrogen is also a relatively insoluble gas (although that doesn’t mean that its solubility isn’t a consideration for divers and hyperbaric chambers). During a nitrogen washout lung volume test, a subject replaces the nitrogen in their lung with oxygen. The total volume of nitrogen in the blood is approximately:

or about 47 ml, which is about 1.2% of the total volume of nitrogen in the lung and is about the same level of error as for helium and methane measurements. Admittedly this does not account for the nitrogen in the muscles and tissue of the body, but these stores are only slowly depleted and for the short time interval involved in a nitrogen washout test they don’t make a particularly great contribution to exhaled nitrogen.

Gases with high solubilities on the other hand, have been used to measure cardiac output. Acetylene, Dimethylether (DME) and Freon-22 have been used for this purpose. The calculations are a bit more involved but basically since the amount of soluble gas in an inhaled gas mixture is known, its solubility and the rate at which it disappears over time can be used to measure pulmonary blood flow. Specifically in a single-breath maneuver:

Where:

Qc = pulmonary capillary blood flow rate

Sol_b = solubility coefficient of gas in blood

Sol_t = solubility coefficient of gas in lung tissue

Vt = volume of lung tissue

Fa = fractional concentration of soluble gas in alveolar air

t1, t2 = starting and ending time of breath hold

Finally, the solubility of oxygen in blood plasma is why hemoglobin is necessary. Oxygen is actually poorly soluble. The oxygen content of blood is calculated from:

For a PaO2 of 100, without hemoglobin the amount of oxygen in a decaliter of blood would only be about 0.31 ml. With hemoglobin it is about 20 ml and that difference is what makes it possible for us to exist (or at least able to walk and talk, since without hemoglobin we wouldn’t have the energy to be much more than lumps of protoplasm that were unable to move or think more than slightly).

The differences in the solubility of gases allows us to make a number of interesting physiological measurements. Gas solubility may be a slightly esoteric aspect of physics, chemistry and pulmonary function testing and it is true that calculations with a low degree of error can be made without accounting for its effects, but that doesn’t mean it doesn’t matter and that it shouldn’t be taught correctly even if only to medical students.

References:

Brusasco V, Crapo R, Viegi G et al. ATS/ERS Task Force: Standardisation of lung function testing. Standardisation of the measurements of lung volumes. Eur Respir J 2005; 26: 511-522.

Cander L. Solubility of inert gases in human lung tissue. J Applied Physiol 1959; 14(4): 538-540.

Ramage JE, Coleman RE, MacIntyre NR. Rest and exercise cardiac output and diffusing capacity assessed by a single slow exhalation of methane, acetylene and carbon monoxide. Chest 1987; 92: 44-50.

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

 In a recent post on the AARC Diagnostics forum a PFT Lab manager asked how long they need to keep database records. The ostensible reason for this was that they had too many years of records and had been having database problems.

The poster wasn’t specific about what kinds of problems they were having. Database problems can be hard to diagnose particularly when a database is networked but with a modern SQL database the number of records shouldn’t be an issue. SQL databases containing millions of records are routinely used in demanding multi-user applications. If this was thirty years ago when computers first started to be commonplace in the PFT Lab I could understand since PC-based databases were still in their infancy then. It was at least partly for this reason that a number of PFT equipment manufacturers developed their own proprietary databases. This is no longer the case and I have difficulty believing that there are any manufacturers at this time that don’t use a commercial SQL database of one kind or another.

I am not suggesting the poster wasn’t having problems. Even though SQL databases tend to be very robust that doesn’t mean that incorrect settings or bugs in the software accessing the database can’t cause problems. Equipment manufacturers and hospital IT departments may not have the expertise or the patience (or even the desire) to diagnose and fix these kinds of problems either. What I found curious however, was that almost everybody responding to the original post seemed to be eager to get rid of their “old” patient data as soon as they possibly could.

I don’t understand this at all. My lab’s database goes back to 1990 and we’ve worked hard to maintain its integrity throughout this time. Since 1990 my lab has gone through at least six major software and database revisions and has migrated the database from its original home in a IBM PC AT, to a lab-only local area network and then to a shared SQL server managed by the hospital’s IT department. When my hospital merged with another in the late 1990’s we also merged our database with the other hospital’s PFT lab. Our database currently contains (among other things) 667,000 spirometry results from 159,000 patient visits. It’s hard to be absolutely sure of course, but as far as I can tell we haven’t lost any information along the way.

So why go to all this trouble? Legally, as long as our paper PFT reports are in Medical Records (yes {sigh}, we’re still required to generate paper reports although with electronic report signing on our horizon that requirement will go away soon) we’re not required to keep our electronic database records for any particular time period at all (I will mention in passing that our state’s requirements for regular Medical Records is that they need to be kept for 40 years). We’ve also had an interface with the hospital’s computer system for almost 20 years (which itself has gone through at least four major revisions) and all of the patient reports we’ve uploaded are still in the hospital’s information system.

The reason we go to all this trouble is very simple: neither Medical Records nor the hospital’s information system can generate a trend report.

I think that trends are a critical but often overlooked part of PFT testing. Certainly there are many patients who are only seen once in the PFT Lab and never seen again (or at least not in the same lab and that is an important issue unto itself). Many patients are seen more than once however, and how normal or abnormal their test results are is often less important than the changes in their test results. We regularly get at a number of patients every week who have PFT records dating from 10, 15 or even over 20 years ago. When test results are reviewed their trends often have a significant influence on the test interpretation (and the inability to assess trends is one reason that computerized interpretations have been a consistent failure for decades).

Keeping patient records, most particularly in a useable form, is a critical part of patient service, and this is why I don’t understand the apparent desire of some labs to get rid of their data as quickly as they can. Even if a lab regularly uploads patient test results to their hospital’s information system, does that system store the graphical results? Does it store all trials for a single test? Does it store the raw test data and not just a few of the results? And most importantly of all, can it generate a trend report? If the answer is yes to all these then I would agree that the lab itself does not need to retain test data any longer than the bare minimum that is necessary. Otherwise, I think a lab has a responsibility to try to retain patient test results indefinitely.

[Full disclosure: I am forced to admit that I have a reputation as a data pack rat, and with some justification. I’ve had a PC of one kind or another since the 1970’s (anybody remember the TRS-80 Model III?) and I have some personal files on my computer that are over 30 years old, so you can see that I have trouble understanding why you wouldn’t want to keep patient data for as long as possible.]

There are a number of factors however, that are driving dramatic improvement in data interchange between hospital information systems, clinics, physicians and patients. Patient information has been stored as paper records in Medical Records for a very long time and more recently and more conveniently in Hospital Information Systems, but both are a bit like a black hole: information goes in but it takes an awful lot of hard work to get it back out. The need to interchange data is forcing fundamental changes in the way information is stored and retrieved. This process is still ongoing, but it is already allowing extremely large on-line datasets to be easily created and maintained. These in turn can be searched quickly for trends and correlations, and although this is certainly changing the nature of research, it is also changing the nature of patient care.

At some point, data interchange will reach a point where it won’t matter when or where a patient had their PFT tests performed since it will all be on tap, ready to be reviewed and trended no matter where the patient is or who they are seeing. We’re not there yet however, and at a guess the era of universal and transparent data interchange is still at least a decade away, so retaining data still matters.

When we have the opportunity to acquire new test systems for our labs, we usually focus on what tests the equipment performs and how well we think it will perform them. As importantly, we also need to think about how the test data is stored, retrieved and shared. There should be no technical reasons a lab can’t keep all of its test data for as long as it wants or needs, even if that is for multiple decades. In general, SQL databases are a mature and reliable technology. Retrieval speed is not greatly affected by how many records are stored and disk space is cheap. All of the major SQL databases have a variety of tools for maintaining database health. Database problems are unacceptable and if your lab is having them it is unlikely that having “too many” records is necessarily going to be the reason. Instead, those responsible, the equipment vendor and hospital IT department, need to be taken to task until they are fixed.

 

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

When it comes to spirometry, it’s really all about FEV1. FVC and the FEV1/FVC ratio are also important of course, but because FVC is more likely to be underestimated than FEV1 they are less reliable.

Changes in FEV1 are critical in monitoring airway disease. The recent ATS guidelines on Occupational Spirometry indicate that a 15% decrease (adjusted for changes in age) is significant and cause for concern. For diagnosing airways disease however, it is important to know what a normal FEV1 is.

I have been able to find twenty-four different reference equations for FEV1. That’s good in one sense but that quantity also makes it that much more difficult to determine which reference equations should be used. When I graph results it often becomes more apparent what the equations are trying to tell us but in this case I came away a bit more confused instead.

After gender, height and age, ethnicity is considered to be a critical factor in determining normal values. For this reason, I re-graphed the FEV1 results and (somewhat arbitrarily) clustered the different ethnicities based (mostly) on their geographic location.

What I saw was a great deal of overlap between ethnicities and a great deal of variance within ethnicities.

Ethnicity may be important but the more closely you look at ethnicity the less apparent it becomes as to what it actually means. The primary problem with ethnicity and reference equations revolves around the use of standing height as a metric for lung volume.

