Author: Richard Johnston

If you are not already performing supine spirometry you should consider adding it to your arsenal of tests. Other than an exam table no new equipment is needed to perform it and it is a simple technique that can provide useful information towards diagnosing and monitoring diaphragmatic dysfunction. It is non-invasive when compared to a transdiaphragmatic pressure test (which requires an esophageal balloon), does not require ionizing radiation (fluoroscopy) and is likely more accurate and better tolerated than MIP and MEP tests. Candidates for this test include patients with neuromuscular diseases, suspected or known diaphragmatic paralysis or any patient complaining of dyspnea that cannot be explained by other routine testing.

Vital capacity is dependent on a number of factors, an important one being the range of motion of the diaphragm. The initial position of the diaphragm and the distance it can move is determined by effect of gravity on the abdomen and its contents. For this reason vital capacity is greatest when performed in the upright position and lower when performed in the supine position.

Persons with normal lung function usually see a decrease in FVC from upright to supine of about 3% to 8%. In individuals with diaphragmatic dysfunction this decrease is usually over 10%. Patients with unilateral diaphragmatic paralysis tend to have a decrease of at least 15% whereas those with bilateral diaphragmatic paralysis tend to have decreases greater than 25%.

The change in FVC from upright to supine may be less sensitive than the actual percent predicted FVC, however. As a rule of thumb, therefore, an FVC that decreases more than 15% in the supine position or that is less than 75% of predicted in the supine position should be considered as a positive indicator of diaphragmatic dysfunction.

Since this test requires the patient to be in a supine position an exam table that can be set in a completely horizontal position is necessary, and one that can be raised and lowered is ideal. We have used a folding massage table for a time, but I do not recommend using an actual bed as the softness and/or springiness of a mattress may interfere with the ability of the patient to perform the FVC maneuver. Although a pillow may make the patient more comfortable, it may also cause the upper airway to bend or constrict and for this reason should be avoided.

Before performing a supine spirometry test some thought should be taken regarding the patient’s suitability for testing. Patient and technician safety should not be compromised. Since many candidate patients have neuromuscular disease they may have limited mobility and may not be able to transfer to an exam table without assistance. Given that back injuries from lifting patients is one of the most common employee injuries in a hospital, patients that require more assistance than a technician is able to safely provide should not be tested. It should also be remembered that a patient is allowed to refuse testing if they don’t feel comfortable with the test. Lab staff should always take the time to explain the purpose of the test and the reason it should be performed, but after that it is the patient’s decision whether or not to proceed.

Supine spirometry should be performed using the same ATS/ERS criteria used for upright spirometry. We use the pre-drug mode for the upright spirometry and post-drug mode for the supine spirometry and are able to label the post-drug mode as Supine.

There is no CPT code for upright and supine spirometry so you can’t bill more than plain spirometry for the test. We are still on a mostly manual billing system and so we can control how the test is billed but if you have an automated billing system you should make sure that it will not take the presence of pre-drug and post-drug spirometry results as a flag to bill for pre/post bronchodilator testing.

When reviewing results it is useful to differentiate between diagnosing and monitoring. Patients sent for diagnosis are often in the early stages of their disease process and so the FVC criteria of 15% change and less than 75% of predicted is relatively easy to apply. When monitoring patients trends in the supine FVC is likely more important.

The Neurology department at our hospital has an ALS clinic so we routinely see a dozen or more patients a month with ALS, most often for monitoring the progress of their disease. ALS patients tire easily and this can limit the number of times they can perform a spirometry effort. There is also often upper airway involvement with ALS and spirometry results in both the upright and supine positions often shows pauses, plateaus and early termination and this can make interpretation difficult.

Even though supine spirometry requires extra effort for the PFT Lab and is not specifically reimbursed I think that it is a critical test for a portion of our patient population and for this reason alone it needs to be performed.

References:

Fromageot C, Lofaso F, Annane D, Falaize L, Lejaille M, Clair B, Gajdos P, Raphael JC. Supine fall in lung volumes in the assessment of diaphragmatic weakness in neuromuscular disorders. Arch Phys Med Rehabil 2001; 82:123-128.

Lechtzin N, Wiener CM, Shade DM, Clawson L, Diette GB. Spirometry in the supine position improves the detection of diaphragmatic weakness in patients with Amyotrophic Lateral Sclerosis. Chest 2002; 121:436-442.

