Author: Richard Johnston

  • Oscillometry

    A month or two ago in the AARC Diagnostics forum several members noted that their labs had acquired Impulse Oscillometry systems a number of years ago but that their physicians had since stopped ordering oscillometry tests, mostly because nobody understood what it was measuring and didn’t know how to interpret the results. There are a number of reasons why this is probably not an uncommon scenario and why, despite being first described in 1956, oscillometry is not used more widely.

    But first, what is oscillometry, and what’s the best way to understand it?

    Oscillometry refers to a closely related group of techniques for measuring respiratory impedance by superimposing small pressure waves on top of normal tidal breathing.

    There are three main approaches: the Forced Oscillation Technique (FOT), which is sometimes used a blanket term for all oscillometry techniques but more often refers to a single frequency technique, Impulse Oscillometry (IOS) and Pseudo-Random Noise (PRN). Most commercial oscillometry systems use either PRN or IOS because each approach uses multiple oscillation frequencies more or less simultaneously which allows testing to performed relatively quickly. The mono-frequency technique is used mostly in research because although it is slow to scan all frequencies, it is able to resolve rapid changes occurring at a single frequency.

    All techniques share a similar equipment configuration:

    The oscillatory pressure is usually generated by a loudspeaker, although the actual waveform and the frequency it produces differ for each technique. The peak pressures are usually on the order of +/- 1 to 5 cm H2O (+/- 0.1 to 0.5 kPa). Because patients have to breathe during testing, the system provides a steady flow of fresh air in one manner or another but this has to include a low pass filter of some kind so that the pressure waveform is not significantly diverted or blunted. The key measurements are flow and the pressure at the mouth.

    Oscillometry measures the impedance of the respiratory system, which is usually denoted as Zrs. Respiratory impedance has two components; resistance (Rrs) and reactance (Xrs). Reactance itself has two frequency-dependent components, capacitance and intertance.

    Resistance more or less follows a standard formula:

    But this is also where it starts to get interesting (and complicated). When pressure is applied to the airway, there are two different ways that gas flow responds. This first is termed ‘capacitance’ and is primarily dependent on the elasticity the airways. To be clear, capacitance is not the same thing as compliance and this is one point where the oscillometric model of lung physiology diverges significantly from the traditional model.

    When capacitance predominates airflow increases most rapidly at the beginning of the pressure change. As pressure continues to increase however, the rate of airflow actually decreases. A way to think about this is that the airways are acting like a spring. A spring has the least resistance to force when it is fully extended (relaxed) but its resistance increases as it is compressed.

    So when a pressure is applied, flow is highest at the beginning and decreases over time.

    What this means is that for capacitance, the flow waveform leads the pressure waveform.

    The second effect is termed ‘inertance’, and is primarily due to the inertia of air and the respiratory system. When inertance predominates airflow increases slowly at the beginning of a pressure change and becomes more rapid while the pressure continues. A way to think about this is that air is acting like a weight. A weight has the most resistance to force when it starts to move but its resistance decreases as its speed increases.

    So when a pressure is applied, flow is lowest at the beginning and increases over time.

    What this means is that for inertance, the flow waveform follows the pressure waveform.

    Together, capacitance and inertance are the components that make up reactance, but how much each contributes to the total amount of reactance depends on the oscillation frequency. At low frequencies (very approximately 2 to 10 hz) capacitance effects tend to predominate. At high frequencies (very approximately 10 to 30 hz) inertance effects tend to predominate. By comparing the phase of the flow and pressure waveform (i.e. which leads and which lags), it is possible to determine which effect predominates. Very importantly, there is going to be a frequency where the capacitance and inertance effects are equal and this is going to be the resonant frequency (Fres).

    For mathematical reasons capacitance effects are reported as negative numbers and inertance as positive numbers, and they are also graphed that way. A typical airway resistance and reactance graph looks something like this:

    For both physiological and technical reasons oscillometry results are most often reported as the resistance and reactance at 5 hz (Rrs5, Xrs5), the resistance and reactance at 20 hz (Rrs20, Xrs20) and the resonant frequency (Fres), although the results from other frequencies can be reported as well.

    In addition, the area bounded by a line at 5hz up to the resonant frequency can be determined. This is a measure of the magnitude of the frequencies where the elastic properties of the lung dominates (capacitance) dominates over inertance, and is reported as AX. Linear regression analysis can also be performed on the resistance and reactance waveforms and the slope of resistance, and the zero intercepts of resistance and reactance (i.e. what the resistance or reactance would have been at 0 hz) reported as Rrs(0), Rrs(1) and Xrs(0). Of these, Rrs(0) can be considered to be an index of airway obstruction while Rrs(1) is associated with respiratory system non-homogeneity. Subtracting Rrs20 from Rrs5 (Rrs5-Rrs20) also gives an approximate slope and is a value that is reported relatively frequently. Finally conductance, the inverse of Rrs(0), can be reported as Grs(0).

    Although all oscillometry techniques produce similar results at least one study showed that IOS systematically produced produced a higher Rrs than did PRN and that the IOS Fres tended to be slightly higher than the PRN Fres.

    Research has shown that higher oscillation frequencies are reflected from the larger airways and that lower frequencies travel more peripherally before returning to the mouth. This is because capacitance is primarily a property of the smaller airways and inertance a property of the larger airways. Disorders that reduce the elasticity of the lung, which includes both fibrosis and hyperinflation, causes the low frequency reactance to increase (become more negative). When airway obstruction increases there tends to be characteristic changes in resistance and reactance. Specifically, the reactance waveform shifts downward (more negative) which in turn causes the resonant frequency to increase. At the same time overall resistance increases but more so at low frequencies than at high frequencies.

    Oscillometry is performed with the subject in a sitting position without crossed legs. The head and neck should be in a neutral or slightly extended position. The subject’s nose must be clipped and their hands need to firmly support their cheeks. Subjects should breathe quietly during testing and although some manufacturers claim that a test can be performed in as short as 8 seconds, tests more commonly last between 30 and 45 seconds. The reported impedence results are usually an average of measurements made during the testing period.

    Software should reject individual measurements made during the transition from exhalation to inhalation or vice versa, since tidal flow is usually changing relatively rapidly at these times and this reduces the accuracy of superimposed pressure and flow waveform measurements. In addition, poor cheek support, leaks or artifacts like swallowing, glottis closure and tongue movement will also reduce measurement accuracy. For this reason Coherance, which is a value that reflects the reproducibility of the impedance measurements, should also be reported. A Coherance value <0.8 cm H2O at 5 hz or <0.9 cm H2O at 20 hz is an indication of suboptimal test quality.

    The ability of oscillometry to distinguish between different lung disorders is the first area where some of its limitations start to appear. Specifically, there isn’t a significant difference in oscillometry results between interstitial lung diseases (ILD) and obstructive lung disease. In addition although there are differences between asthma and COPD, these tend to be subtle and are more associated with the severity of airway obstruction than with any specific differences between the two.