Ideally, we would like to know what an individual’s lung function “should” be if they were in perfect health. An individual’s “ideal” FEV1 will depend on lung volume and airway caliber, neither of which can be determined with any precision from simple external measurements. There are a number of proportionalities however, between different parts of the human anatomy that are fairly constant across a broad range of human heights and the volume of the thorax is one of these. This relationship was first noted by John Hutchinson over 150 years ago and has been used ever since. The proportionality is not exact, of course, since there is approximately a 30% range in FEV1 across all ethnicities (at least based on these reference equations there is).

Given the way humans have settled over the earth throughout history, it is not surprising that there would be clustering in genes, diet and environment that would cause local populations to have similar relationships between height and FEV1 (and the other lung function values). Historically this has been taken by researchers as a genetic issue, most particularly the distinction between whites and blacks. I (and many others) strongly suspect that diet and environment have as much, if not much greater, effect. Since not only our genes but both diet and environment play a large role in the development and maturity of the human body as well I guess we should be amazed that the range is only 30%.

But 30% is a pretty broad range and can make the difference between calling an FEV1 either normal or abnormal for a very large number of people. Although we categorize these differences under the heading of “ethnicity” what this really means is that there are factors other than height that predict lung volume and airway caliber and we don’t know what they are.

Every lab should choose reference equations that are appropriate to the population they serve but there are no real guidelines on determining this. Probably all too often labs leave their test equipment software set to the manufacturer’s default settings, partly, perhaps in the belief that the equipment manufacturer knows better than they do what reference equations should be used.

There are several factors that I think would help a lab and interpreting physician select reference equations. Although ethnicity should be a consideration it is a slippery concept and frequently lab populations don’t fit neatly into any specific group. A far more important factor should be, I think, the size of the study group. Larger is better and this is because small groups are more prone to selection effects. Next would be good representation of all age groups, particularly the young and the elderly.

The last factor is good statistics. This is not an area that I am particularly qualified to judge, but I’ve seen that the studies with the largest populations and most sophisticated statistical analysis (ie., NHANESIII) show that the decline in FEV1 (and other lung function values) is not linear but accelerates with age. Given the aging of the populations we serve I think this is a critical factor and that reference equations that don’t show this may be causing a mis-interpretation of test results in the elderly.

The apparent rates of decline in FEV1 should be taken with a grain of salt. These are from static population studies and not longitudinal studies. Having said that the ATS Statement on Occupational Spirometry indicates that a normal decline for non-smoking adults is around 29 ml/year and although that value is closely approximated by most of these reference equations, I don’t think that this should be a primary factor in selecting an FEV1 reference equation.

A final thought is that many of the older studies were performed using equipment that may be significantly different from that in use today. Testing standards have also been refined as well and these two factors may account for some of the differences from more recent studies.

The simple answer to the question I posed at the beginning of this blog is that ethnicity does matters, and it matters a lot, but the real and more complex answer is that it is not at all clear what ethnicity is even when we think we know what it is.  The Global Lung Initiative released their preliminary spirometry reference equations based on results from PFT Labs around the world a year or so ago but has indicated they await further data in order to continue to refine them. Despite the fact their reference equations come from an exceptionally large and diverse population it is interesting to note that they have already been criticized for not meeting the needs of a local population.

I think that continuing to focus on ethnicity is not giving us the right answers. We need to start looking for metrics that can be used in place of, or along with, height that don’t depend on ethnicity. I will admit that I don’t have any clear notion what we should be looking for. Sitting height has been used several times but has not been shown to be a significant improvement over standing height. Attempting to measure chest breadth and depth is frustrated by the tissue (muscle and fat) that overlays the ribcage and also doesn’t say anything about the anatomical position of the diaphragm. Perhaps some combination of standing height, sitting height, chest measurements and BMI would be better than standing height alone. This would place a greater burden on PFT labs to make these measurements, but I think the improvement in precision would be worth it.

FEV1 Study Populations:

Reference	Ethnicity:	#Female:	Female Ages:	#Male:	Male Ages:
[A]	White	927	21-80	476	21-80
	Black	772	21-80	422	21-80
	Hispanic	872	21-80	506	21-80
[B]	White	327	20-79	300	20-79
[C]	White	471	20-84	517	20-84
[D]	White	97	Not stated	102	Not stated
[E]	White	176	20-69	86	25-70
[F]	White	1129	27-82	1106	27-82
[G]	Japanese-American	0		6349	45-68
[H]	American Indian	253	45-74	190	45-74
[I]	Asian Indian	137	20-80	226	16-80
[J]	Chinese	595	18-80	494	18-80
[K]	Malaysian	614	20-69	1385	20-69
[L]	White	102	18-70	110	18-70
[M]	Black	205	18-90	206	18-85
[N]	Jewish-Ashkenazi	663	20-74	1154	21-79
	Jewish-Sephardic	547	20-69	786	21-84
[O]	Black	117	18-47	143	18-47
[P]	White	96	18 to >70	83	18 to >70
[Q]	Chinese	0		440	18-80
[R]	White	270	25 to >75	373	20 to >75
[S]	Iranian	255	17-82	295	17-82
[T]	Saudi	292	18-65	175	18-65
[U]	Filipino	153	16-68	130	17-78
[V]	Korean	694	20+	926	20+
[W]	White	7009	18-80	4565	18-80
[X]	Iranian	1110	21-80	1302	21-80

Female FEV1 Reference Equations:

[A] White	0.4333-(0.00361*age)-(0.000194*age^2)+(0.00010846*ht^2)
[B] White	-1.901+(0.037*ht)-(0.025*age)
[C] White	(0.089*(ht/2.54)-(0.025*Age)-1.932)
[D] White	(0.085*(ht/2.54))-(0.025*age)-1.692
[E] White	-1.405+(0.0309*ht)-(0.0201*age)
[F] White	-1.747-(0.0263*age)+(3.619*(ht/100))
[L] White	-2.73-(0.031*age)+(4.47*(ht/100))
[P] White	(3.321*(ht/100))-(0.025*age)-1.394
[R] White	(0.0314*ht)-(0.0203*age)-1.353
[W] White	EXP(-8.397+(1.865*LN(ht))+(0.0057*age)-(0.00015*age^2))
[A] Hispanic	0.4529-(0.01178*age)-(0.000113*age^2)+(0.00012154*ht^2)
[H] American Indian	(0.0358*ht)-(0.0262*age)-1.774
[N] Jewish-A	-1.574-(0.021*age)+(3.247*(ht/100))
[N] Jewish-S	-1.636-(0.021*age)+(3.247*(ht/100))
[O] Black	-1.6158-(0.0178*age)+(0.0298*ht)
[S] Iranian	(0.039489*ht)-(0.023593*age)-2.498
[T] Saudi	(0.036*ht)-(0.018*age)-2.482
[X] Iranian	(0.03715*ht)-(0.0238*age)-2.072
[M] Black	-1.398-(0.023*age)+(2.848*(ht/100))
[A] black	0.3433-(0.01283*age)+(0.00010846*ht^2)
[I] Asian Indian	0.401+(0.021*ht)-(0.021*age)
[J] Chinese	-1.272-(0.0199*age)+(0.02825*ht)
[K] Malaysian	(0.0294*ht)-(0.0238*age)-1.609
[U] Filipino	-1.0375+(0.0256*ht)-(0.0187*age)
[V] Korean	(0.03558*ht)-(0.000192*age^2)-2.4114

Male FEV1 Reference Equations:

[A] White	0.5536-(0.01303*age)-(0.000172*age^2)+(0.00014098*ht^2)
[B] White	-2.832+(0.047*ht)-(0.03*age)
[C] White	(0.092*(ht/2.54))-(0.032*age)-1.26
[D] White	(0.093*(ht/2.54))-(0.032*age)-1.343
[E] White	-6.5147+(0.0665*ht)-(0.0292*age)
[F] White	-4.261-(0.0296*age)+(5.465*(ht/100))
[L] White	-2.16-(0.031*age)+(4.47*(ht/100))
[P] White	(3.961*(ht/100))-(0.033*age)-1.558
[R] White	(0.0338*ht)-(0.0252*age)-0.789
[W] White	EXP(-8.957+2.014*LN(ht)+(0.00281*age)-(0.000105*age^2))
[A] Hispanic	0.6306-(0.02928*age)+(0.00015104*ht^2)
[G] Japanese-American	-1.845-(0.018*age)+(0.035*ht)
[H] American Indian	(0.0599*ht)-(0.024*age)-5.65
[S] Iranian	(0.043822*ht)-(0.028801*age)-2.425
[T] Saudi	(0.036*ht)-(0.019*age)-1.886
[N] Jewish-A	-3.302-(0.026*age)+(4.686*(ht/100))
[N] Jewish-S	-3.302-(0.026*age)+(4.686*(ht/100))
[X] Iranian	(0.045302*ht)-(0.02566*age)-2.78204
[A] Black	0.3411-(0.02309*age)+(0.00013194*ht^2)
[M] Black	-1.933-(0.027*age)+(3.609*(ht/100))
[O] Black	-3.6679-(0.0331*age)+(0.0501*ht)
[I] Asian Indian	-1.936+(0.035*ht)-(0.026*age)
[J] Chinese	-2.404-(0.0254*age)+(0.03978*ht)
[K] Malaysian	(0.0353*ht)-(0.0315*age)-1.78
[U] Filipino	-3.2068+(0.0436*ht)-(0.0205*age)
[V] Korean	(0.04578*ht)-(0.0002484*age^2)-3.4132
[Q] Chinese	-1.86083-(0.02755*age)+(0.03733*ht)