Meysmann M, Vincken W. Effect of body posture on spirometric values and upper airway obstruction indices derived fro the flow-volume loop in young nonobese subjects. Chest 1998; 114:1042-1047.

Patel AS, O’Donnell C, Parker MJ. Diaphragm paralysis definitively diagnosed by Ultrasonography and postural dependence of dynamic lung volumes after seven decades of dysfunction. Lung 2007; 185:15-20.

Shepard JW, Burger CD. Nasal and oral flow-volume loops in normal subjects and patients with obstructive sleep apnea. Am Rev Resp Dis 1990; 142:1288-1293

Vilke GM, Chan TC, Neuman T, Clausen JL. Spirometry in normal subjects in sitting, prone and supine positions. Respir Care 2000; 45:407-410

Wade OL, Gilson JC. The effect of posture on diaphragmatic movement and vital capacity in normal subjects with a note on spirometry as an aid in determining radiological chest volumes. Thorax 1951; 6:103-124.

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

Many years ago I used to think that lung volume measurements were the easy part of PFTs. As time has gone on I’ve seen that getting accurate lung volume measurements is actually more difficult than getting accurate spirometry and DLCO results mostly because the errors tend to be subtle.

The errors that occur in lung volume measurements tend to cause an overestimation of lung volumes. This often means that restrictive diseases can be unrecognized or that hyperinflation and gas trapping can be diagnosed where it does not exist.

I see questionable lung volume test results more often than I’d like even from experienced technicians. When I find what went wrong I try to use these as “teachable moments” for all the the lab staff. Despite this the number of questionable test results never seems to drop below a certain level. I’d much prefer the error level was zero but since this is a situation that involves humans making measurements on humans I am likely being overly optimistic. A more realistic goal is to ask that the testing systems be smarter.

For at least the last 30 years there has been a industry-wide movement towards more automation in testing. The last time that I remember when you could buy a pulmonary function testing system that did not require a computer was the early 1980’s. This upside of this is that I can test a lot more patients more accurately and in less time with computer assistance than I could without it. The downside is that too many people believe that results are accurate because “that’s what the computer said”.

One of the most powerful aspects of computer software is that it can leverage expertise. Despite the dominence of computerized pulmonary function testing however, I have seen little increase in expertise. Routine testing errors that I first saw in computerized systems well over 20 years ago are still present. Here are two examples:

The procedure for the nitrogen washout test is for the patient to breath tidally for a period and then perform a slow vital capacity (SVC) maneuver. At maximal exhalation (RV) valves in the patient manifold are triggered, switching the patient to 100% oxygen as they resume tidal breathing. When the exhaled nitrogen level reaches a certain minimum level the test is completed. Here, there is a patient leak during testing and the post-SVC tidal breathing volume drifts upwards. When the computer analyzes the test results it overlooks two significant errors. First, it fails to recognize that the drift in the post-SVC tidal breathing indicates a leak which causes RV to be overestimated. Second, instead of measuring the maximal inspiration from where the SVC was performed, it takes it from the maximum of the post-SVC tidal breathing which causes SVC to be overestimated. Since TLC = RV+SVC, TLC is then markedly overestimated.

The procedure for plethysmography is for the patient to breath tidally for a period. This period is used to determine the volume level of the patient’s FRC. At end-exhalation a shutter interrupter closes (optimally at FRC) and the patient pants for a short period of time. While the shutter is closed the patient’s mouth pressure and the plethysmograph’s box pressure are measured and used to compute thoracic gas volume (TGV). When the shutter opens, the patient resumes tidal breathing and then performs a slow vital capacity maneuver. When the computer analyzes this test, it fails to recognize that the patient leaked while the shutter was closed which in turn caused the volume baseline for the SVC test to shift upwards. This causes the Inspiratory Capacity (IC) to be overestimated and since TLC = FRC+IC and RV = TLC – SVC, both TLC and RV are overestimated.

I have mixed feelings about calling for the manufacturers of test equipment to make their test systems smarter because I believe that technicians have a responsibility to understand the limitations of the equipment and the tests they perform. But since test equipment has become quite complicated and even trained and experienced technicians let these kind of errors pass through to a report, then it is evident that smarter software that at least warns that certain errors may be occurring would be helpful.

