6MWT re-visited, now with the MCID!

I often find topics for this blog in a sideways fashion. Recently while searching for something else I ran across an article about the minimum clinically important difference (MCID) of the Residual Volume (RV) in patients with emphysema. I’ve come across the MCID concept before but I had never really followed up on it. This time I started researching MCID and immediately ran across a number of articles about the MCID of the 6-minute walk test (6MWT). This got me to review the articles I have on hand and I found that since I last wrote about the 6MWT I’ve accumulated quite a few new (or at least new to me) reference equations as well as a number of articles about performance issues. Given all this how could I not re-visit the 6MWT?

In addition to the 6 reference equations I had previously I’ve found another 13 female and 14 male reference equations for the 6MWT (total 19 female, 20 male) which is an opportunity to re-visit the selection process. This immediately raises the question about what factors should be used to calculate the predicted 6-minute walk distance (6MWD). Because the 6MWT is essentially an exercise test age has an obvious effect on exercise capacity so it is no surprise that with the exception of one set all of the reference equations consider age to be a factor. It should be noted however, that many of the reference equations are intended to be only applied over a limited range of ages and this may limit their utility.

Given the fact that stride length and therefore walking speed are directly related to height it is somewhat surprising to find that only twelve of the male and eleven of the female reference equations consider height to be a factor. When height is a factor, the predicted 6MWD is usually affected something like this:

Height_6MWD

Weight also affects exercise capacity but an interesting question is whether the observed 6MWD should be compared to a predicted 6MWD based on a “normal” weight or whether the 6MWD should be adjusted to the individual’s actual weight and assessed accordingly. To some extent this is already an issue in current PFT predicted equations. For example, weight is not a factor in any of the FVC or TLC reference equations and when lung volumes are decreased in the presence of obesity they are considered to be abnormal. On the other hand, the reference equations I use for maximum oxygen consumption during a CPET include weight as a factor and for a number of reasons this is likely the correct approach. For this last reason I would think that weight should be a factor and ten of the reference equation sets consider weight (or BMI) to be a factor. When weight is a factor, the predicted 6MWD is usually affected like this:

Weight_6MWD

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Proposal to improve the readability of flow-volume loops

I’ve been planning on putting together a tutorial on characterizing and interpreting the contours of flow-volume loops so I’ve been accumulating flow-volume loops that are examples of different conditions. Lately I was reviewing some of them and noticed that when I tried to compare loops from different individuals with similar baseline conditions that the different sizes of the flow-volume made this difficult. For example, these two loops are both from individuals with normal spirometry.

FVL_Scaling_05

FVL_Scaling_08

One is from short, elderly female and one is from a tall, young male. If all you had to look at was the flow-volume loops, you might think that the smaller loop was abnormal, but the larger loop actually comes from a spirometry effort with an FVC that was 92% of predicted while the smaller loop’s FVC was 113% of predicted. The difference in sizes of these loops is of course due to the difference in age, gender and height between these individuals but also because of settings we’ve made in our lab software and because of the ATS/ERS spirometry standards.

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Temperature (in)correction

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

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

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

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

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Have you checked the math on your reports lately?

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

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

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

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

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Transgender PFTs

I was reviewing PFT reports today and noticed that a patient appeared to have had the wrong gender entered in their demographic information. Specifically, the patient had an unambiguously masculine name but had been entered as female. Just to be sure I checked the patient’s on-line medical record and there he was listed as male. I had noticed from the trend report that the patient had been in the PFT lab numerous times. Since the basic patient demographics (name, date of birth, height, gender, etc.) are automatically forwarded into a new demographics record when a new PFT lab visit is created it struck me as odd that after all this time we had somehow managed to make a mistake with something as basic as gender. For this reason I thought it would be a good idea to see how far back this problem existed and started going back through the patient’s PFT records. About four visits ago the patient’s name suddenly changed to one that was unambiguously feminine.

I was immediately concerned that two different patient’s records had somehow gotten merged. The last time this happened was over 20 years ago and was due to an entry error in the patient ID that was further compounded by how the lab’s software handled new demographic records at the time. Merged records is therefore a symptom of a serious database problem but when I compared the date of birth of the two patients, I was immediately able to see that they were the same. Since this is incredibly unlikely my thought then was that the patient may have had a gender reassignment. When I went back to the patient’s online medical record and searched more carefully, I was able to find that this had occurred over a year ago. This is not the first time we’ve had a transgender patient and so it is an issue we’ve learned how to handle.