References:

[A]	Hankinson JL, Odencrantz JR, Fedan, KB. Spirometric reference values from a sample of the general U.S. Population. Amer J Resp Crit Care 1999; 159: 179-187
[B]	Gutierrez C, et al. Reference values of pulmonary function tests for Canadian caucasians. Can Respir J 2004; 6: 414-424.
[C]	Morris JF, Koski A, Johnson LC. Spirometric standards for healthy nonsmoking adults. Am Rev Resp Dis 1971; 103: 57-67.
[D]	Morris JF, Koski A, Temple WP, Claremont A, Thomas DR. Fifteen-year interval spirometric evaluation of the Oregon Predictive equations. Chest 1988; 93: 123-27
[E]	Knudson RJ, Lebowitz MD, Holberg CJ, Burrows B. Changes in the normal maximal expiratory flow volume curve with growth and aging. Am Rev Resp Dis 1983; 127: 725-734
[F]	Johannessen A, Lehmann S, Omenaas ER, Side GE, Bakke PS, Gulsvik A. Post-bronchodilator spirometry reference values in Adults and implications for disease mangement. Amer J Resp Crit Care Med 2006; 173(12): 1316-1325
[G]	Marcus EB, MacLean CJ, Curb JD, Johnson LR, Vollmer WM, Buist AS. Reference Values for FEV1 in Japanese-American Men from 45 to 68 years of age. Am Rev Respir Dis 1988; 138:1393-1397
[H]	Marion MS, Leonardson GR, Rhoades ER, Welty TK, Enright PL. Spirometry reference values for American Indian adults. Chest 2001; 120: 489-495
[I]	Fulambarker A, Copur AS, Javen A, Jere S, Cohen ME. Reference values for pulmonary function in Asian Indians living in the United States. Chest 2004; 126: 1225-1233
[J]	Ip MS, Ko FW, Lau AC, Yu W, Tang K, Choo K, MM Chan-Yeung. Updated spirometric reference values for Adult Chinese in Hong Kong and implications on clinical utilization. Chest 2006; 129: 384-392.
[K]	Singh R, Singh HJ, Sirisinghe RG. Spirometric studies in Malayasian between 13 and 69 years of age. Med J Malaysia 1993; 48: 175-184
[L]	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.
[M]	Perfura-Yone EW, Kanko-Nguekam NF, Kengne AP, Balkissou AD, Noseda A, Kuaban C. Spirometric Reference Equations for semi-urban and urban Bantu Cameroonians. Open J Resp Dis 2013; 3: 164-174.
[N]	Steinvil A, Fireman E, Wolach O, Rebhun U, Cohen M, Shapira I, Berliner S, Rogowski O. The effect of ethnic origin on pumonary prediction equations in a Jewish immigrant population. Respiratory Medicine 2008; 102: 919-926.
[O]	Mengesha YA, Mekonnen Y. Spirometric lung function tests in normal non-smoking Ethiopian men and women. Thorax 1985; 465-468.
[P]	Roberts CM, MacRae KD, Winning AJ, Adams L, Seed WA. Reference values and prediction equations for normal lung function in a non-smoking white urban population. Thorax 1991; 46: 643-650.
[Q]	Lam DCL, Fong DYT, Yu WC, Ko FWS, Lau ACW, Chan JWM, Choo KL, Mok TYW, Tam CY, Ip MSM, Chan-Yeung MMW. FEV3, FEV6 and their derivatives for detecting airflow obstruction in adult Chinese. Int J Tuberc Lung Dis 2012; 16(5): 681-686.
[R]	Pereira CADC, Sato T, Rodrigues SC. New Reference Values for forced spirometry in white adults in Brazil. J Bras Pneumol 2007; 33: 397-406.
[S]	Razi E, Moosavi GHA, Akbari H. Spirometric standards for healthy Iranians dwelling in the centre of Iran. Tanoffos 2005; 4(15): 19-26.
[T]	Al Ghobain MO, Ahamad EH, Alorainy HS, Hazmi MA, Al Moamary MS, Al-Hajjaj MS, Idress M, Al-Jahdali H, Zeitouni M. Spirometric reference standards for healthy nonsmoking Saudi adults. Clinical Respir J 2014; 8: 72-78.
[U]	Roa CC, Zaldivar CA, Salonga RC, Bobadilla J, Lansang MA, Reodica R, Balgos A, Blanco J, Tanchuco JQ. Normal standards for ventilatory function in adult Filipinos. Phillipine J Internal Med, 2013; 51(1): 1-6.
[V]	Oh YM, Hong SB, Shim TS, Lim CM, Koh Y, Kim WS, Kim DS, Kim WD, Kim YS, Lee SD. Effect of a new spirometric reference equation on the interpretation of spirometric patterns and disease severity. Tuber Respir Dis 2006; 60: 215-220.
[W]	Kuster SP, Kuster D, Schindler C, Rochat MK, Braun J, Held L, Brandli O. Reference equations for lung function screening of healthy never-smoking adults aged 18-80 years. Eur Respir J 2008; 31: 860-868.
[X]	Golshan M, Nematbakhsh M, Amra B, Crapo RO. Spirometric reference values for a large Middle Eastern population. Eur Respir J 2003; 22: 529-534.

Ben Saad H, El Attar MN, Hadj Mabrouk K, Ben Abdelaziz A, Abdelghani A, Bousarssar M, Limam K, Maatoug C, Bouslah H, Charrada A, Rouatbi S.The recent multi-ethnic global lung initiative 2012 (GLI2012) reference values don’t reflect contemporary adult’s North African spirometry. Respiratory Medicine 2013; 107: 2000-2008.

Redlich CA, Tarlo SM, Hankinson JL, Townsend MC, Eschenbacher WL, Von Essen SG, Sigsgaard T, Weissman DN. Official American Thoracic Society Technical Stanards: Spirometry in occupational setting. Amer J Respir Crit Care Med 2014; 189(8): 984-994.

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

Pulmonary patients have been using personal peak flow meters for several decades and I started to seeing patients that had their own oximeter over 10 years ago. Within the last couple of years a number of different spirometers intended for personal use have become available. These devices have significant limitations when compared to regular office or lab spirometers but because there are many individuals with asthma or COPD for whom FEV1, and possibly FVC, are significantly better indicators of lung health than Peak Flow (PEF) alone, I think they can serve a useful purpose.

There is no official definition of what constitutes a personal spirometer but I’m going to go with the ability to measure FEV1 as a minimum which means that there is a bit of crossover with some of the electronic peak flow meters. Because the majority of personal spirometers I have been able to find sell for less than $500 for the time being I’m going to keep the discussion to spirometers that I believe are under that price point.

There is, of course, a correlation with price and the number of features. Not surprisingly, the least expensive units measure the fewest values and have the least memory. More is not necessarily better, however, and I think that the first factor that should be considered when comparison shopping is what needs to be measured?

Company:	Product:	Measures:
Carefusion	Micro1	FEV1, FEV6, FEV1/FEV6, PEF, FEF25, FEF75, FEF25-75, Pre/Post-Bronchodilator, %predicteds
Carefusion	Precison Diary	FEV1, FEV6, PEF
Carefusion	PulmoLife	FEV1, FEV1% predicted, Lung age
Contec	SP10	FEV1, FVC, FVC, PEF, FEF25, FEF75, FEF25-75, %Predicted.
Ganseman	PC-Spiro	FEV1, FVC, PEF, FEV1/FVC ratio, %predicteds
MDSpiro	PulmoLife	FEV1, FEV1% predicted, Lung age
MDSpiro	SpiroCheck	FEV1, FEV1% predicted, Lung age
MDSpiro	SpiroCheck Home Monitor	FEV1, FEV6
Nspire	Piko-6	FEV1, FEV6, FEV1/FEV6

After FEV1, the FVC (or FEV6) and the FEV1/FVC (or FEV1/FEV6) ratio look to be most useful. My personal opinion is that FEF25, FEF75 and FEF25-75 are of little value largely because they are highly variable and usually provide much less information than FEV1 and the FEV1/FVC ratio. I’m also uncertain about the value of Lung Age calculations. It’s one way to assess results that may be easier for some individuals to understand but it also depends a lot on the accuracy of the reference equations and I think that just trending FEV1 is more useful in the long run. Pre/post-bronchodilator testing looks to be most useful for clinical trials but is probably a less important option for an individual.

The second most important factor is how do the results need to be managed?