    For both ILD’s and OVD’s the Rrs5, AX and Fres tend to be elevated and Xrs 5 decreased (more negative). One minor difference is that Rrs20 tends to be fairly normal in subjects with ILD but elevated in those with OVD. Nevertheless, oscillometry results for ILD overlap significantly with those of airway obstruction. This doesn’t mean that oscillometry can’t be used to monitor changes in subject with ILD over time, but there is little to differentiate ILD’s from OVD’s and for this reason oscillometry seems better suited for characterizing obstructive lung disorders than restrictive.

    Oscillometry has probably been studied with asthma more often than any other lung disorder. Post-bronchodilator changes in oscillometry have been studied by numerous researchers and decreases in Rrs5 of between 30% and 40%, or an increase in Xrs5 of between 30% and 35% have been found to be significant. One study showed that showed an increase in Grs(0) of 10% correlated with an increase in FEV1 of 10%. Despite these findings however, there is no consensus as to what constitutes a positive bronchodilator response by oscillometry at this time.

    Bronchoconstriction has also been studied by numerous researchers. Not surprisingly studies have shown that Rrs5, AX and Fres increased and Xrs5 decreased (became more negative) during exercise-induced bronchoconstriction. Another study showed that an increase of 50% in Rrs5 following hyperventilation bronchoprovocation correlated with a 20% decrease in FEV1.

    In COPD, the magnitude of the changes in Fres, Rrs5, Rrs20, Xrs5 and AX tends to correlate well with GOLD1-GOLD4 severity.

    Modified from DiMango AMGT, Lopes AJ, Jansen JM, Melo PL. Changes in respiratory mechanics with increasing degrees of airway obstruction in COPD: detection by forced oscillation technique. Respir Med 2006; 100: page 403.

    When compared to asthma, patients with COPD tended to show a greater increase in Rrs5, particularly compared to Rrs20, and for this reason the Rrs5-Rrs20 is often more elevated in COPD.

    In one study of obesity subjects showed the Rrs5, Rrs20 and Fres were increased significantly and Xrs5 was significantly decreased compared to subjects with normal body weight and that these changes tended to correlate with BMI. There were similar decreases in the same population in FVC and FEV1, also correlating with BMI (although they remained WNL) however the FEV1/FVC ratio did not change significantly.

    Since oscillometry measurements are made relatively quickly and frequently during tidal breathing it is also possible to report resistance, reactance and the resonant frequency for both inspiration and expiration. This can be useful since several studies have shown that individuals with normal lungs have relatively little difference in Rrs5 and Xrs5 between inspiration and expiration, but those with airway obstruction such as COPD tend to show a significantly greater Rrs5 during expiration than during inspiration. Interestingly, one study showed that although Rrs5-Rrs20 was higher in subject with ILD than normal subjects, there was little difference between inspiration and expiration while subjects with asthma and COPD had relatively large changes in Rrs5-Rrs20 between inspiration and expiration.

    Since oscillometry is frequently performed on children (there are probably more oscillometry research papers on children than adults) it’s important to note that there are a number of important differences that are present between children of the same age and changes that occur as children age. Specifically, numerous studies have shown that Rrs5, Rrs20 and Fres decrease and that Xrs5 increases (becomes less negative) with increasing height. The same set of changes (Rrs5, Rrs20 and Fres decrease and Xrs5 increases) with increasing age. This is most likely due to the normal increase in airway diameter and lung volume with increasing height and age.

    So why isn’t oscillometry used more frequently?

    One of the major reasons that oscillometry can be difficult to understand and this is because the terminology and underlying concepts of oscillometry are usually presented in the same terms as those that are used in electrical engineering. This is not accidental since the physical responses of the respiratory system to oscillation matches the equations that describe simple electrical circuits. On the plus side, this type of circuitry is well understood and this means that there are many mathematical tools available for analyzing test data. On the minus side however, these equations require a relatively advanced knowledge of mathematics and although the underlying physiological concepts can be easily modeled in terms of resistors, capacitors and inductors, they do not map at all well onto the standard concepts and terminology of pulmonary physiology.

    Note: I’d also have to say that those who actually do understand the mathematics and concepts of oscillometry have done exceedingly little to bridge the gap with those that don’t. As an example I was reading a monograph on oscillometry which ostensibly was intended as a basic primer on the subject and equation sets like this:

    were presented throughout, but without any explanation whatsoever of the terms used or what they or the equation represented. The obvious presumption was that you already had to understand the math in order to understand the math!

    I will also mention that because the Xrs at low frequencies is negative discussions of changes in Xrs can be somewhat confusing. Too often authors interchangeably use increase and decrease to mean the same thing (i.e. that Xrs has become more negative) and this makes it necessary to read study results carefully.

    There is also the fact that there is only fair correlation at best between traditional pulmonary function tests and values obtained from oscillometry. Research has shown there are occasionally statistically significant associations between certain oscillometry values and values such as FEV1, PEF, TLC and DLCO but this shouldn’t be taken to mean there is a correlation. Given the fact that oscillometry and spirometry are measuring completely different things this shouldn’t be surprising, but it has been an additional barrier against acceptance.

    There are also a limited number of reference equations and the differences in predicted values are occasionally large. One study of oscillometry that derived reference equations from an elderly population compared its results to the reference equations from a couple prior studies and found up to a 29% difference in Rrs5, up to a 33% difference in Rrs20 and up to a 76% difference in Xrs5. Since numerous studies compare their results to predicted values this opens the interpretation of their results to question.

    Much of the interpretation of oscillometry results, particularly when differentiating between different lung disorders, relies less on predicted values and more on the patterns of resistance and reactance. These patterns are occasionally distinct, but recognizing them requires practice and they are hard to pin down from reference equations alone. An additional limiting factor is that the diagnostic ability of oscillometry is questionable due to the overlap between diseases like ILD, COPD and asthma. This probably makes oscillometry better suited to monitoring changes over time, in particular for assessing bronchodilation and bronchoconstriction even though there is no clear consensus as to what constitutes a significant change.

    I also have some concerns about the measurements associated with oscillometry. Although values like Rrs5, Rrs20 and Xrs5 do seem to reflect their specific parts of the Rrs and Xrs spectrums, they are arbitrary choices. I’ve seen no research that indicates that the values from these specific frequencies are in any way optimum. In addition, linear regression is used to analyze the slope and intercept of the Rrs and Xrs frequency spectrums but since these spectrums are usually curves, how accurate, reproducible and meaningful are Rrs(0), Rrs(1) and Xrs(0)?

    Finally, although it is possible to calibrate the flow and pressure sensors of a given oscillometry system results from oscillometry systems are highly dependent on the software used to analyze the raw data. The 2003 ERS recommendations for oscillometry includes some suggestions for software algorithms but it’s not possible to determine whether or not these are actually followed, and depending on the technology being used, even whether it is even appropriate to do so. I’m not suggesting that oscillometry systems are inaccurate, since it’s my experience that most manufacturers try to design systems that produce accurate measurements, but at the same time there are no real standards for assessing oscillometer accuracy. For these reasons I think it past time that the 2003 ERS recommendations were updated.

    The main advantages of oscillometry is that little patient cooperation, other than the ability to breathe on a mouthpiece with a noseclip, is needed (and even then it has also been adapted for use in intubated patients receiving mechanical ventilation). This means that measurements can be made on any individual that might have difficulty with traditional tests, which in particular includes children, but also adults that are otherwise unable to perform spirometry or are medically contraindicated from doing so.