So what effect does gender reassignment have on an individual’s pulmonary function test results?

None whatsoever. Gender reassignment by itself does not affect FVC, FEV1, TLC or DLCO. What it does affect is how we interpret the test results and it can also cause some interesting data management problems that are worth noting.

All pulmonary function reference equations differentiate between genders. Although the differences between races and ethnicities is somewhat open to question, there is little doubt about the differences between genders. When individuals with the same height are compared, females universally have lower flow rates, volumes, respiratory muscle strength, gas exchange and oxygen consumption than males. Because lung function is determined during an individual’s childhood and adolescent developmental periods, gender reassignment does not affect lung function and when it is assessed this has to be done using reference equations that are appropriate to an individual’s original gender.

Depending on which way a gender reassignment occurs, results that would be considered normal for a female would likely look reduced for a male, and results that would be considered reduced for a male would likely look normal for a female. The selected gender will therefore make a difference about what an individual’s PFT results look like to a reviewer.

The patient whose gender raised this issue has relatively severe lung disease and is probably not the best example for this, but its what’s in front of me right now.

Female: Observed: %Predicted: Predicted:
FVC: 1.37 42% 3.25
FEV1: 0.92 36% 2.54
FEV1/FVC: 67 84% 80
TLC: 2.69 54% 4.93
RV: 1.34 79% 1.69
DLCO: 14.90 78% 19.12

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What’s normal about MIP and MEP?

The static respiratory pressures, Maximal Inspiratory Pressure (MIP or PIMAX) and Maximal Expiratory Pressure (MEP or PEMAX) are a way to non-invasively assess respiratory muscle strength. Respiratory muscle weakness is present in a number of conditions, most notably neuromuscular diseases and disorders, but also malnutrition, cardiovascular disease, polymyositis, sarcoid and COPD. Strictly speaking, the maximal inspiratory and expiratory pressures are not generated solely by the respiratory muscles but also by the elastic recoil. The elastic recoil of the lung at TLC contributes up to 40 cm H2O towards MEP and the elastic recoil of the chest wall at RV contributes up to 30 cm H2O towards MIP. Even so, an individual cannot reach TLC or RV without the use of their respiratory muscles so the measurements are still valid regardless of how the pressures are generated.

I have mixed feeling about MIPs and MEPs but this is mostly because many patients perform these tests poorly, making it hard to interpret results. Normal results can rule out respiratory muscle weakness but reduced results are not necessarily diagnostic. Nevertheless, they are still valuable tests and it is important for them to be performed correctly.

MIP is measured at RV and MEP is measured at TLC. The ATS/ERS statement on respiratory muscle testing indicates that each effort should last at least 1.5 seconds and that at least three measurements within 20% of the highest value should be obtained. A maximum number of attempts has not been specified but most research studies limited this to 5 or 6.

The actual maneuver depends somewhat on the equipment configuration. Respiratory pressures were originally measured using a pressure gauge and most early systems consisted of just a mouthpiece and a gauge (or gauges).

from 'Interpretation of Pulmonary Function Tests - A Practical Guide' by RE Hyatt, PD Scanlon and M Nakamura, Published by Lipincott-Raven, 1997, page 90.

from ‘Interpretation of Pulmonary Function Tests – A Practical Guide’ by RE Hyatt, PD Scanlon and M Nakamura, Published by Lipincott-Raven, 1997, page 90.

To use this type of system the patient either exhales to RV or inhales to TLC, places their lips around the mouthpiece and then forcefully inhales or exhales. Because of the limited amount of time available for lip placement a round plastic or cardboard mouthpiece is usually used.

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When TLC, RV and VC don’t add up

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

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

predicted TLC = predicted VC + predicted RV.

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

predicted TLC ≠ predicted VC + predicted RV.