Company:	Product:	Results:
Carefusion	Micro1	Uploads to PC via USB, includes PC software to manage results
Carefusion	Precision Diary	Uploads to PC via USB, includes PC software to manage results
Carefusion	PulmoLife	Self-contained, no internal memory
Contec	SP10	Uploads to PC via USB, Bluetooth optional, includes PC Software to manage results
Ganseman	PC-Spiro	Sensor attached to PC via USB, PC software performs tests, manages results
MDSpiro	SpiroCheck	Self-contained, no internal memory
MDSpiro	SpiroCheck Home Monitor	Self-contained, stores up to 200 results
MDSpiro	PulmoLife	Self-contained, no internal memory
Nspire	Piko-6	Optionally uploads results to PC via USB cradle with PC software to manage results

Being able to download results to a PC so that they can be stored, trended and printed certainly makes managing the information much easier and more convenient. Results can also be hand-written in a logbook or hand-entered into a spreadsheet however, which actually may be quicker and easier than going through the download process. Having said that, at least one personal spirometer comes with a bluetooth option that would seem to make the download process relatively painless.

Most of the spirometers come with a built-in LCD display that usually displays only numbers and very simple graphics. The PC software that comes with some of the spirometers can display volume-time and/or flow-volume curves once the test results have been uploaded. This is a critical function for lab or office spirometry but is not really necessary for a personal spirometer and may even be too much information for many users. This function would seem to be important only for sophisticated users and for clinical trials.

An important question, and one I cannot answer, is how accurate and reliable are these spirometers?

Making a flow or volume sensor that is accurate and reliable is difficult. This is why PFT Lab staff are accustomed to routinely calibrating and performing quality control on all of their spirometers. None of the personal spirometers, however, can be calibrated (and in some cases a 3-liter calibration syringe costs more than the spirometer!) and I do not expect that the average user could be expected to perform regular and accurate calibrations. This means that the manufacturers have had to make choices about their measurement technology that will allow the spirometers to be reasonably accurate over the lifetime of the device. The majority of personal spirometers use turbine sensors.

Company:	Product:	Sensor:
Carefusion	Micro1	Turbine
Carefusion	Precison Diary	Turbine
Carefusion	PulmoLife	Turbine
Contec	SP10	Turbine
Ganseman	PC-Spiro	Pneumotach
MDSpiro	SpiroCheck	Turbine
MDSpiro	SpiroCheck Home Monitor	Turbine
MDSpiro	PulmoLife	Turbine
Nspire	Piko-6	Vane

Turbine sensors have been around for decades and although they have been shown to have long-term reliability and accuracy I have some reservations about their use in personal spirometers (it’s not personal though since I have reservations about any sensor used in personal spirometers). There are two specific limitations of turbine sensors. The first is inertial lag. This occurs whenever flow rates are rapidly increasing or decreasing. Most turbine sensors have a fixed set of vanes (like fan blades) on either end of the sensor which causes the airflow through the sensor to swirl and move a flat vane. The rotation of the vane is detected by a light sensor.

Although the rotating vane has very little mass, there is still a delay from when a change in flow rate occurs and when the rotation speed of the vane matches the new flow rate. This is particularly true when flow changes direction.

The second limitation exists because airflow through the sensor must swirl for the internal vane to rotate. When flow rates are low, however, swirling may not occur or may not occur with enough force to rotate the vane. This means that turbine sensors require air flow to be above some minimum value before it can be measured.

Inertial lag is corrected in software by noting changes in rotation rate (either acceleration or deceleration) and then “predicting” what the flow rate “really” is by knowing the inertial characteristics of the sensor. The minimum airflow limitation cannot be corrected and may be the primary reason that some personal spirometers measure FEV6 rather than FVC.

A variety of manufacturers sell lab and office spirometers using turbine sensors that meet ATS/ERS standards and there is no reason to believe the turbines used in personal spirometers are any different. Lab and office spirometers are capable of being calibrated however, and don’t sit for periods of time at the bottom of pockets or purses before being used. Lab and office spirometers are also usually attached to relatively fast and powerful PC’s instead of a low-power (both in terms of power consumption and processing power) microprocessor.

I am not picking specifically on turbine sensors. Given the application they are probably one of the better choices. I am concerned however, that changes in FEV1 and FVC may be due to changes in sensor function and not the individual performing the test and that this may cause either unnecessary alarm or for decreases in lung function to go unnoticed. To my knowledge none of these personal spirometers have ever been studied for long term accuracy and reliability under “field” conditions and I will continue to have reservations until this has been done

Personal health monitoring has become an explosively expanding field and I think this is a good thing. I started in the medical field when it was still very paternalistic and I have watched it evolve into the more open and collaborative system it is today. I think that personal health monitors have the ability to engage participants in their own health care, improve quality of life, reduce hospitalizations and reduce costs. In our particular area of health care I think that FEV1 is superior to PEF when it comes to monitoring respiratory health. I think that FVC (or FEV6) can also be a useful measurement and it is for these reasons that I think that personal spirometers are superior to peak flow meters and should be more commonly used.

I am a bit dismayed at the cost of personal spirometers (particularly considering their simplicity) since at this time most insurers will not cover their cost and this limits who can afford them. I am also somewhat dismayed at the range in prices within the same families of spirometer since there is little physical difference between the least expensive and most expensive personal spirometers except for their software.

Results also need to be shared with an individual’s physician to be really useful and there continues to be significant limitations in this area. Usually the best that can be expected is to be able to print results and bring them along on an office visit. Very rarely results can be emailed to a physician or clinic, but as an example I personally receive my own health care at two very technologically advanced medical centers and I can’t do that other than by manually typing test results in an email within their patient care system. This area is improving rapidly, but mostly in the communications between hospitals, clinics and physician offices. Patient communications is coming in a distant last so I suspect it will still be quite a few years before routine communication between personal health monitors and health care providers occurs. Admittedly some of the personal spirometers are probably intended for clinical trials and can transmit results over the internet but this is primarily to proprietary systems and not to regular health care providers.

Finally I think that personal spirometers are a work in progress. The ultimate goal would be a flow sensor that is robust, accurate, reliable and inexpensive but I doubt all of these criteria can be met in a single device. There will always be trade-offs but better solutions than those in current use may come forward at some point. Additionally most of the personal health monitors shown at the recent consumer shows have bluetooth links to android or apple smartphones. Those personal spirometers that can upload their results usually do this with a USB cable to a personal computer. None are able to link to smartphones (or tablets) and I think this is a significant mistake. Partly because costs could be decreased by having the spirometer consist of only a sensor and bluetooth module (potentially inexpensive enough to be cheap to be able replace regularly?) with all of the processing being done by the smartphone. Software updates and enhancements could easily be distributed and since results would already be in the smartphone it would also be much easier to store and share results.

Links:

Carefusion

Micro1

Precision Diary

Pulmolife

Contec

The SP10 spirometer is sold by a variety of distributors on Ebay and Amazon. There is a version with bluetooth built in. It is made in China, probably by more than one manufacturer, and the Contec brand name is the most recent one used for this spirometer. It has been sold in the past under the MediTech brand name as well.

Ganseman

PC-Spiro. Update: No longer sold.

MDSpiro

Pulmolife

Spirocheck

Spirocheck Home Monitor

Nspire

Piko-6.  Update: No longer listed on the Nspire website.

 

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

My lab stopped inserting A-lines to get arterial blood samples during exercise testing well over 10 years ago. Our decision was partly based on the fact that we didn’t do them often enough to be good at it and partly based on the fact that we didn’t think that we were getting enough extra information from ABG’s to be worth the effort. Since another local hospital (a competitor but part of the same medical school network so we share pulmonary fellows with them) routinely performs level II and level III exercise tests we felt we could refer any patients that really needed ABG’s to the lab there. We don’t regret the decision and don’t feel that it has compromised the quality of our exercise testing.

Because we don’t obtain ABG’s, one of the values we don’t calculate is the deadspace/tidal volume ratio (Vd/Vt). Recently I was reading an article that related Ve-VCO2 to Vd/Vt and I was reminded of some the issues I had with Vd/Vt when I calculated it in the past. We’ve gone through two different exercise test systems since that time so I’m not sure if some of these problems still exist but I thought it would be a good idea to review both the problems and the literature on Vd/Vt to see if I could make some sense of them.

As a reminder, the original Bohr equation for Vd/Vt was:

The first problem I had run into was that mixed-expired CO2 (PECO2) is routinely calculated from CPET data as:

But it was also reported as a separate value by the test system’s software and the two values did not match.

The second problem was that the test system software reported a non-zero inspired CO2 concentration (PICO2). The PICO2 ranged from 10 mmHg at rest to 6 mmHg at peak exercise and when I reviewed some of the data from that time it is apparent that the PICO2 closely matched the difference between the reported and calculated PECO2.
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The most common problem we have with helium dilution FRC tests are leaks. Although the system tubing and spirometer bell leak occasionally, we do have valve failures relatively frequently. Valve failures are usually obvious but they sometimes only fail partially so leak checks are regularly performed on these test systems. We can’t perform leak checks on patients except while they are being tested however, and patient leaks are far more common than system leaks.