    Spirometry and oscillometry each have their own strengths and weaknesses. There are indications that oscillometry may be more sensitive to the smaller, more peripheral airways than spirometry. There are indications that because inhalation to TLC can reverse bronchoconstriction oscillometry may be superior to spirometry for challenge testing. Oscillometry’s primary utility however, appears to lie mostly in its ability to obtain clinically useful measurements from individuals that are otherwise unable to perform routine spirometry. Oscillometry isn’t a replacement for spirometry but it can still be a useful adjunct.

    References:

    de Albuquerque CG, de Andrade FMD, de Almeida Rocha MA, de Oliviera AFF, Ladosky A, Victor EG, Rizzo Ja. Determining respiratory system resistance by impulse oscillometry in obese individuals. J Bras Pneumol 2015; 41(55): 422-426

    de Assumpcion MS, Goncalves RM, Martins R, Bobbio TG, Schivinski CIS. Reference equations for impulse oscillomtry system parameters for in healthy Brazilian children and adolescents. Respir Care 2016; 61(8): 1090-1099.

    Baswa S, Diong B, Nazeran H, Goldman M. Respiratory system models based on parameter estimates from impulse oscillometry data. Proceedings of the 2005 IEEE, Engineering in medicine and biology, 27th annual conference. Pages 2958-2961.

    Bickel S, Popler J, Lesnick B, Eid N. Impulse oscillometry. Interpretation and practical applications. Chest 2014; 146(3): 841-847.

    Bikov A, Pride, NB, Goldman MD, Hull JH, Horvath I, Barnes PJ, Usmani OS, Paredi P. Glottal aperature and buccal airflow leaks critically affect forced oscillometry measurements. Chest 2015; 148(3): 731-738.

    Brashier B, Salvi S. Measuring lung function using sound waves: role of the forced oscillation technique and impulse oscillometry system. Breathe 2015; 11(1): 57-65.

    Crim C, Celli B, Edwards LD, Wouters E, Coxson HO, Tal-Singer R, Calverly PMA. Respiratory system impedance with impulse oscillometry in healthy and COPD subjects: ECLIPSE baseline results. Respir Med 2011; 105: 1069-1078.

    DiMango AMGT, Lopes AJ, Jansen JM, Melo PL. Changes in respiratory mechanics with increasing degrees of airway obstruciton in COPD: detection by forced oscillation technique. Respir Med 2006; 100: 399-410.

    Evans TM, Rundell KW, Beck KC, Levine AM, Baumann JM. Airway narrowing measured by spirometry and impulse oscillomtry following room temperature and cold temperature exercise. Chest 2005; 128(4): 2412-2419.

    Galetke W, Randerath WJ, Feler C, Muth T, Borsch-Galetke E. Esophageal pressure method and impulse oscillometry to assess mechanical properties of the respiratory system in health men. Med Sci Monit 2009; 15(8): CR429-435.

    Grimby G, Takishima T, Graham W, Macklem P, Mead J. Frequency dependence of flow resistance in patients with obstructive lung disease. J Clin Invest 1968; 47(6): 1455-1465.

    Guan WJ, Yuan JJ, Gao YH, Li HM, Zheng JP, Chen RC, Zhong NS. Impulse oscillometry and spirometry small airway parameters in mild to moderate bronchiectasis. Respir Care 2016; 61(11): 1513-1522.

    Hellinckx J, Cauberghs M, De Boeck K, Demedts M. Evaluation of impulse oscillation system: comparison with forced oscillation technique and body plethysmography. Eur Respir J 2001; 18: 564-570.

    Houghton CM, Woodcock AA, Singh D. A comparison of plethysmography, spirometry and oscillometry for assessing the pulmonary effects of inhaled ipratropium bromide in health subjects and patients with asthma. Brit J Clin Pharmacol 2004; 59(2): 152-159.

    Kolsum U, Borrill Z, Roy K, Starkey C, Vestbo J, Houghton C, Singh D. Impulse oscillometry in COPD: identification of measurements related to airway obstruction, airway conductance and lung volumes. Respir Med 2009; 103: 136-143.

    Mansur AH, Manney S, Ayres JG. Methacoline-induced asthma symptoms correlate with impulse oscillometry but not spirometry. Respir Med 2008; 102: 42-49.

    van Noord JA, Clement J, Cauberghs M, Mertens I, Van de Woestijne KP, Demedts M. Total respiratory resistance and reactance in patients with diffuse interstitial lung disease. Eur Respir J 1989; 2: 846-852.

    Ohishi J, Kurosawa H, Ogawa H, Irokawa T, Hida W, Kohzuki M. Application of impulse oscillomtry for within-breath analysis in patients with chronic obstructive pulmonary disease: pilot study. BMJ Open 2011; 2: e000184.

    Oostveen E, MacLeod D, Lorino H, Farre R, Hantos Z, Desager K, Marchal F. ERS Task Force. The forced oscillation technique in clinical practice: methodology, recommendations and future developments. Eur Respir J 2003; 22: 1026-1041.

    Oostveen R, Boda K, van der Grinten CPM, James AL, Young S, Nieland H, Hantos Z. Respiratory impedance in healthy subjects: baseline values and bronchodilator response. Eur Respir J 2013; 42: 1513-1521

    Pasker HG, Schepers R, Clement J, van de Woestijne KP. Total respiratory impedance measured by means of the forced oscillation technique in subjects with and without respiratory complaints. Eur Respir J 1996; 9: 131-139.

    Schulz H, Flexeder C, Behr J, Heier M, Holle R, Huber RM, Jorres RA, Nowak A, Peters D, Wichmann HE, Heinrich J, Karrasch S. Reference values for impulse oscillometric lung function indices in adults of advanced age. PlosOne 8(5): e63366.

    Smith HJ, Reinhold P, Goldman MD. Forced oscillation technique and impulse oscillometry. Eur Respir Mon 2005; 31: 72-105

    Sugiyama A, Hattori N, Haruta Y, Nakamura I, Nakagawa M, Miyamoto S, Onari Y, Iwamoto H, Ishikawa N, Fujitaka K, Murai H, Kohno N. Characteristics of inspiratory reactance in interstitial lung disease. Respir Med 2013; 107: 875-882.

    Zerah F, Lorino AM, Lorino H, Harf A, Macquin-Mavier I. Forced oscillation technique vs spirometry to assess bronchodilation with asthma and COPD. Chest 1995; 108: 41-47

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

  • Eye was fooled

    A couple of days ago I was reviewing (triaging, actually) the spirometry portion of a full panel of PFTs performed with pretty terrible test quality and was trying to decide if the technician responsible for performing the tests had made the right selections from the patient’s test results. I noticed that the FEV1 that had been selected was actually the lowest FEV1 from the all the spirometry efforts the patient made, and was trying to decide whether this was really the correct choice. We use peak flow to help determine which FEV1 to select and that particular spirometry effort appeared to have the highest and sharpest peak flow by a large margin:

    particularly when compared to the other spirometry efforts:

    But this was hard to reconcile given how low the FEV1 was relative to the others:

    Test #1 Test #2 Test #3
    Observed: %Predicted: Observed: %Predicted: Observed: %Predicted:
    FVC (L): 1.71 41% 2.46 59% 2.39 58%
    FEV1 (L): 1.24 39% 1.81 57% 1.77 55%
    FEV1/FVC: 73 95% 74 96% 74 97%

    All of the other efforts though, had significant quality issues that might cause the FEV1 to be overestimated. Effort #2 had a large amount of back-extrapolation (0.32 L, 13% of FVC). Effort #3 also had a lot of back-extrapolation (0.28 L, 12% of FVC) and it also had a blunted peak flow that was substantially lower than the other efforts. Or did it?