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

predicted TLC ≠ predicted FRC + predicted IC

predicted RV ≠ predicted FRC – predicted ERV

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The NHANESIII FEV1/FVC ratio and height, revisited

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

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

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

Male_50yo

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Standing height, ethnicity and the vital capacity

In 1844 John Hutchinson published his first paper describing his spirometer and his research on the Vital Capacity. He was the first person to use the word “spirometer” to describe his instrument and the first to use the term “vital capacity” to designate the maximum amount of air an individual can exhale after a maximal inhalation. Although he is remembered as the inventor of the spirometer, he was not the first person to use a gasometer to measure lung volumes nor was he the first to measure the vital capacity. What made his research different from those that came before him was partly the prodigious number of individuals whose vital capacity he measured but far more importantly that he was able to show a clear relationship between standing height, age and vital capacity which had not been previously apparent. This finding galvanized researchers in England, Europe and the United States and in many ways helped set the course of research into lung function for many decades to come.

This clear relationship between standing height and vital capacity has been taken as scientific fact since that time despite inconsistencies not only in Hutchinson’s data but in almost all population studies since that time. The problem is that the relationship between standing height and vital capacity is not precise but only approximate. In order to explain the range of results that appeared in his data Hutchinson and other researchers of his time divided their study population into groups by their occupation. This approach may appear to be quaint to us now but at the time they were very serious both about the utility of doing this and what it told them about the different classes of society.

The first studies on vital capacity that divided the population by race were done in the United States. The reasons that this was done are both simple and complex, and overall there’s not a lot we can look back and be proud of. At that time there was an overwhelming societal concern with the races in general and not only the recently freed black slaves and the Amerindians but also about the different “races” of Europe that were emigrating to the United States. There was much public talk and private thought about the concepts of racial degeneracy, racial mongrelization and racial vitality, and unfortunately the vital capacity was taken as a way of measuring these things. Despite incredibly significant errors in both the methods and conclusions of these studies this approach spread to Europe during the second half of the 19th century and dividing study populations by race has become standard practice ever since.

When I first started doing pulmonary function testing I was taught to decrease the predicted vital capacity by 15% for Blacks and 10% for Asians. Decades later ethnicity-based population studies replaced these fractions. I always took this as the correct way to approach predicted values (and it is embedded in the ATS/ERS standards) but at the same time I’ve always had patients where it was either difficult to assign ethnicity or where their results significantly exceeded their ethnicity-based reference values. Over the last several years I have had the opportunity to study the issues surrounding reference equations extensively and I have become somewhat disenchanted with the notion of ethnicity-based reference equations.

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Assessing MVV results

The Maximum Voluntary Ventilation (MVV) test was initially described in 1933. It was the first pulmonary function test that involved inspiratory and expiratory air flow in a significant way and for this reason it helped to set the stage both conceptually and technically for the FEV1, the FEV1/FVC ratio and our present understanding of obstructive lung diseases. MVV is reduced in a variety of conditions, including obstructive, restrictive and neuromuscular diseases, but a reduced MVV is non-specific and this limits its clinical utility. Nevertheless, it continues to be performed both in clinical labs and for research, and for this reason it would seem to be a good idea to know how to assess MVV results.

As usual, there are two aspects to assessing pulmonary function results; test performance and normal values.

Currently the ATS/ERS statement on spirometry contains the only available standard for performing the MVV test. Unfortunately this standard also contains some significant flaws. Its primary recommendation is that the MVV test be performed with a tidal volume that is approximately 50% of the forced vital capacity and a breathing frequency of around 90 breaths per minute. These recommended values are problematic and some simple mathematics will show why.

A respiratory rate of 90 BPM means that there is 2/3 of a second for both inhalation and exhalation. With a 1:1 ratio for inspiration and expiration, there is only 1/3 of a second for exhalation. Since it normally takes a full second to exhale approximately 75% of the vital capacity (i.e. the FEV1), 1/3 of a second would only allow time to exhale 25% of the vital capacity (not exactly true of course, but it helps prove the point). How then is it possible to exhale 50% of the vital capacity, twice that amount, in the same amount of time? The answer is that it isn’t and if it was somehow possible for somebody to actually meet the ATS/ERS recommended values they would have an MVV that would be 45% to 100% higher than any of the predicted MVV’s. I suspect the ATS/ERS agrees this is a problem since following the initial recommendation it also says that “… since there are little data on MVV acceptability criteria, no specific breathing frequency or volume is required”.

The fact is that no single tidal volume recommendation is going to work for all patients and this is because the MVV tidal volume has to reside mostly within the maximal flow-volume loop envelope.

MVV_TV_FVL_01

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