A technician asked me to look at a patient’s helium dilution FRC test because it had an odd helium tracing. The technician was sure the patient had been leaking but the FRC from this test was was actually the lowest of three tests and they weren’t sure why that was the case.

Once I saw it I was immediately able to tell the technician that it wasn’t a leak and that it was probably okay to report the results. I was able to say this because when there is a leak during a helium FRC test the helium constantly decreases and never plateaus. The rate of decrease may change but the most pertinent point is that the helium concentration never plateaus and even more importantly, it never increases.

I’ve seen this particular type of helium tracing before but to be sure I could properly explain what caused it I downloaded a table of system readings from the test software and they verified that what I thought happened was probably correct.

A bit of background first. A helium dilution FRC is measured using a closed-circuit technique.

Well over a hundred years ago it was realized that carbon dioxide was a potent respiratory stimulant and for this reason when a patient breathes in a closed circuit exhaled carbon dioxide has to be removed. Several different (and hazardous) chemicals were tried for this purpose but it was discovered that soda-lime was very effective at doing this and soda-lime has been used for this purpose ever since. (An interesting historical side note is that the first measurements of the rate of exhaled carbon dioxide production was performed by measuring the weight of soda-lime before and after it had absorbed carbon dioxide.)

One of the first clinical uses of a closed-circuit spirometer system was to perform basal metabolism testing by measuring oxygen consumption. This was done by filling a closed-circuit with oxygen and having a patient breathe for an extended period of time. Since all of the patient’s carbon dioxide was being absorbed, the decrease in circuit volume could only occur because of oxygen consumption. This kind of testing was performed first in Germany in the 1890’s and was brought to the United States before 1910. By the 1940’s the volume decrease due to oxygen consumption was a well documented and understood consequence of closed-circuit testing.

The first helium dilution FRC test was performed in the mid-1940’s. It used the same principle as a hydrogen dilution lung volumes test first performed in the 1930’s. Both helium and hydrogen are relatively insoluble gases. When a gas is insoluble only small amounts of it are absorbed by the blood or lung tissue and this makes it useful as a tracer gas. Helium is more insoluble than hydrogen and it is relatively easy to measure accurately, and it is for these reasons that it became a standard way to measure lung capacity.

Measuring lung volume with helium requires that the volume of the closed-circuit system remains constant. Since carbon dioxide is being absorbed and oxygen is being consumed this means that oxygen needs to be added throughout the test. The question then becomes how do you know how much oxygen to add?

When I started performing pulmonary function testing with manual systems the practice was to use the kymograph pen to draw a horizontal line where the patient’s end-exhalation (FRC) would be once the system had been set up for the test. Once I switched a patient into the circuit at end-exhalation I would set the oxygen flow meter for around 350 ml/min and then watch where their tidal breathing was relative to the line I’d drawn. If they rose or fell from the baseline I’d decrease or increase the oxygen flow rate. The idea was that at the end of the test, the patient was still on the baseline.

When computerized systems came along basically the same technique was used. The patient’s end-exhalation level is measured at the start of the test and oxygen is added (usually in pulses, not continuously) whenever the patient dropped below the baseline. When I added added oxygen manually there were times when I did better at it and times when I did worse. What I quickly learned was that there were a number of subtle things like the patient shifting their position in the chair or changing their breathing pattern (patients often hyperventilate at the start of a test and slow down later in the test) that could change their FRC baseline. Sometimes tests went longer than they “should have” because I added too much oxygen, “overshot” their FRC baseline and then had to wait for the patient’s oxygen consumption to return them to it.

The same problems occur when patients are tested with a computerized system as when they were tested on a manual system. When I reviewed the information for the FRC test with the odd helium tracing what I saw was that a modest amount of oxygen was being added during the first minute of testing but during the next minute or so the amount of oxygen being added to the circuit went up dramatically. During the final minute and a half or so the amount of oxygen being added decreased to a more or less normal level and stayed there until the end of the test.

So what likely happened was that the system added too much oxygen during the second minute of the test and “overshot” the patient’s FRC baseline. This diluted the helium in the breathing circuit and caused the dip in the helium concentration. It then took almost two minutes for the extra oxygen to be consumed and the helium concentration to return to its “real” level. Unfortunately, the test software doesn’t store any of the volume information from the test, so I couldn’t actually see if this what happened but I think this scenario fits the facts best.

But even if I’m wrong it still wasn’t a leak.

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

The first reasonably accurate flow-measuring device was the Fleisch pneumotachograph which was developed in 1925. Originally the Fleisch pneumotach bounced a light beam off a mirror mounted on a diaphragm and from there onto photographic film, all of which made it difficult to use. World War II saw the development of sensitive pressure transducers, amplifiers and recorders and by 1950 the pneumotachograph went totally electronic and began to be commonly used in routine pulmonary research.

The first spirometers that used a flow sensor came onto the marketplace around 1970. Since that time, flow sensors of one kind or another have made steady inroads and now the majority of test systems use flow sensors and there are only a small handful of volume-displacement spirometer systems still being manufactured.

There are a variety of difficulties involved with measuring gas flow rates and this has driven the development of a number of different flow measurement techniques. As well as the pneumotachograph, there are now Pitot tube, hot wire, turbine and ultrasonic flow sensors. Some of these techniques are more linear than others but none of them are perfectly linear.

The pneumotachograph however, is inherently the most linear method for measuring gas flow rates and has been more completely characterized than all other techniques. For this reason it is probably used in pulmonary function equipment more frequently than any of the other type of flow sensor and is also far more likely to be used in research.

Gas flow through a pneumotach is measured from the difference in pressure across a resistance. There are a variety of ways of creating this resistance but there are only two methods that are relatively linear, the Fleisch and the screen (aka Lilly) pneumotach.

The resistance in the Fleisch pneumotach consists of a set of narrow capillary tubes, parallel to the direction of flow.

In the screen pneumotach the resistance is one or more sheets of narrow-mesh screen placed perpendicular to the direction of flow.

 

Although a pneumotach is the most linear flow-sensing device, it is not perfectly linear. When a pneumotach is calibrated against a series of precision flow rates the pressure-flow relationship always shows a slight curve. The greatest difference between this calibration curve and a straight line is usually small (less than 3%) but it is not negligible and must be accounted for.

For Fleisch pneumotachs the primary factor that determines pressure-flow relationships is gas viscosity. The difference in pressure across the resistance is described by Poisselle’s equation for flow through a tube:

Since for any particular pneumotach its length and radius are fixed and it would seem that the only variable would be the velocity (flow rate) of the gas. Viscosity, however, is also variable and depends both on gas composition and on gas temperature.

Room air (~21% oxygen, 78% nitrogen, 1% argon, 25 degrees centigrade) has a viscosity of approximately 0.01846 centipoises. Exhaled air (~16% oxygen, 74% nitrogen, 4% carbon dioxide, 6% water vapor, 1% argon, 35 degrees centigrade) has a viscosity of approximately 0.01824 centipoises which is a decrease in 1.1%. Interestingly, although viscosity increases with temperature the addition of CO2 and H2O, both of which have substantially lower viscosities than oxygen and nitrogen, acts to decrease the overall viscosity of exhaled air. This example is only an approximation, however, since exhaled gas composition and viscosity will differ depending on the exhalation maneuver and where the gases are measured.

The Poisselle equation only applies to laminar gas flow. Turbulence occurs when the velocity of gas through a pneumotach rises above a threshold value which is best described by the Reynolds number. This is calculated from:

A flow with a Reynolds number below 2300 is laminar, above 4000 turbulent and in-between it is transitional. For turbulence gas density does matter and this is why helium-oxygen mixtures have been used both for research and therapeutic purposes.

The volume-pressure relationship of screen pneumotachs is complicated but seems to depend primarily on the Reynolds number determined by the diameter of the wire mesh and to the ratio between the hole size and wire diameter which in turn means that both gas density and gas viscosity can affect linearity.

The Reynolds number formula also shows that the narrower the diameter of the pneumotach the lower the flow rate at which turbulence occurs. The ATS-ERS standards state that a spirometer should be able to accurately measure flow rates up to +/- 14 liters/second. Theoretically this should determine the optimal size of a pneumotach used for pulmonary function testing but there is a tradeoff involved. In order to measure higher flow rates the diameter of a pneumotach needs to increase but when it does it will have a lower pressure/flow relationship and will be correspondingly less sensitive to low flow rates. Since the maximum flow rates are only rarely achieved the pneumotach for a test system may be selected that is more sensitive and accurate over a lower range of expiratory flows with the expectation that some kind of correction will be made for higher flow rates.

Turbulence is not necessarily bad. When gas flow is laminar the velocity of gas is highest in the center of a pneumotach and lowest at the outer edges.

The differential pressure within a pneumotach is measured at the edges of the pneumotach, not the center and for this reason is lower than would be expected from the average velocity of the gas flow. Turbulent flow tends to have a much “flatter” velocity profile and I suspect that some types of pneumotach (the variable-orifice type in particular) exploit this fact. Even so, all pneumotachs will make a transition from laminar to turbulent flow at some point, and the pressure-flow relationship is somewhat different on either side of the transition. As importantly, turbulent flows are “noisier” and this reduces the precision of flow measurements.