    I was looking across all the numerical peak flow results and suddenly noticed that the first effort, the one that appeared to have the highest peak flow, actually had the very lowest.

    Test #1 Test #2 Test #3
    Observed: %Predicted: Observed: %Predicted: Observed: %Predicted:
    PEF (L/sec): 1.79 21% 3.66 0.44 2.64 0.32

    So what was going on here?

    As I said, the patient’s test quality was pretty poor and when I looked at the volume-time curve I saw what the problem was.

    The patient had actually made two back-to-back efforts. The numerical values (FVC, FEV1 and PEF) were reported from the first effort. The second effort however, was what produced the flow-volume loop with the highest peak flow. The smaller loop that was inside the maximal loop (which I had taken to be one of the tidal loops and ignored) was actually the first effort.

    So, both the technician and I had been fooled by looking at the first effort’s flow-volume loop and taking it at face value. It was obvious that the first spirometry effort had the highest peak flow so the FEV1 from that effort had to be the best and most accurate one, didn’t it? Well actually, no, it didn’t, particularly since we weren’t looking at the right flow-volume loop.

    To some extent I blame our lab’s software for this problem. The traces that make up the flow-volume loop are presented in one color with no differentiation between the pre-test tidal loops, the test effort itself, and whatever comes after the test effort. Oftentimes towards the end of an exhalation, the tracings from the tidal loops and the actual spirometry effort frequently overlap and there have been many times when I have wished that the tidal loops were in a different color in order to make it clear which tracing was which (particularly when I’m trying to determine whether the spirometry effort ended at a volume lower than where it started). This particular problem makes it clear that the tracing color should also be different once the end of a spirometry effort has occurred. Maybe if it looked something like this:

    then it would be clear which part of the flow-volume loop was which.

    I ended up selecting effort #2 to be reported, partly because it had the largest FVC (and longest expiratory time), partly because it had the best PEF and partly because even if the FEV1 was overestimated because of of back-extrapolation, it was still more believable than the FEV1’s from all the other efforts. I also think this was a better choice since if the FEV1 from the first effort had been reported it would have looked like the patient had airway obstruction on top of his restriction (the TLC was moderately reduced) and I just don’t think that was correct.

    The fact that I was trying to salvage something out of this patient’s tests results re-raises the question of when results should be reported and when they shouldn’t. You could say that if none of the tests meet the ATS/ERS standards then none of them should be reported and that argument could be made for this patient’s spirometry efforts since none of the spirometry efforts met all of the ATS/ERS standards. The problem with taking this approach is that the ATS/ERS spirometry standards have loopholes. In particular you can take the FEV1 from one effort and the FVC from another. If this was done then the FEV1 from the first effort would have been reported since it was the only one that had essentially no back-extrapolation (0.05 L) and the ATS/ERS standards do not use PEF in any way when selecting FEV1. The effort the FVC would have been taken from was longer than 6 seconds and also met the end-of-test criteria. For these reasons it could be said that the results derived in this way would have met the ATS/ERS standard even though it’s also apparent that the test quality wasn’t particularly good and that the results probably wouldn’t reflect the patient’s status.

    There’s also the point that even when test results don’t meet all of the ATS/ERS criteria, they can still answer some questions. For example if a spirometry effort was only 1-1/2 seconds long but the FEV1 was normal, then that makes it reasonably unlikely that there is any airway obstruction even if the FVC is significantly underestimated. I’d say that’s a reason to still report the results. Ditto if the FVC was above the LLN but the FEV1 was mis-estimated due to an expiratory pause or back-extrapolation.

    For this patient test quality and reproducibility was poor, but there were still bits and pieces that were able to present a somewhat coherent picture and for this reason (after some editing) I put the report in my out basket.

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  • PFTs on YouTube

    A friend recently sent me the links to several YouTube videos on pulmonary function testing. I’ve spent some time off and on over the last year looking at YouTube videos and in particular I’ve been looking for ones that can be used as part of technician education. Maybe I’ve set the bar too high but all too often I’ve been disappointed and frustrated with what I’ve found. One reason for this is that many videos are aimed at other audiences than technicians (i.e. medical students, physicians, patients). Another reason is that too often only simple concepts are presented, often in rote fashion and often without good visual explanations (c’mon, these are videos after all, not podcasts). A final reason is that sometimes they’re outdated, misleading or just plain wrong.

    Still, even the flawed videos can be useful. Sometimes this is because they occasionally explain some concepts well; sometimes despite being simplistic they present a good overview; and sometimes because their mistakes can serve as points for discussion. I’ve tried to select videos that have at least some potential for use in technician education.

    John B. West Respiratory Physiology Lectures

    Based primarily on his classic textbook, ‘Respiratory Physiology’ (which should be on everybody’s bookshelf). Not 100% perfect but this is what many of the other videos should aspire to be. Many complex concepts explained using simple examples. Lots of interesting pictures and illustrations. Should be part of every technician’s education.

    1. Structure and Function
    2. Ventilation
    3. Blood Gas Transport
    4. Acid-Base Balance
    5. Diffusion
    6. Pulmonary Blood Flow
    7. Pulmonary Gas Exchange, Part 1
    8. Pulmonary Gas Exchange, Part 2
    9. Mechanics of Breathing, Part 1
    10. Mechanics of Breathing, Part 2
    11. Control of Ventilation
    12. Defense Systems of the Lung
    13. Respiration under Stress
    14. Respiration at the Limit

    Allan Prost

    A series of casual video lectures on pulmonary function testing. Some are flawed by shaky camera handling and poor audio. The PFT test videos cover a lot of the basic material needed for good testing. They’re light on physiology but an adequate starting point for demonstrating test maneuvers to new technicians. All tests are performed using MedGraphics equipment. The product introductions are adequate for orienting a tech to new equipment.

    PFT Tests:

    1. Slow Vital Capacity
    2. Forced Vital Capacity
    3. DLCO Single Breath
    4. MVV
    5. N2 washout
    6. Single Breath N2 washout
    7. Plethysmography

    Product Introductions:

    MedCram PFT

    I found this series of lectures frustrating. Using animated slides they explained some important concepts with simple and clear examples. Having said that, it was flawed because a fair amount of the information presented was outdated and occasionally even incorrect. The interpretation algorithm was particularly quirky. I felt that if this was presented in 1980 it would have been considered state of the art but there’s been a lot of water under the bridge since then.