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

Almost all pulmonary function test systems seem to come with a module that can perform a computerized interpretation of PFT results. Their accuracy has been studied occasionally, often by the developers of a particular algorithm and just as often a rosy picture is painted. Given their limited (and likely pre-cleaned) data sets I am sure this is accurate as far as it goes. I have done my own admittedly very unscientific comparison and would say that for two-thirds of the patients tested the results are probably okay. The other third? Varying degrees of not so much.

This concerns me because the very locations that could use the expert assistance of computerized interpretation, small clinics and doctor’s offices where inexperienced and under-trained staff are usually tasked to perform the tests and where this would be most useful, cannot rely on it. This fact was highlighted in a recent report in the European Respiratory Journal which showed that computerized interpretation did not improve the quality of care in general practitioners offices.

Computerized interpretation of pulmonary function tests have been around for at least 40 years. At one time or another developers have used expert systems, branching logic, fuzzy logic and neural networks. Algorithms have been tweaked and updated as our understanding of pulmonary function testing has improved but none are essentially any better or more accurate now than in the 1970’s.

Why haven’t they gotten better? I think there are at least two important reasons why they haven’t and until these are addressed the quality of computerized interpretation will not improve.

First, interpretation algorithms proceed with the assumption that the test results are accurate and little or no thought has been given to the importance of assessing the quality of real-world test results. I am sure that all us who have performed pulmonary function testing realize that despite our best efforts to coach patients effectively test results are often less than perfect. Hesitation, early termination, leaks, inability to follow directions and just plain submaximal effort on the part of the patient are all too common.

Here are two examples of spirometry efforts we have all probably seen more than once or twice that any interpretation algorithm is likely to mis-interpret.

The first effort has a hesitation within the first second of exhalation that causes FEV1 to be underestimated. The second has an early termination of exhalation that is held for a prolonged period which causes FVC to be underestimated. The test systems these results came from indicated that they met all ATS/ERS criteria for back-extrapolation, length of test and end-of-test flow rates. Computer algorithms look only at the numbers and by the numbers these two efforts appear to be acceptable but in both cases the numbers are misleading.

When reviewing test results the first step should be to look at the quality of the test. The reported FVC, FEV1, TLC and DLCO values are always provisional until this is done. Teaching a computer system to recognize when these values are under- or over-estimated is a lot more difficult than teaching it an interpretation algorithm however, and this is because both patients and test systems can be incredibly ingenious when it comes creating errors. Nevertheless, common quality issues in tests can and should be recognized.

One possible approach would be to assign a confidence factor to each test result. As different searches for errors are made, the confidence factor for specific values can be raised or lowered as appropriate. When a final analysis is made the interpretation algorithm can take then take into consideration how accurate or how under or overestimated a test value may be. This in itself would likely lead to more reasonable interpretations and when the uncertainty is great enough the algorithm would also be able say “although results suggest X, because Y is {under/over} estimated due to Z, this may not be the case”. It is better that the uncertainty is clear when the results themselves are uncertain rather than reporting a diagnosis simply because it fits the numbers.

Second, interpretation algorithms tend to focus solely on the results from a single testing session. This is unfortunate because prior test results can significantly alter how the current test results should be viewed.

As one example, a certain number of patients with asthma routinely have spirometry results that show a symmetrically reduced FVC and FEV1 with a relatively normal peak flow. When looked at in isolation this pattern suggests restriction. However since these patients may have either had prior lung volume measurements that were normal or have had prior studies that showed a significant increase in FVC and FEV1 post-bronchodilator, this would show it is not restriction but obstruction with gas trapping.

Comparison of prior results can also be an alert to testing errors. For most patients TLC does not change significantly from visit to visit so a sudden dramatic change in TLC, particularly when spirometry or diffusion capacity values don’t change, is a red flag on test quality either in the current visit or the prior visit. Dramatic changes in spirometry or DLCO values could be considered to be more likely depending on the underlying disease state but should also raise some kind of a red flag.

Strictly speaking commenting on PFT trends pre se may not be considered to be part of a computerized interpretation but unless edited and amended manually these comments will not become part of the interpretation. Creating comments on trends as part of a computerized interpretation are probably trivial in a programming sense but assessing trends is a critical part of reporting results and any interpretation algorithm that ignores this is missing a critical component.