The Fleisch and screen pneumotachs depend on laminar flow and the Reynolds formula assumes that gas stream entering the pneumotach is already laminar. This means that what happens upstream of a pneumotach does matter. Asymmetrical velocity profiles caused by sharp bends, narrowings and interior projections can induce turbulence and so some care must be made in a test system’s architecture to prevent this.

Temperature is probably the most important factor affecting pneumotach accuracy. One reason is that the volume of inhaled air increases as it is warmed to body temperature and becomes saturated with water vapor inside the lung. At a room temperature of 20 degrees centigrade a liter of inhaled air expands by approximately 13%. Some of this expansion is lost during exhalation as heat and water vapor are recovered by the respiratory tract and more is lost between the patient’s mouth and the pneumotach but it still means that a greater volume of air is exhaled than was inhaled. This is usually corrected by the BTPS calculations but it is not as clear to me as I’d like about how the BTPS correction should be performed on exhaled volumes measured by pneumotachs.

The original notion for BTPS correction came from the difference between the temperature in the interior of a volume-displacement spirometer and that of exhaled air. A pneumotach may be at room temperature but compared to a volume displacement spirometer it has negligible thermal mass and does not affect the temperature of exhaled air anywhere nearly as much. I think that the distance the pneumotach is placed from an individual’s mouth has a greater influence on exhaled air temperature than the temperature of the pneumotach itself.

However, even though a pneumotach’s thermal mass is low, successive exhalations will cause its temperature to increase which in turn means that the BTPS correction factor needs to change as well. This change in temperature will be related to the number of spirometry maneuvers performed and how close in time they are performed to each other but is not necessarily predictable.

It is possible to measure exhaled air temperature within a pneumotach but this appears to be done only rarely. To some extent this is understandable because measuring exhaled air temperature is technically difficult and has a set of problems all its own but it does mean that when temperature is not measured the test system software will need to make assumptions of some kind in order to perform the BTPS correction.

Because pneumotachs are more or less at room temperature this means that the water vapor in exhaled air can condense on the resistance element (screen or tubes). Condensation acts to increase the resistance through the pneumotach and at least one study showed that after a series of exhalations expiratory volume can be overestimated up to 7% because of condensation.

It used to be common for pneumotachs to be heated to prevent condensation from occurring but this is now relatively rare. More than one study has shown that a heated pneumotach is more stable not only due to a lack of condensation but because its internal temperature is more stable and less affected by the temperature of exhaled air. Heating a pneumotach requires a fair amount of power which makes it unsuitable to portable applications and although it mitigates a number of temperature-related issues it does not completely abolish them.

The accuracy and linearity of a pneumotach also depends on the accuracy and linearity of the transducer that measures its differential pressure. The ATS-ERS statement on Spirometry states that spirometry equipment should be able to measure flow rates of +/- 14 liters/sec but does not set standards for the minimum expiratory flow rate that should be measurable except when discussing end-of-test (EOT) criteria. There it states that an exhaled volume that changes less than 0.025 L in 1 second meets EOT criteria. This means that a pneumotach needs to differentiate flow rates below 25 ml/sec in order to accurately determine EOT.

The maximum differential pressure range for a pneumotach is usually less than +/- 2 cm H2O and this means that to meet EOT criteria a pressure transducer must be sensitive enough to able to measure a differential pressure of less than 0.0036 cm H2O. The transducer also needs to be linear across the entire pressure range. One study, admittedly from over twenty years ago, showed a number of discrepancies in transducer linearity when actual results were compared to the manufacturer’s specifications although interestingly these tended to be at the highest pressures not the lowest.

Pneumotachographs used to be calibrated using a variable flow source and a precision rotameter (flowmeter). A range of flow rates were applied one at a time and a flow/pressure curve that described the characteristics of the pneumotach was slowly built using this process. The pneumotachs used for pulmonary function testing are now universally calibrated using a 3-liter syringe. Most test systems only require a few strokes of the syringe at different flow rates for a calibration. The flow range used for calibration differs from one system to another, but most probably are in the range of 1 to 5 liters/second.

During a series of syringe strokes the flow/pressure curves are analyzed mathematically and used to generate calibration curves. This process was first described over thirty years ago but at that time 50 strokes of the syringe were needed to develop the flow/pressure curves. This process was updated more recently (2003) but even then at least 10 strokes were required to develop the calibration curves. This doesn’t necessarily mean that the small number of strokes used to calibrate test systems are not sufficient since a relatively large number of strokes may be necessary when calibrating a pneumotach with unknown characteristics. Of more concern, at least conceptually, is the is that calibration is performed with room air at room temperature and the flow rates used are less than the maximum range of the pneumotach.

I started my career with volume-displacement spirometers. They have their own problems involving inertia, back pressure, frequency response, leaks and temperature. In addition they tend to be large, mechanically complex and relatively non-portable. For all these reasons I understand why manufacturers have moved towards systems that use flow sensors instead. The biggest advantage of volume-displacement spirometers however, was that it was relatively easy for anybody to verify their accuracy and linearity, and for this reason I am sorry they are no longer as common as they once were.

For all their simplicity there are numerous factors that can affect the accuracy of gas flow measurements made by a pneumotachograph. I do not think these factors are as widely known and appreciated as they should be. This is partly because this information is often hard to find (in older journals behind paywalls), partly because it is often hard to understand (the math can be very dense and authors frequently don’t write for a non-math audience) and partly because textbooks tend to spend more time explaining how pneumotachs work than on the reasons they don’t.

I am not suggesting that the computerized pneumotach systems we use in pulmonary function testing are inaccurate. These devices are usually developed and validated using computer-controlled motor-driven syringes capable of generating the standard ATS waveforms with physiologically correct gases at body temperature. Nevertheless, numerous assumptions about gas viscosity, laminar flow, temperature and electronic linearity are designed into these systems and I am concerned that we do not know what they are or how well they work. Nor is there any easy way to verify their accuracy since most labs do not have the expertise, the equipment or the time needed to perform advanced verifications.

A large amount of time and effort is put into the development of pulmonary function test systems and manufacturers have every right to consider their engineering and computer algorithms to be proprietary information. Manufacturers shouldn’t be required to disclose this proprietary information but I’d like to see something better than just a paper claim of accuracy. There should be some kind of middle ground where the factors that affect flow measurement accuracy are acknowledged, tested and verified. One place this could be addressed would be in the next set of ATS-ERS statements on pulmonary function testing. The current ATS-ERS standards were released almost a decade ago and set only broad outlines for test system specifications (although admittedly better than what came before). I think it is time for the bar to be raised and for a more precise set of requirements to be adopted.

References:

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

Duvivier C, Peslin R, Gallina C. An incremental method to assess the linearity of gas flowmeters: application fo Fleisch pneumotachographs. Eur Respir J 1988; 1:661-665.

Finucane KE, Egan BA, Dawson SV. Linearity and frequency response of pneumotachographs. J Appl Physiol 1972; 32(1): 121-126.

Frye RE, Doty R. A comparison of response characteristics of airflow and pressure transducers commonly used in rhinometry. IEEE Transactions of Biomedical Engineering 1990; 37: 937-944.

Gelfand R, Lambertson CJ, Peterson RE, Slater A. Pneumotachograph for flow and volume measurement in normal and dense atmospheres. J Appl Physiol 1976; 41(1): 120-124.

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

Johns DP, Pretto JJ, Streeton JA. Measurement of gas viscosity with a Fleisch pneumotachograph. J Appl Physiol 1982; 53(1): 290-293.

Miller MR, Pincock AC. Linearity and temperature control of the Fleisch pneumotachograph. J Appl Physiol 1986; 60(2): 710-715.

Miller MR, Sigsgaard T. Prevention of thermal and condensation errors in pneumotachographic recordings of the maximal forced expiratory maneuver. Eur Respir J 1994; 7: 198-201.

Shephard RA. Pneumotachographic measurement of breathing capacity. Thorax 1955; 10: 258-268.

Tang Y, Turner MJ, Yem JS, Baker AB. Calibration of pneumotachographs using a calibrated syringe. J Appl Physiol 2003; 95: 571-576.

Townsend MC, Hankinson JL, Lindesmith LA, Slivka WA, Stiver G, Ayres GT.  Is my lung function really that good? Flow-type spirometer problems that elevate test results.  Chest 2004; 125: 1902-1909.

Turney SZ, Blumenfeld W. Heated Fleisch pneumotachometer: a calibration procedure. J Appl Physiol 1973; 34(1): 117-121.

Van den Boom G, Van der Star LM, Folgering H, Van Schayck CP, Van Weel C. Volume calibration alone may be misleading. Respiratory Medicine 1999; 93: 643-647.

Yeh MP, Gardner RM, Adams TD, Yanowitz FG. Computerized determination of pneumotachometer characteristics using a calibrated syringe. J Appl Physiol 1982; 53(1): 280-285.