     Intro to the PFT Lab

    1. Introduction to PFTs
    2. Concepts
    3. Flow-Volume Loops
    4. Lung volumes
    5. DLCO
    6. Interpretation, part 1
    7. Interpretation, part 2

    Strong Medicine

    Essentially a PowerPoint slideshow with voiceover. More current than MedCram but flawed because the narrator often just read the slides and basic concepts were often poorly explained. Did a good job of following the spirit of the ATS/ERS interpretation algorithm.

    Note: For reasons that are unclear this set of videos appears several times from different sources. Strong Medicine however, is dated earlier than the others and for this reason receives the credit for them here.

    1. Introduction
    2. Spirometry
    3. Lung volumes
    4. DLCO
    5. Summary and practice cases

    Peter Sloane MD.

    Series on Pulmonary Function Interpretation using animated slides. Most concepts presented in rote fashion using text and voiceover with either no or an inadequate visual explanation of underlying physiology or techniques. Complex issues were occasionally presented but often jumped through much too quickly. Almost no explanation of testing errors except very quickly when discussing interpretation pitfalls. Voiceover too often read from the slides. Still covered all the basics though.

    1. Definitions, interpretation of spirometry and flow-volume loops.
    2. Lung volumes and diffusion capacity
    3. Pitfalls in interpretation / common patterns
    4. Practice questions & explanations

    TTUHSCtv

    PowerPoint slideshow of text and flow-volume loops with voiceover. Detailed review of reports but approach to interpretation is outdated and does not follow current ATS/ERS guideline. Some incorrect information.

    1. PFT Interpretation part 1 (normal)
    2. PFT Interpretation part 2 (obstruction)
    3. PFT Interpretation part 3 (restriction)

    Khanacademymedicine

    Videoed drawings with voiceover. Khan Academy has a large number of videos on physiology and anatomy presented by different lecturers. Concepts are presented a bit simplistically but clearly and thoroughly, nonetheless.

    professorfink

    Numerous classroom physiology lectures. Video using an overhead projector with text and diagrams. Basic, college-level A&P that’s better than average.

    Arzoo Sadiqi

    Overhead shots of drawings with voiceover. Quick overview of physiology that was somewhat superficial but material was otherwise mostly correct.

    ERS Education

    I included because it’s from the European Respiratory Society. Disappointing considering the source but a banner indicates this was a demo so it’s an edited version (full version is behind the ERS paywall). A quick overview of spirometry with peculiar and poorly explained volume-time curves. Various flow-volume were shown and labeled but with no explanation about their contour. An explanation of patient prep was cut off before showing an actual spirometry test.

    CompleWare

    Showed the spirometry procedure with spirometer calibration, patient explanation and test performance. Quickly explained criteria for an acceptable quality test with some examples. Hit all the high points but there was little in the way of detailed explanations and it went through its material very quickly.

    Morgan Scientific

    Training videos on how to perform tests using various Morgan Scientific test systems. All are professionally produced and many of the subjects covered are applicable to other manufacturer’s equipment.

    Carefusion

    Professionally produced training videos but highly oriented towards the Vyntus system. Surprisingly, other than sales pitches I was unable to find videos of any other Carefusion PFT equipment.

    1. Vyntus Spiro hardware review and set up
    2. Vyntus Spiro calibration
    3. Vyntus Spiro FVC Measurement
    4. Vyntus Spiro Review and Reporting

    MGC Diagnostics

    Training videos. Casual format. Surprisingly, other than sales pitches I was unable to find videos of any other MGC Diagnostics PFT equipment (at least from MGC Diagnostics).

    NDD

    Training videos. A mixture of casual lectures and animation. Professionally produced, although some are better than others.

    CPUSB Human Performance Lab

    A series of casual video lectures, with slides, on calibrating and using various systems. Shaky video. Covers the basics for specific systems.

    Allan Dunphy

    Classroom lectures. Sometimes shaky video. Covers the basics.

    NHSWestminster

    Spirometry (SVC and FVC) with a patient is demonstrated. Video with slides. Includes patient questions, explanations to patient, test procedure.

    MisteryGanz

    Video of equations and graphics being written on paper. Covers a complex series of equations and concepts but explanations are limited and some concepts are missing. No discussion of testing issues and errors.

    Darren Roesch

    Video of equations and graphics being highlighted on paper. Covers a complex series of equations and concepts but explanations are limited and some concepts are missing. No discussion of testing issues and errors.

    Deb Akers

    Casual lecture showing how to calibrate VMax gas analyzers. Shaky video but covers the subject.

    VC Respiratory

    Shows basic calibration procedure of an electronic spirometer. Shaky video and poor audio but shows the basics.

    ♦     ♦     ♦     ♦

    There are an awful lot of videos I haven’t included. Too many people seem to think that going through the motions of performing a PFT of one kind or another in front of a camera, without any particular explanation of anatomy, physiology, gas laws or technical details of the test, somehow makes an acceptable video (although in some instances this is probably okay for patient-oriented videos).

    There are also too many videos about pulmonary function testing created by individuals who seem to have read a few textbooks and then feel qualified to (superficially) teach the subject. Too few videos are created by individuals with hands-on experience and what’s most often missing is any significant discussion of technical details, potential testing errors and their effects on results. I was particularly disappointed that all of the videos that purported to teach interpretation almost universally did so using 80% of predicted as the LLN and used the GOLD FEV1/FVC ratio criteria. I found nothing discussing the LLN or Z score.  

    There there also were many reasonably good videos that touched on pulmonary anatomy and physiology but I had to draw the line somewhere so I settled for ones that in my opinion seemed most relevant to educating pulmonary function technicians.

    Watching all these videos has made me think about what should be part of a technician’s education, however. This list is certainly open to discussion but I think that a curriculum needs to include following topics:

    Gases.

    Gas laws. Aerodynamics. Turbulence. Molecular diffusion. BTPS/STPD/ATPD. Partial pressures. Barometric pressure. Viscosity. Solubility. Temperature.

    Anatomy

    Upper airway (larynx and pharynx). Airway anatomy including stucture of airway wall, acinus and alveoli. Thorax including ribcage, diaphragm and pleura. Arterial and venous circulation.

    Physiology

    Compliance. Pressure-volume. Equal pressure point. Cardiac output. Fick’s law. A-a gradient. Dead space. Vd/Vt. Qs/Qt.

    Test system technology.

    Volume displacement spirometers. Flow sensors (pneumotachs, hot-wire anemometers, turbines, ultrasonics). Transducers and A-D conversion. Gas analyzers. Flow-volume loops. Plethysmographs. Helium dilution FRC. N2 washout FRC. Single Breath N2 washout. Oximeters.

    ATS/ERS/ACCP/OSHA standards

    Spirometry. Lung volumes. DLCO. 6MWT. Methacholine challenge. MIP/MEP. CPET. DLNO.

    Test quality

    Back extrapolation. Expiratory time. Plateaus. Leaks. Hesitations and coughs. Calibration. Biological QC. Levey-Jennings charts.

    Lung diseases

    Asthma. COPD. Bronchitis. Bronchiectasis. Cystic Fibrosis. Pulmonary fibrosis. Sarcoidosis. ALS. Tracheomalacia.