Finally, this may be silly in a way and not necessarily anything an interpretation algorithm could ever be expected to recognize, but errors that are occasionally made in entering a patient’s demographics can also have a significant effect on interpretation. Mary Jane Smith is not likely male. It is unlikely for a patient to have a FVC that is 160% of predicted so their 62” height is more likely 6 feet 2 inches instead. I see these errors several times a year and as testing systems become more integrated with hospital and clinic information systems they will likely become less common. That is in the future, however, and even then it may be necessary to recognize when to override a patient’s “real” demographic information, transgender patients being an example.

Interpretation algorithms have always held promise but by solely focusing on the reported numerical results and ignoring quality and prior test information they will always lack sufficient accuracy to be reliable. As well as reliability they should also attempt to meet real-world PFT lab needs such as commenting on trends that don’t necessarily meet the strict criteria of PFT interpretation but are still an important part of the process.

References:

Aikins JS, Kunz JC, Shortliffe EH, Fallat RJ. PUFF: An expert system for interpretation of Pulmonary Function data. Comp Biomed Res 1983; 16:199-208.

Ellis JH, Perera SP, Levin DC. A computer program for calculation and interpretatio of Pulmonary Function studies. Chest 1975; 68: 209-213.

Poels PJP, Schermer TRJ, Schellekens DPA, Akkermans RP, de Vries Robbe PF, Kaplan A, Bottema BJAM, van Weel C. Impact of a spirometry expert system on general practitioners decision making. Eur Resp J 2008; 31: 84-92.

Veezhinathan M, Ramikrishnan S. Detection of obstructive respiratory abnormality using flow-volume spirometry and radial basis function neural networks. J Med Sys 2007; 31:461-465

Zarandi MHF, Zolnoori M, Moin M, Heidarnejad H. A fuzzy rule-based expert system for diagnosing asthma. Transaction E:Indus Eng 2010; 17: 129-142

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

The PFT Lab I work with has recently gone through a major software and hardware upgrade. As part of this process we made the decision to switch our spirometry predicted equations to NHANESIII. The lab has been using the Morris predicteds for at least the last 25 years and this switch has led us to re-visit some of the issues involved in interpreting spirometry results.

More than one person that I’ve known and respected has said that spirometry is all about FEV1 and I think this is a true statement. There is a lot of other information you can get from a Forced Vital Capacity but it always comes back to FEV1.

Stepping aside from the mechanical and patient issues involved in obtaining an FEV1, once you have an acceptable FEV1 measurement how do you assess it? There is always the percent predicted and the lower limit of normal (LLN) but a reduced or normal FEV1 by itself cannot differentiate between an obstructive, restrictive or normal pattern. This is where the FEV1/FVC ratio comes in and an interesting question is where the predicted values for this ratio come from.

A day or so ago a report came across my desk got me curious about how the software was handling the FEV1/FVC ratio. Specifically:

                   Obs:         %Pred:         Predicted:

FVC:           1.90             78%            2.45

FEV1:         1.24              77%           1.62

FEV1/FVC:   65               93%            70

Looking at this it seemed that the predicted FEV1/FVC ratio is wrong. Up until the upgrade the predicted FEV1/FVC ratio was always calculated by taking the predicted FEV1 and dividing it into the predicted FVC. In this case the result would have been 66.1 and 98.7 percent predicted. So what’s happening here?

The NHANESIII study includes a predicted equation for the FEV1/FVC ratio that is separate from the equations for predicted FEV1 and predicted FVC. This makes sense because it allows for the calculation of an LLN specifically for the FEV1/FVC ratio. I am not sure how you would do this using the LLN from the FEV1 and the LLN from the FVC since I can easily see where both the FVC and FEV1 could be well within normal limits, but the ratio isn’t.

Our new software is calculating the predicted ratio using this equation (direct calculation) and not from the predicted FEV1 and FVC (indirect calculation). What is interesting about this equation is that the only factor is age whereas the predicted equations for FVC and FEV1 use both age and height, and in addition uses them exponentially (as squares). This has some interesting consequences. I set up a spreadsheet and graphed the equations to help make this clearer.

As would be suspected both height and age play a role in the difference between direct and indirect calculations of the FEV1/FVC ratio and this is most evident in short people and somewhat evident in those who are tall. The first graph is for an average-sized 69 inch tall male and the difference between the direct and indirect values for predicted FEV1/FVC ratio are minimal. In contrast the second graph is for a 62 inch tall male and the difference is particularly significant for young and elderly individuals. As a point of information the patient whose test results originally brought this question up was both short and elderly.