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

It’s been several decades since I last saw water-seal bell spirometers being used in a Pulmonary Function lab. They have been displaced mostly by systems that use flow sensors of one type of another and the small handful of equipment manufacturers that still make volume-displacement spirometers use rolling seals. This isn’t to say that this kind of spirometer isn’t being manufactured any more and in fact there appears to be a modestly thriving market in water-seal spirometers intended for use by students.

In the low-end of the market (under $1000) there are several different systems that would likely never make it into a PFT Lab. None of the manufacturers or distributors provide any claims about their accuracy and considering they are mostly made of injection-molded plastic it is hard to see what level of accuracy they could ever offer. Moreover, the volume readout for these spirometers is a dial that is moved by the chain attached between the bell and the counter-weight. The gradation on these dials allows you to measure (somewhat optimistically, I’d say) differences in exhaled volume of 0.1 liter.

 

At the higher end of the market (~$10,000) there at least one precision bell teaching spirometer with a kymograph that would probably meet ATS-ERS standards for volume, but since all counter-weighted bell spirometers have a limited frequency response (the bell can rise faster than the counter-weight and kymograph pen-assembly can fall) it may not meet standards for flow rates. This system has an in-line canister for soda-lime which allows it to measure oxygen uptake as well as being able to perform basic spirometry (it would probably also be able to measure lung volumes if it had a helium analyzer but that option is not offered).

So, why would you want to use an old-fashioned counter-weighted, water-seal, bell spirometer to teach students about the respiratory system? I think the first answer would be their durability and simplicity. Spirometers of this type can last for years despite the constant abuse of indifferent (and occasionally hostile) students and there is not much that can go wrong with them that isn’t relatively easy to fix.

Another reason though, is the causal and conceptual link that can be shown between exhaled air and the movement of the spirometer bell. This makes it clear that exhaled air is something that can be measured.  Most PFT lab systems are pretty much a black box between the patient and what shows up on the computer screen. This can make it hard to show somebody that has had no prior experience with pulmonary function testing what the link is between what the patient is doing and what the results of the tests look like. I will admit this is a personal bias since I was taught on bell spirometers (not that there was any other type way back when). My lab still has several bell spirometer systems and when I taught PFTs I almost always started with one of these systems.

So what can you teach with a student spirometer? Not much, but more than you might think at first. Vital capacity, of course, and I am sure that more than one enterprising teacher has had his class perform their vital capacity and then had their students line up in order based on their vital capacity volume. This almost always provides a clear lesson about the relationship between height, gender and vital capacity.

The other thing you can teach is something about the lung volume subdivisions. Even though these systems are mostly equipped with just a dial and are intended to measure only exhalation, you can have a student note the volume before they’ve exhaled as much as they can and then, while the student stays on the mouthpiece, have them return to their normal breathing level (FRC) and then note the volume again. Simple math will let the student calculate their vital capacity, inspiratory capacity, expiratory reserve volume and possibly even tidal volume.

What the low-end spirometers can’t teach is anything about expiratory flow rates. With the high-end spirometer, students can perform a timed vital capacity and from the pen tracing they can extract FEV1 and FEF25-75, but it is not possible to derive peak flow or a flow-volume curve from a kymograph tracing.

Having said that these system can’t show flow rates there is at least one student pneumotach-based spirometer.

 

Given the dominance of flow-based PFT systems this is a bit surprising there aren’t more spirometer systems like this, but even more surprising, the software used to analyze the flow signal is only designed to integrate the area under the flow curve and measure vital capacity (it may be able to show a flow-volume curve but the manual only talks about measuring vital capacity).

In one sense, the inability to teach expiratory flow rates is disappointing but student spirometers are intended for basic anatomy and physiology courses and expiratory flow rates are more about disease processes. I don’t think these student spirometers are in any way adequate to teach pulmonary function testing other than possibly a few of the most basic concepts but as a teaching adjunct for anatomy and physiology I think they serve a good purpose.

It also shows that good designs never go away. Almost 170 years after Hutchinson invented it, the water-seal bell spirometer still has a role to play.

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

The primary goal of a Cardio-Pulmonary Exercise Test (CPET) is to determine an individual’s maximum oxygen consumption (VO2), minute ventilation (Ve) and heart rate (HR). An adequate CPET is usually indicated by a Respiratory Quotient (VCO2/VO2) that is greater than 1.10, a heart rate greater than 85% of predicted or a Ve greater than 85% of predicted. There are a variety of reasons why patients are unable to exercise to their maximum. Although these reasons can of course include poor motivation, factors such a musculo-skeletal limitations or concerns about patient safety due to EKG changes can cause patients have a sub-maximal test.

Assessing a sub-maximal test is problematic but there are a number of derived CPET values that have been shown to be useful indicators even when the amount of test data is limited. We have used the Ve-VCO2 slope as one of these indicators for quite a while. Ve-VCO2 slope can be calculated using the Ve and VCO2 from the entire CPET or from just the pre-anaerobic threshold data. Given that there is usually a different Ve-VCO2 slope after AT that is influenced by lactic acidosis as well as VCO2 compared to the slope before AT our preference has been to use only pre-AT data. This means that a CPET can be significantly sub-maximal and we can still get an accurate Ve-VCO2 slope.

The Ve-VCO2 slope is primarily sensitive to the match between ventilation and perfusion in the lung. There is a loose correlation between the Ve-VCO2 slope and cardiac disease and this is usually because of the pulmonary consequences of cardiac disease, not because it is necessarily sensitive to cardiac output or peripheral vascular disease.

An individual’s maximum VO2 is a significant indicator of morbidity and mortality from cardiac disease but when a CPET is sub-maximal the VO2 will be as well. The Ve-VCO2 slope does not correlate well with maximum VO2 and cannot be used as a way to estimate it. A number of investigators however, have shown that the Oxygen Uptake Efficiency Slope (OUES) strongly correlates with maximum VO2 and that OUES can be calculated from sub-maximal CPET test data.

OUES is a function of VO2 and Ve. Ve/VO2 has been on CPET reports for almost as long as I have been doing exercise tests but I have had difficulty seeing its value. The primary reason for this is that an individual’s ventilation during exercise is driven by PaCO2 and acidosis, not PaO2. Like the Ve-VCO2 slope, the Ve-VO2 slope is relatively linear up to anaerobic threshold but after AT, it diverges strongly and can even become alinear.

It is for this reason the OUES is derived from the slope of VO2 versus Log Ve and this slope is actually reasonably linear over the course of an entire exercise test.

 A steeper slope and a higher OUES represents a more efficient oxygen uptake while a lower OUES shows that a higher amount of ventilation is required for a given oxygen uptake. Like the maximum VO2 OUES increases with increasing height and decreases with increasing age.

OUES has been studied using 50%, 75%, 90% and 100% of the data from a CPET study and has been shown to produce similar results and to show an excellent correlation with the maximum VO2 across this range. For this reason it has the ability to act as a surrogate value for VO2 during a sub-maximal test.

OUES is sometimes reported using VO2 as ml/min and sometimes with VO2 as Liters/min. A few investigators have used weight corrected VO2 (i.e. ml/kg/min) but is unclear that this has added any precision to the calculations or analysis of the results.

Reference equations from Hollenberg et al, published in 2000, indicates that for males OUES (in ml/min/log(L/min)) is:

1320 – (26.7 x age) + (1.394 x BSA)

and for females: 

1175 – (15.8 x age) + (841 x BSA)

A more recent set of reference equations from Sun et al, published in 2012 indicates that (in L/min/log(L/min)) OUES for males is:

-1.178 – (age x 0.032) + (0.023 x height (cm)) + (0.008 x weight (kg))

and for females it is:

-0.61 – (age x 0.032) + (0.023 x height (cm)) + (0.008 x weight (kg))

OUES has been studied almost exclusively in normal subjects and those with cardiac disease. Since the correlation between OUES and maximum VO2 depends on a normal arterial-venous oxygen gradient it is not clear how effective OUES is as a prognostic factor in patients with pulmonary disease. The relationship between OUES and maximum VO2 has been studied however, in subjects breathing a hypoxic gas mixture and in patients with pulmonary hypertension, and the correlation remained very good in both instances.

A small group of investigators has proposed that an alternate measurement, Oxygen Uptake Efficiency Plateau (OUEP) has a better correlation with an individual’s cardiac status. During exercise, before the anaerobic threshold occurs, there is a period where a plateau in VO2/Ve occurs. OUEP is the average value of VO2/Ve during this plateau.

The reference equation for OUEP (in ml/min/liter/min) for males is:

39.16 – (0.189 x age) + (0.036 x height (cm)) 

and for females it is:

42.18 – (0.189 x age) + (0.036 x height (cm))

Although they are calculated from similar values, OUEP and OUES seem to be sensitive to different aspects of cardiopulmonary fitness. Because OUES correlates with maximum VO2 it is increased when an individual is exceptionally fit. OUEP on the other hand, is relatively independent of fitness and appears to decrease only when cardiac disease is present. A study of mortality and morbidity in patients with cardiac disease showed an increased morbidity when OUEP decreased below 75% of predicted and increased mortality when it decreased below 67% of predicted.