    Interpretation

    ATS/ERS algorithm. Reference equations. LLN and ULN. Z score.

    Patient relations

    Mouthpieces. Noseclips. Hygiene. Explaining tests. What to do when things go wrong.

    There are a lot of subjects here for which there are no corresponding videos (or at least none that I’d recommend). If anybody has aspirations of producing their own YouTube videos on pulmonary function testing – please!!! No more spirometry videos, or if you must at least tackle some of the technical details. Instead choose one of these subjects that hasn’t already been covered.

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

  • Z Score to remember is -1.645

    The use of Z scores to report PFT results, both clinically and for research is occurring more and more frequently. Both the Z score and the Lower Limit of Normal (LLN) come from the same roots and in that sense can be said to be saying much the same thing. The difference between the two however, is in the emphasis each places on how results are analyzed. The LLN primarily emphasizes only whether a result is normal or abnormal. The Z score is instead a description of how far a result is from the mean value and therefore emphasizes the probability that a result is normal or abnormal.

    Reference equations are developed from population studies and the measurements that come from these studies almost always fall into what’s called a normal distribution (also known as a bell-shaped curve).

    A normal distribution has two important properties: the mean value and the standard deviation. The mean value is essentially the average of the results while the standard deviation describes whether the distribution of results around the mean is narrow or broad.

    The simple definition of the Z score for a particular result is that it is the number of standard deviations that a result is away from the mean. It is calculated as:

    For mathematical reasons 68% of the results in a normal distribution fall within ±1 standard deviation from the mean and 95% of the results will fall within ±2 standard deviations from the mean (and 99.7% of results will fall within ±3 standard deviations). Although in some respects it is an arbitrary decision, research on many different biological processes has shown that the 5% of results that are 2 standard deviations away from the mean are usually abnormal. For this reason a Z-score of > ±2 means a specific result is probably abnormal.

    Elevated pulmonary function results are usually not considered abnormal however. This is because having an FVC or FEV1 that is abnormally high may be physiologically abnormal but clinically it is not. Pulmonary function results from the bottom 5% are therefore considered abnormal, not the bottom 2.5% and top 2.5%. Again for mathematical reasons, the bottom 5% of results will occur at a Z-score of -1.645 and strictly speaking the value represented by a Z-score of -1.645 and the LLN are the same thing.

    Obviously some care must be taken in selecting which results from a population study are analyzed for mean and standard deviation. If, for example, the spirometry results from both males and females were analyzed as one group this would of course affect both the mean and the standard deviation. The effect of this would likely be that more females who are clinically normal would be considered abnormal and more males who are clinically abnormal would be considered to be normal.

    For this reason the results from large population studies are divided into subgroups and each subgroup will have its own mean and standard deviation. This is also where reading the fine print is important since the decisions on how a study population is subdivided has significant implications on the statistical results.

    Subdividing by gender is relatively straightforward (although it should be remembered that depending on how you define it between 1 in 1000 and 1 in 2000 babies are born with intersex characteristics) but subdividing by ethnicity is much more difficult, particularly since there is no clear definition for ethnicity. There is also a limit on how far subdividing makes sense since depending on the value being measured and the size and composition of a subgroup results may no longer fit a normal distribution.

    But an opposite problem can occur when results aren’t subdivided enough. I am not a statistician but I am concerned when I see an LLN that is as an offset of the mean that was determined using the standard deviation from an entire group.

    The question is whether or not this is a problem for those individuals at the extremes of height or age. The answer depends on whether or not the results for the group are homoscedastic, that is whether or not the variance of the results show a homogeneous amount of variability across the range of results. Many of the more recent studies indicate that this is indeed the case, but I’m not sure that this type of distribution applies to all of the variables. For example, it’s relatively easy to believe that a homoscedastic distribution applies when the variable is age. But how about height?

    FVC and FEV1 change by at least a factor of two over the normal range of heights. If FEV1, for example was homoscedastically distributed by height:

    that would also imply that the range of normal values for a short individual with a small lung is proportionally larger than it is for a tall individual with a large lung. This just doesn’t seem correct and it is more likely that the range of normal values is relatively proportional to size of the lung.

    This type of problem is offset to a large extent by more complex statistical analysis. In particular the Lambda-Mu-Sigma method (LMS) which uses the “skewness” of the results (Lambda), the non-uniform distribution of the results (Mu) and the coefficient of variation for the results (Sigma) to produce Z scores which have been shown to be a better fit of clinical abnormalities than Z scores derived from simple multiple regression.

    Z-scores aren’t that hard. Use of the Z score can be made easier when the results are presented in an appropriately helpful manner. For example a graph like this:

    Graphic courtesy of Morgan Scientific

    can make it immediately clear what probability a given result has for being normal or abnormal.

    In the “bad old days” normal results were defined by being 80% of predicted or above. This most likely came about because 80%-60%-40% was an easy rule to remember for classifying results but was also completely arbitrary. The selection of the bottom 5% of the population as the LLN is certainly less arbitrary since it is grounded in biological research. The common practice however, is just to report the LLN next to the observed result and leave it up to the reviewer to eyeball the difference between the two. Remembering that a Z score of -1.645 is the LLN is not quite as easy to remember as 80% but including the Z score for a result has the ability to give a reviewer a sense of how “normal” or “abnormal” it actually is.

    For the time being the percent predicted will continue to be reported and this is so that severity can be assigned when results are below the LLN. At least one study has indicated that Z scores of -2, -2.5, -3 and -4 can be used for the same purpose but this has not yet become standard practice.

    One limitation of both Z scores and the LLN is that they are linked to a specific single population study. For this reason their actual value will depend on how a study population is subdivided, the quality of its statistical analysis and on the quality of the study population itself. But the same limitations also apply when using criteria like 80%-60%-40% to assess results.

    In general I think that it’s part of human nature to prefer simple answers and to only want to know whether a result is normal or abnormal but that requires thinking only in terms of black and white. Like it or not, the range between normal and abnormal involves shades of gray. The Z score makes these shades of gray clearer.

    References:

    Drummond MB, Hansel NN, Connett JE, Scanlon PD, Tashkin DP, Wise RA. Spirometric predictors of lung function decline and mortality in early chronic obstructive pulmonary disease. Amer J Respir Crit Care Med 2012; 185(12): 1301-1306.

    Fragoso CAV, Gill TM, McAvay G, Van Ness PH, Yaggi HK, Concato J. Use of Lambda-Mu-Sigma-Derived Z Score for evaluating respiratory impairment in middle-aged persons. Resp Care 2011; 56(11): 1771-1777.

    Stanojevic S, Wade A, Stocks J, Hankinson J, Coates AL, Pan H, Rosenthal M, Corey M, Lebecque, Cole TJ. Reference rages for spirometry across all ages. Amer J Respir Crit Care Med 2008; 177(3): 253-260.

    Quanjer PH, Pretto JJ, Brazzale DJ, Boros PW. Grading the severity of airways obstruction: new wine in old bottles. Eur Respir J 2014; 43(2): 505-512.