Which approach for calculating the FEV1/FVC ratio is correct? I think the key question is whether the FEV1/FVC ratio is actually the same regardless of height or whether there is a scaling effect. We’ve run into this problem in the past when trying to interpret results from excessively short (48”) or excessively tall (86”) individuals. At the time we decided to use the FEV1/FVC ratio from an average-sized individual because the predicted ratio in these cases (an indirect calculation using the Morris equations) was clearly incorrect, but this was just a guess on our part. It is evident however, that patients who are height outliers will have unusual predicted FEV1/FVC ratios if they are calculated indirectly.

Although the NHANESIII equations were published without specifically noting a height range for its participants a graph of height versus FEV1 indicates that the minimum height for Caucasian males was 158 cm (62”) and the maximum height was 194 cm (76”). The effect of height on the predicted FEV1/FVC ratio at the extremes of this height range show opposite effects. For tall individuals the indirect ratio is less than the direct ratio for the young and greater for the elderly. For short individuals the indirect ratio is greater than the direct ratio for the young and less for the elderly. This may well indicate that there is a height-associated scaling effect or it may be a problem with the statistics used to create the equations.

I have searched and have been unable to find any research that specifically looked at the FEV1/FVC ratio and height. The issue of height and FEV1/FVC ratio is intriguing but presently I’d have to say there is no clear evidence so for the time being we are going to continue to use the directly calculated FEV1/FVC ratio.

References:

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

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

I was reviewing the specifications of different pulmonary function test systems recently and saw that several manufacturers were advertising that some of their test systems are able to measure TLC, FRC and RV from a single-breath maneuver. This is true, but only to a very limited degree and I think it is reasonable to ask how accurate and clinically useful these measurements are and whether it is legitimate to bill for the test.

The measurement is made by having a patient exhale to RV and then inhale a gas mixture containing a tracer gas (an insoluble gas like helium or methane) to TLC. When the patient exhales, the degree by which the tracer has been diluted is then used to calculate the patient’s TLC. The math is quite simple and as is expressed as:

TLC = (inspired volume x (Fi_trace/Fe_trace)) – machine deadspace

This is done routinely as part of the DLCO test and there it is referred to as alveolar volume (VA) and it should be noted that all manufacturers are using the VA from the DLCO test as a substitute for TLC and are not performing single-breath TLC as a separate measurement.

The full panel of lung volumes is calculated from the overall breathing maneuver. When the patient exhales to RV, ERV is measured from end exhalation of the tidal breathing immediately beforehand. When the patient performs a inspired vital capacity, RV is calculated by subtracting the VC from the calculated TLC. FRC is then calculated by adding ERV to RV.

In patients with normal lungs the correlation between TLC measured by the single-breath method and by the helium dilution, nitrogen washout and plethysmographic methods is good. In patients with obstructive lung disease however, the correlation is poor and the TLC measured by the single-breath technique systematically underestimates the TLC obtained by other methods. This is attributed variously to maldistribution of inspired gas, gas trapping and poor gas mixing and has been common knowledge since at least the 1960’s.

More than one researcher has studied the relationship between the degree of airway obstruction as indicated by the FEV1/FVC ratio and single-breath TLC and then devised a correction factor. When applied to groups of patients these correction factors appear to work reasonably well but an inspection of the scatter of the results from these studies show that for an individual patient this is much less so. Part of this can be attributed to differences in a specific patient’s underlying lung disease, but there are also other confounding factors.

First, the FEV1/FVC ratio itself is dependent on patient effort and the FVC in particular is dependent on the length of time a patient is willing to exhale. In a patient with obstructive lung disease a given spirometry effort may be acceptable by ATS standards but can still underestimate FVC and therefore overestimate the FEV1/FVC ratio. So how accurate is the FEV1/FVC ratio when applied to correcting the single-breath TLC?

Second, none of the researchers studying single-breath TLC have shown any particular concern about inspired volume and its effect on the measurement of TLC. Their underlying assumption has been that all of their patients inhaled to TLC. They may have been correct, but in any given test how is this determined? The ATS/ERS standard for DLCO testing says that the inspired volume should be 85% of the patient’s largest known vital capacity. An acceptable DLCO effort can therefore have an end-inspiration that is 15% of the VC below TLC and when that happens the measured TLC will be likewise reduced.