Even though OUES has been studied since the mid-1990’s, it has not entered into common use. Part of the reason for this is that even though reference equations for OUES have been available since 2000 almost all studies of OUES have instead used group or longitudinal comparisons. I don’t think that OUES can be used as a substitute for maximum VO2 but in a sub-maximal CPET I think there is enough evidence in its favor that it should be possible to use it as an indication of what the maximum VO2 would have been if the test was adequate. OUEP is a much more recent arrival and at the moment I’d say that the jury is still out on it. The evidence appears to be strongly in its favor however, and if I see that it is reduced I will look carefully at the other CPET values that correlate with cardiac disease.

OUES and OUEP both look to be promising and useful additions to the CPET analysis toolbox. Their great advantage is that they can be calculated from sub-maximal test results. Like many other CPET values however, they are dependent on cardiac output, ventilation-perfusion matching and peripheral oxygen extraction. I suspect that OUES and OUEP will be shown to have limited value when lung diseases like ILD and COPD with diffusion defects are present. For this reason, until they have been studied more extensively with pulmonary diseases, the utility of OUES and OUEP will have to continue to remain on probation and should be relied on only when SaO2 remains normal during testing. 

References:

Arena R, Arrowood JA, Fei DY, Helm S, Kraft KA. Maximal aerobic capacity and the oxygen uptake efficiency slope as predictors of large artery stiffness in apparently healthy subjects. J Cardiopulm Rehabil Prev 2009; 29(4): 248-254.

Baba R, Tsuyuko K, Kimura Y, Ninomiay K, Aihira M, Ebine K, Tauchi N, Nishibata K, Nagashima M. Oxygen uptake efficiency slope as a useful measure of cardiorespiratory function reserve in adult cardiac patients. Eur J Appl Physiol 1999; 80: 397-401.

Baba R, Nagashima M, Goto M, Nagano Y, Yokota M, Tauchi N, Nishibata K. Oxygen uptake efficiency slope: a new indec of cardiorespiratory functional reserve derived from the relation between oxygen uptake and minute ventilation during incremental exercise. J Am Coll Cardiol 1996; 28: 1567-1572.

Baba R. The oxygen uptake efficiency slope and its value in the assessment of cardiorespiratory functional reserve. CHF 2000; 6: 256-258.

Baba R, Tsuyuki K, Yano H, Ninomiya K, Ebine K. Robustness of the oxygen uptake efficiency slope to exercise intensity in patients with coronary artery disease. Nagoya J Med Sci 2010; 72: 83-89.

Davies LC, Wensel R, Georgiadou P, Cicoira M, Coats AJS, Piepoli MF, Francis DP. Enhanced prognostic value from cardiopulmonary exercise testing in chronic heart failure by non-linear analysis: oxygen uptake efficiency slope. Eur Heart J 2006; 27: 684-690.

Hollenberg M, Tager IB. Oxygen uptake efficiency slope: an index of exercise performance and cardiopulmonary reserve requiring only submaximal exercise. J Am Coll Cardiol 2000; 36(1): 194-201.

Mollard P, Woorons X, Antoine-Jonville S, Jutland L, Richalet JP, Favret F, Pichon A. Oxygen uptake efficiency slope in trained and untrained subjects exposed to hypoxia. Resp Physiol & Neurobiol 2008; 161: 167-173.

Pogliaghi S, Dussen E, Tarperi C, Cevese A, Schena F. Calculation of oxygen efficiency slope based on heart rate reserve end-points in healthy elderly subjects. Eur J Appl Physiol 2007; 101: 691-696.

Sun XG, Jansen JE, Stringer WW. Oxygen uptake efficiency plateau best predicts early death in heart failure. Chest 2012; 141(5): 1284-1294.

Sun XG, Hansen JE, Stringer WW. Oxygen uptake efficiency plateau: physiology and reference values. Eur J Appl Physiol 2012; 112: 919-928.

Thomson SD, Peacock AJ, Johnson MK. The relationship between oxygen uptake efficiency slope and peak oxgen update is constant across different groups of pulmonary hypertension. Amer J Resp Crit Care 2013; 187: A4679.

Van Laethem C, Bartunek J, Goethals M, Nellens P, Andries E, Vanderheyden M. Oxygen uptake efficiency slope, a new submaximal parameter in evaluating exercise capacity in chronic heart failure patients. Am Heart J 2005; 149: 175-180.

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

For the last couple of years it seems that I’ve had more problems than usual with lung volume tests. Even though this seems to date from the time that my lab went through its hardware and software upgrade and we started performing N2 washouts I suspect that these problems have been around for a long time and these events just heightened my awareness of lung volume testing problems.

My lab performs helium dilution, N2 washout and plethysmographic lung volume tests. When you are assessing the quality of lung volume tests the first problem for the helium dilution and plethysmographic techniques is whether or not the Functional Residual Capacity (FRC) was accurately measured and for N2 washout, it’s whether or not the Residual Volume (RV) was accurately measured. Leaks are always an issue for any of these measurement techniques and for helium dilution and N2 washout leaks will almost always cause the Total Lung Capacity (TLC) to be overestimated. For plethysmography the picture is less clear since leaks can cause TLC to be either over- or under-estimated.

Once you accept that the initial measurement of FRC or RV is accurate, however, the next question is whether the SVC is accurate or not. Since SVC is a more relaxed test than a forced vital capacity the SVC volume should be at least the same as the FVC volume and it is often larger. When I see an SVC that is smaller than the FVC I tend to think that the calculated TLC is probably okay and it’s the RV that is more likely to be overestimated. This is because the Inspiratory Capacity (IC) part of the SVC maneuver (“take as deep breath in as you can!”) is the easiest part and when the SVC is low, it is usually because the Expiratory Reserve Volume (ERV, “blow everything out that you can!”) is underestimated.

This report came across my desk a couple of days ago. The lung volumes were performed by helium dilution.

 

At first glance the reduced TLC would seem to indicate the patient has restrictive lung disease but there were a number of things that didn’t quite add up. First, the FVC was reasonably normal. As restrictive diseases progress it’s not uncommon for the TLC to decrease more than the FVC but the difference in percent predicted between the two tests was more than I usually see.

Second, the SVC was significantly smaller than the FVC. If the SVC was reduced because the ERV portion was underestimated, then the RV should be elevated, but in this case the percent predicted RV was reduced even more than the TLC.

When I reviewed the raw helium dilution test data, two tests had been performed and the FRC was almost identical for both tests. The SVC was quite different for both tests however, and the reported SVC was the larger of the two and had the largest IC and ERV as well.

Next I reviewed the patient’s FVC tests and found that there was a lot of variability in FVC, FEV1 and the flow-volume loops. The reported test however, was the best of all the tests the patient had performed both in terms of volume and quality. The FVC test module does not calculate IC or ERV (and in fact I don’t know of any FVC test module that does) but when I looked at the position of the tidal loop within the overall flow-volume loop, it looked like the IC was larger than the one reported from the SVC. In order to confirm this, I transferred the flow-volume loop to a graphics program that has a ruler function and I was able to measure the IC from the FVC as being 2.46 liters.

 

Assuming that the IC from the flow-volume loop was correct, the TLC was actually 4.97 liters and 84% of predicted, and that puts it within the normal range.

A simple solution would have been to manually enter a new SVC using the FVC volume and if this was done it would have bring the calculated TLC to 4.87 liters and 82% of predicted (the reason it’s not 4.97 liters has to do with the difference in the assumed ERV). The problem with doing this is that ERV and IC do matter and that this would mix the ERV from one test with the VC from another. This is the same reason I believe that using linked maneuvers (the FRC and SVC from the same test) is much more accurate than measuring FRC and SVC separately and combining the “best” results.

The other problem is that the FVC test is not designed to measure IC and ERV and I used the second tidal loop from the last to measure the IC. It looked like the “best” tidal loop to me but there were other tidal loops and I would have gotten a different IC depending on which I selected. There may also be reasons why the tidal loops from this FVC don’t accurately reflect the patient’s normal end-exhalation FRC and it’s even remotely possible that the IC that was markedly overestimated and the ERV was markedly underestimated.

Although manually entering the FVC volume would probably provide more accurate results than those calculated using the SVC, for all these reasons I couldn’t guarantee that this was actually the case. Rightly or wrongly the best I felt I could do was to add a note that the lung volume test quality was suboptimal and the TLC was likely underestimated, and otherwise left the results alone (although I may re-think this the next time I see this kind of situation). I also emailed the ordering physician (one of the Pulmonary physicians I work with) and alerted them to this.

Errors with helium dilution lung tests usually cause the TLC to be overestimated so when a TLC is reduced I tend to think the test is going to be relatively accurate. Likewise, when a SVC is reduced I tend to think it is the IC that is going to be more accurate than the ERV. In this case the evidence points in the other direction and that makes this is a useful reminder that you always need to be skeptical when you review lung volume test results.

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