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

  • Contraindications

    A couple weeks ago I was asked whether it was safe for a patient with an abdominal aortic aneurysm (AAA) to have pulmonary function testing. My first thought was that it was probably unsafe but after a moment or two of thought I realized that I hadn’t reviewed the subject for a long time. When I checked the 2005 ATS/ERS general testing guidelines (there are no contraindications in the 2005 spirometry guidelines) I found that AAA wasn’t mentioned at all. In fact, the only absolute contraindication mentioned was that patients with a recent myocardial infarction (<1 month) should not be tested. Some relative contraindications were mentioned:

    • chest or abdominal pain
    • oral or facial pain
    • stress incontinence
    • dementia or confusional state

    and activities that should be avoided prior to testing include:

    • smoking within 1 hour of testing
    • consuming alcohol within 4 hours of testing
    • performing vigorous exercise within 30 minutes of testing
    • wearing clothing that restricts the chest or abdomen
    • eating a large meal with 2 hours of testing

    but these were factors where test results were likely to be suboptimal and not actually contraindications.

    This got me curious since I thought that pulmonary function testing was contraindicated for more conditions than just an MI. I reviewed the 1994 and and then the 1987 ATS statements on spirometry but again found no mention of contraindications. Ditto on the 1993 ERS statement on spirometry and lung volumes. Finally, in the 1996 AARC clinical guidelines for spirometry I found a much longer list of contraindications:

    • hemoptysis of unknown origin
    • pneumothorax
    • recent mycardial infarction
    • recent pulmonary embolus
    • thoracic, abdominal or cerebral aneuysms
    • recent eye surgery
    • presence of an acute disease process that might interfere with test performance (e.g. nausea, vomiting)
    • recent surgery of thorax or abdomen

    So where did the AARC’s list of contraindications come from? And why is there such a discrepancy between the ATS/ERS and the AARC guidelines?

    A search of the literature led me to BG Cooper’s excellent review of the subject. He points out that the contraindications in both the ATS/ERS and AARC guidelines are based on expert opinion that originated more than 30 years prior to the publication of either standard and not from any formal research. In addition changes in medical technology and practices make the value of many of these older contraindications questionable. In particular changes in post-surgical patient care, and most specifically the widespread use of incentive spirometry (which is usually instituted immediately following surgery) has patients performing maneuvers that are similar in nature to pulmonary function testing.

    So what makes anything a contraindication? The primary requirement for this has to be the level of risk. Risk is determined by two factors; first, the likelihood that an ‘adverse event’ will occur during pulmonary function testing. Second, the severity of the ‘adverse event’ if and when it does occur. An absolute contraindication has both a high likelihood of occurring and a high degree of severity. A relative contraindication on the other hand is where either the likelihood or the severity of an adverse event is low. There’s a level of risk that’s greater than zero, but that risk depends on an individual patient’s status.

    Whenever there is any level of risk, it of course has to be outweighed by the potential benefit ratio of testing. There are going to be situations where even though spirometry has an elevated level of risk the information it provides is critical to the patient’s care. Realistically however, the number of times when the results from any pulmonary function tests will have an immediate benefit for a patient with a high level of risk are rare and it is more likely that testing can be deferred to another time.

    Cooper reviewed surgical and medical literature extensively and by cross referencing the likelihood and potential severity of adverse events, developed an evidence-based list of contraindications.

    Contraindication: Complication: Likelihood: Severity: Risk:
    MI (recent) Death 5 5 25
    MI (recent) Further MI 5 5 25
    PE (untreated) Death 4 5 25
    Ascending Aortic Aneurysm (>6 cm dilation) Death 4 5 20
    Ascending Aortic Aneurysm (>6 cm dilation) MI 4 4 16
    Pneumothorax Lung collapse 3 4 12
    Thoracic surgery futher surgery 3 4 12
    Pneumothorax Pain 5 2 10
    Ascending Aortic Aneurysm (<6 cm dilation) Death 2 5 10
    Thoracic surgery Death 2 5 10
    Hemoptysis Bleed 2 4 8
    Angina MI 2 4 8
    Ascending Aortic Aneurysm (<6 cm dilation) MI 2 4 8
    Eye surgery (<1 week) Undo surgery 2 3 6
    Abdominal surgery Pain 3 2 6
    Thoracic surgery Pain 3 2 6
    Hemoptysis Death 1 5 5
    Pneumothorax Discomfort 5 1 5
    MI (>1 week) Death 1 5 5
    PE (treated) Death 1 5 5
    Hemoptysis PE 1 4 4
    Acute diarrhea Discomfort 4 1 4
    Abdominal surgery Rupture 1 4 4
    Angina Pain 2 2 4
    PE (treated) Hypoxia 1 3 3
    Eye surgery (<4 week) Undo surgery 1 3 3
    Eye surgery (<4 week) Pain 1 2 2
    MI (>1 week) Pain 1 2 2

    Where the scoring for likelihood, severity and risk are:

    Likelihood:
    1 <1%
    2 2-10%
    3 11-20%
    4 20-50%
    5 >50%
    Risk:
    1-4 Low
    5-9 Moderate
    10-19 High
    20-25 Very High
    Severity:
    1 Discomfort
    2 Pain
    3 Syncope/bleeding
    4 Tissue Damage, minor surgery
    5 Emergency care, major surgery, death

    Cooper’s list is, of course, a simplification and an individual patient’s level of risk may differ from these general guidelines for any number of reasons. Nevertheless, it is an excellent starting point for an ordering physician who is attempting to determine the risks versus the benefits of pulmonary function testing for a patient.

    The list however, is primarily oriented towards spirometry, since that test tends to generate relatively large intra-thoracic and intra-abdominal pressures. Since MIP and MEP testing also generates high intra-thoracic and intra-abdominal pressures the same contradictions likely apply. Lung volume measurements (regardless of which technique) and DLCO also require a vital capacity maneuver, but this can (and should) be performed with significantly less force and therefore much lower intra-thoracic and intra-abdominal pressures. Any patient for whom incentive spirometry can be ordered should be able to perform lung volume and DLCO testing.

    A more specific contraindication for lung volume measurements (specifically the helium dilution and plethysmographic techniques) is the potential for hypoxia in oxygen-dependent patients. When lung volumes are important for the management of a patient’s care however, this can be managed to some extent by monitoring a patient’s oxygen saturation with a pulse oximeter and terminating testing only if SpO2 drops below a safe threshold. A more likely limitation in these patients however, is claustrophobia which is a common occurrence in those who are chronically dyspneic.

    Elevated levels of carbon monoxide has been raised as a potential concern for DLCO testing, particularly for pregnant women. Realistically however, the level of CO that a developing fetus is exposed to from DLCO testing is no greater than would routinely be seen in urban settings, and certainly is far less risky than cigarette smoking would be.