Finally, the selection of washout volume and alveolar sample volume will affect the calculated single-breath TLC. In a patient with obstructive lung disease, likely because of maldistribution of the inspired gas mixture, the concentration of the tracer gas tends to decrease during exhalation. For this reason using a tracer gas concentration from the beginning of exhalation will lead to a calculated TLC that is lower than if taken from later in exhalation. TLC should be calculated by considering the average tracer gas concentration from the entire exhalation but the washout and sample volumes used to measure it are optimized for DLCO measurement, not TLC.

Single-breath TLC has not been studied in patients with restrictive lung diseases. Since these patient’s tend not be be obstructed it would be easy to assume that their single-breath TLC should be reasonably accurate. Maldistribution of ventilation however, does occur in these patients. I have personally seen a small number of patients with interstitial disease that have a pattern opposite to patients with obstruction where tracer gas concentrations are lowest at the beginning of exhalation and increase as exhalation continues. In these patients single-breath TLC may well be overestimated.

So, are single-breath TLC measurements accurate? Sorta. Sometimes. Maybe. They can be useful in quickly ruling out restrictive lung disease in some patients with a reduced FVC but the fact is that for any given patient there is going to be some uncertainty and that this level of uncertainty is going to be significantly greater for patients with obstructive lung disease. Correction factors are only guesses. Because the single-breath TLC cannot be counted on to produce reliable and accurate test results in my opinion it should neither be reported as part of a patient’s test results nor should it be billed. For the same reasons I also think it is misleading for equipment manufacturers to advertise this capability in any test system and that this practice should be ended.

References:

Burns, CB, Scheinhorn DJ. Evaluation of Single-breath Helium Dilution Total Lung Capacity is Obstructive Lung Disease. Amer Rev Resp Dis 1984; 130: 580-583.

Horstman MJM, Mertens FW, Schotborg D, Hoogsteden HC, Stam H. Comparison of Total-breath and Single-breath diffusing capacity in healty volunteers and COPD patients. Chest 2007; 131: 237-244.

Loiseau A, Loiseau P, Saumon G. A simple method for correcting single breath total lung capacity for underestimation. Thorax 1990; 45: 873-877.

MacIntyre N, et al. Standardisation of the single-breath determination of carbon monoxide uptake in the lung. Eur Respir J 2005; 26: 720–735

Pesola GR,Magari RT, Dartey-Hayford S, Coelho-D’Costa V, Chinchilli VM. Total lung capacity: single breath methane dilution versus plethysmography in normals. Respirology. 2007; 12: 291-294.

Punjabi NM, Shade D, Wise RA. Correction of Single-breath Helium Lung Volumes in patients with Airflow Obstruction. Chest 1998; 114: 907-918.

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

Mouthpieces serve at least two purposes. The first is to prevent cross-contamination among patients using PFT equipment. The ATS Statement on General Considerations for Lung Function Testing, (Eur Resp J, 2005; 26: 153-161) discusses this and it is clear that mouthpieces should be used whenever and wherever pulmonary function tests are performed.

The second purpose however, is to prevent patients from leaking air during testing. Leaks are a chronic problem for all pulmonary function tests and my experience has been that when they occur it is almost always the patient that is leaking and not the equipment.

Although all pulmonary function tests can be affected by patient leaks the helium dilution and nitrogen washout lung volume measurements are particularly prone to leaks due of the length of time it takes for them to be performed. These tests are also sensitive to small leaks because the accuracy of the measurements is based on relatively small changes in gas concentrations.

A flanged rubber (or soft plastic) mouthpiece usually isn’t needed for most spirometry testing and may not be necessary for Diffusion Capacity testing but there will always be patients that cannot maintain a seal with any kind of simple round mouthpiece and so a flanged mouthpiece should always be an option.

I am a strong advocate of the use of flanged mouthpieces and I am concerned that over the last decade, and probably longer, there has been a wholesale movement towards the use of small flanged mouthpieces. It has, in fact, gotten quite difficult to find large mouthpieces.

I know I will be dating myself when I say that when I say that for the first twenty years I spent in a pulmonary function lab there were only two sizes of mouthpieces: adult and child. Almost all flanged mouthpieces being sold today I would consider to be the same as what the child size used to be.

I am not sure how or why this trend began. It may be easier to get a patient onto a small mouthpiece, but once there they have to work harder to keep their lips tight around it and are more likely to leak during testing. Patients often complain that their lips are tired after a lung volume test when a small mouthpiece is used. The advantage of the large (adult) sized mouthpieces is that once it’s in place, it is very hard for a patient to leak around it even if they don’t keep their lips tight. There are patients, like those with TMJ or scleroderma, that cannot open their mouths wide enough for a large mouthpiece but I’ve always been able to get a large mouthpiece into almost every patient I’ve tested.

I’ve talked to a couple manufacturer’s representative about this and they have said this is what their customers want. At the same time though most labs are not offered any alternative to small mouthpieces or may not even be aware there are alternatives. There are only a couple manufacturers (A-M Systems, Vacumed) that still make large mouthpieces and adapters for different brands of equipment and in-line filters can be hard to find or nonexistent.

I am concerned about this trend because I think that small mouthpieces are not benefiting our patients. They may be easier to use but they are far more likely to produce inaccurate results.

I am even more concerned, however that I’ve heard that some PFT labs are not using flanged mouthpieces at all and are instead using cardboard mouthpieces for all of their tests. This is inexcusable both in terms of patient cross-contamination and in terms of accurate testing. If it is being done to save money it is a false economy and the real price being paid is in inaccurate test results and patient safety. If it is being done because the staff don’t know any better, then the medical director needs to be taken to task.

Personally I’d recommend that flanged rubber mouthpieces should be available for any type of pulmonary function testing, and mandated for lung volume measurements. Labs should also stock at least a couple different sizes of mouthpieces and always use the largest one a patient is able to accommodate. There are already a sufficient number of pitfalls involved in performing accurate pulmonary function tests without making it more difficult for the patient to maintain a tight seal during testing.

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

Most pulmonary technicians and physicians are aware that a patient’s hemoglobin and carboxyhemoglobin levels are factors that affect DLCO test results. What may be less well appreciated is the degree to which DLCO varies with the alveolar oxygen concentration.

Oxygen and carbon monoxide both compete for uptake by hemoglobin so when alveolar O2 is low or high the measured DLCO will also vary accordingly. The relationship between DLCO and PAO2 has been studied both in a regards to FIO2 and to barometric pressure. Both empirically and mathematically DLCO is estimated to change by approximately 0.35% per mmHg PAO2 change.

Although PAO2 in exhaled DLCO samples has not been studied to any real degree a table of baseline patient information in the 1986 study by Kanner and Crapo showed a range of 109.8 mm Hg to 121.6 mm Hg in a small group of healthy subjects although testing was performed with an FiO2 of 25% at an altitude of 6000 feet.

I have been unable to find anyone who has studied the effect of the length of time spent exhaling to RV may have on PAO2. The ATS/ERS statement on DLCO testing recommends that exhalation to RV should take less than 6 seconds but in practice this depends on the patient and will probably range from 3 to 15 seconds more or less routinely. Simple math using the alveolar air equation and normal resting values for oxygen consumption produces an estimated change in PAO2 of approximately 10 mm Hg during a 6-second breath-hold at RV.

Because PFT Labs in the USA routinely use an inspired oxygen concentration of 21% and European PFT Lab routinely use a concentration of 17%-18% the results from same patient will vary according to where they are measured. DLCO measured at these two FIO2 leads to an approximately 5% difference in measured values so labs need to be careful when comparing results and when selecting the appropriate predicted equations.

The ATS/ERS statement on DLCO testing acknowledges the effect alveolar oxygen has on DLCO results by recommending that patients be removed from supplemental oxygen ten minutes before testing (and is there anybody that has actually followed this guideline for our oxygen-dependent patients?) and by adjusting predicted values for altitude. The ATS/ERS statement also gives a correction factor if PAO2 is measured but PAO2 is not measured by any commercially-available test system at present.

Since PAO2 has not been studied extensively it is difficult to gauge what level of error it contributes to the DLCO measurement. Back-of-the-envelope calculations suggests that a range of at least 20 mmHg in PAO2 is probably normal which means that PAO2 contributes at an error level of at least 7% to the measurement of DLCO and that is likely a conservative estimate.

Overall DLCO accuracy would likely be improved and both individual and laboratory variability would likely be decreased if PAO2 was routinely measured in the exhaled DLCO alveolar sample. PAO2 isn’t a routine measurement partly because its effect on DLCO has been overlooked and partly because of the added cost and complexity it would bring to testing systems. The latter is no longer the case, however. Any testing system that measures lung volumes by nitrogen washout has a rapid-response, high precision oxygen analyzer already connected to the breathing manifold that could also be used to measure PAO2. Adding PAO2 measurements in these test systems is now only a matter for software and there is no obvious reason that any of these systems couldn’t be upgraded to measure PAO2 with just a software revision.

So why haven’t manufacturers already offered this option? Conservatism is part of it, but also probably because enough customers haven’t asked for it. So, take a step for higher DLCO accuracy and if you already have a test system that measures lung volumes by nitrogen washout, ask for a software upgrade. If you are instead looking for a new test system make it a point to ask if it can measure PAO2.

References:

Frey TM, Crapo RM, Jensen RL, Kanner RE, Kass JE, Castriotta RJ, Mohsenifar Z. Adjustment of DLCO for varying COHb and alveolar PO2 using a Theoretical adjustment equation. Respir Physiol 1990; 81: 303-312

Kanner RE, Crapo RO. The relationship between alveolar oxygen tension and the single-breath carbon monoxide diffusing capacity. Am Rev Respir Dis 1986; 133: 676–678.

MacIntyre N, et al. Standardisation of the single-breath determination of carbon monoxide uptake in the lung. Eur Respir J 2005; 26: 720–735

Normand N, Marie C, Mouadil A. Single breath transfer factor in young health adults: 21% or 17.5% inspired oxygen? Eur Respir J 2004; 23: 927-931

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

Hi!  My name is Richard Johnston.  Pulmonary Function testing is an often overlooked and under-appreciated field.  I first started working in a Pulmonary Function Lab with manual test systems in 1973 where I had to measure pen traces on kymograph paper and hand-calculate test results.  I’ve built, maintained, repaired and modified test equipment since I started in this field.  I started working with computers in the 1970’s and designed and wire-wrapped my own hardware interfaces for them because that’s what you had to do at the time.  I’ve programmed computers for research and routine clinical testing and somehow managed to have one of the first networked PFT labs in Boston. Over the years I’ve learned a lot about equipment but that’s because I broke a lot of things along the way too.  

Against my inclination and better judgement I have been a lab manager for over 30 years.  I found that my job description changed every year and that my hospital managers always seemed to feel that I was supposed to have figured what the changes were on my own.  Although I’ve done my share of research I’ve come to feel that a clinical Pulmonary Function Lab is where the rubber hits the road and far more enjoyable for that reason. I feel fortunate that I’ve always worked in teaching hospitals with physicians that were interested in education.  I’ve learned a bit about teaching and have taught numerous students, technicians and physicians about Pulmonary Function and Cardiopulmonary Exercise testing. The most important thing I’ve learned however, is that there is always something new to learn.

I am primarily a technologist.  For that reason my interest starts with the tests and the test equipment, but the reality is that you can’t consider these things in isolation. What’s also important is the physiology and anatomy of what the tests are supposed to be measuring; how you decide what’s normal and what’s abnormal; how the information is stored and reported; what purpose the tests have for the patient and the ordering physician; and how to run a testing facility effectively.

Because I’ve personally built test systems and programmed computers I’ve learned how hard it can be to get equipment to do what you want it to do.  In order to find out how to do tests and build things I’ve had to read a lot of textbooks and research papers by authors who seemed to delight in making them obscure and hard to understand.  Worst of all I’ve had to become a skeptic since I’ve known some of the researchers who bent the results to fit their preconceptions and still got published.  Despite the negatives I feel fortunate that I’ve had to opportunity to do these things.

I am currently battling pancreatic cancer and have had a very rocky course so far but I’m fortunate that I’ve recovered enough to be able to continue with the blog for the time being.  The prognosis for pancreatic cancer is poor but I’m taking it a step at a time.  Thanks to everybody for their kind comments and wishes.

I will admit to having concerns about the future of the blog.  I would like to see it continue even if I am unable to do so.  The best way to do this would be to make the blog a more public property.  To this end if you would be interested in contributing an article or in becoming an editor please contact me at:

[email protected]

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