    Exercise testing at either moderate (6-minute walk) or heavy (CPET) levels needs to be evaluated on a case-by-case basis. It should be noted that early post-surgical mobilization of patients has become a common practice so exercise per se is not necessarily contraindicated. Testing may be instead be contraindicated for neurological or musculoskeletal reasons such as paralysis, balance, and weakness that have nothing to do with respiratory, cardiovascular or post-surgical factors. However, the 2003 ATS/ACCP statement on cardiopulmonary exercise testing lists the following as absolute contraindications:

    • Acute myocardial infarction (3–5 days)
    • Unstable angina
    • Uncontrolled arrhythmias causing symptoms or hemodynamic compromise
    • Syncope
    • Active endocarditis
    • Acute myocarditis or pericarditis
    • Symptomatic severe aortic stenosis
    • Uncontrolled heart failure
    • Acute pulmonary embolus or pulmonary infarction
    • Thrombosis of lower extremities
    • Suspected dissecting aneurysm
    • Uncontrolled asthma
    • Pulmonary edema
    • Room air desaturation at rest <85%
    • Respiratory failure
    • Acute noncardiopulmonary disorder that may affect exercise performance or be aggravated by exercise (i.e. infection, renal failure, thyrotoxicosis)
    • Mental impairment leading to inability to cooperate

    and the following as relative contraindications:

    • Left main coronary stenosis or its equivalent
    • Moderate stenotic valvular heart disease
    • Severe untreated arterial hypertension at rest (>200 mm Hg systolic, >120 mm Hg diastolic)
    • Tachyarrhythmias or bradyarrhythmias
    • High-degree atrioventricular (AV) block
    • Hypertrophic cardiomyopathy
    • Significant pulmonary hypertension
    • Advanced or complicated pregnancy
    • Electrolyte abnormalities
    • Orthopedic impairment that compromises exercise performance

    The 2014 ERS/ATS statement on field walking tests (which includes the 6-minute walk test) indicates that the same contraindications apply to walking tests as apply to cardiopulmonary tests indicated in the 2003 statement.

    The 2001 AHA statement on exercise testing has an essentially identical list of contraindications as the ATS/ACCP 2003 statement but as absolute contraindications it includes:

    • Physical disability that would preclude safe and adequate test performance
    • Inability to obtain consent

    and for relative contraindications it includes:

    • Atrial fibrillation with uncontrolled ventricular rate
    • Electrolyte abnormalities

    Since challenge testing (methacholine, cold air, eucapnic voluntary hyperventilation, exercise) includes spirometry, the contraindications from the 2017 ERS statement includes factors that are similar to those mentioned in Cooper’s list, but since the intent of challenge testing is to induce bronchoconstriction (under controlled conditions, of course) it contains some that are specific to this form of testing:

    • FEV 1 <60% predicted (adults or children) or 1.5 L (adults)
    • FEV 1 <75% predicted (adults or children) for exercise or eucapnic voluntary hyperventilation challenge
    • Inability to perform acceptable and repeatable spirometry manoeuvres throughout the test procedure
    • Cardiovascular problems
    • Myocardial infarction or stroke in last 3 months
    • Uncontrolled hypertension
    • Known aortic aneurysm
    • Recent eye surgery or intracranial pressure elevation risk
    • Inability to perform any of the testing manoeuvres

    Finally, for bronchodilator reversibility testing using beta-agonist inhalers, there are the following relative contraindications:

    • Thyrotoxicosis
    • Heart failure
    • Hypertension
    • Tachydysrhythmias
    • Decreased glucose tolerance
    • Unstable diabetes mellitus and the concomitant use of cardiac glycosides.

    However, it has been noted that these contraindication actually apply to the risks involved with the regular use of beta-agonist inhalers and the risk of a single administration for diagnostic purposes is likely small.

    What is clear from all this is that the single absolute contraindication to routine pulmonary function testing included in the ATS/ERS 2005 general considerations statement is far too limited. The AARC 1996 contraindications are more similar to Cooper’s list, but lacks nuance or any indication of relative risk. For these reasons I think that until such time as the ATS and/or ERS update the standards for pulmonary function testing Cooper’s list should be added to every PFT Lab’s procedure manual.

    Contraindications are a somewhat neglected part of our field and I think this is because we rarely have a complete diagnosis and patient history available to us when tests are scheduled. Nor do we have the time to review this information, nor for that matter do we necessarily have the expertise. The appropriateness of tests and their risks and benefits for a patient are up to the physician ordering their tests and they are often unaware of possible contraindications. For this reason I’d recommend that labs should have a document detailing contraindications to PFT testing (example) that can be mailed or emailed to physicians whenever necessary.

    I don’t have a good answer why there is only one absolute contraindication in the 2005 ATS/ERS statement when there were so many in the 1996 AARC statement. It’s possible that the ATS/ERS participants thought that without objective data, expert opinion was just that, opinion. Still though, contraindications are important for patient safety and it seems that more attention should have been paid to this issue.

    I was able to report my findings to my medical director and the patient with the AAA was eventually tested without incident. It was evident however, that my lab’s procedure manual needs to be updated and that we need to be better prepared to respond to this issue.

    References:

    AARC Clinical Practice Guideline. Spirometry 1996 Update. Respir Care 1996; 41: 629-636.

    American Thoracic Society. Guidelines for Methacholine and Exercise challenge testing – 1999. Amer J Respir Crit Care Med 2000; 161: 309-329.

    ATS/ACCP Statement on cardiopulmonary exercise testing. Amer J Respir Crit Care Med 2003; 167: 211-277.

    ATS Standardization of spirometry – 1987 Update. Amer Rev Respir Dis 1987; 136: 1285-1296.

    ATS Standardization of spirometry – 1994 Update. Amer J Respir Crit Care Med 1995; 152: 1107-1136.

    Brusasco V, Crapo R, Viegi G. ATS/ERS Task Force: Standardisation of lung function testing. General considerations for lung function testing. Eur Respir J 2005; 26: 153-161.

    Coates AL, Wanger J, Cockcroft DW et al. ERS Technical standard on bronchial challenge testing: general considerations and performance of methacholine challenge tests. Eur Respir J 2017; 49: 1601526.

    Cooper BG. An update on contraindications for lung function testing. Thorax 2011; 66: 714-723.

    Fletcher GF, Balady GJ, Amserdam EA, et al. AHA Scientific statement. Exercise standards for testing and training. A statement for healthcare professionals from the American Heart Association. Circ 2001; 104: 1694-1740.

    Holland AE, Spruit MA, Trooster T et al. An official European Respiratory Society/American Thoracic Society technical standard: field walking tests in chronic respiratory disease. Eur Respir J 2014; 44: 1428-1446.

    Quanjer PH, Tammeling GJ, Cotes JE, Pedersen OF, Peslin R, Yernault JC. Lung volumes and forced ventilatory flows. Official statement of the European Respiratory Society. Eur Respir J 1993; Suppl 16: 5-40.

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  • Assessing post-BD improvement in FEV1 and FVC as a percent of the predicted

    The 2005 ATS/ERS standards for assessing post-bronchodilator changes in FVC and FEV1 have been criticized numerous times. A recent article in the May issue of Chest (Quanjer et al) has taken it to task on two specific points:

    • the change in FVC and FEV1 has to be at least 200 ml
    • the change is assessed based on the percent change (≥12%) from the baseline value

    The article points out that the 200 ml minimum change requires a proportionally larger change for a positive bronchodilator response in the short and the elderly. Additionally, by basing the post-BD change on the baseline value it lowers the threshold (in terms of an absolute change) for a positive bronchodilator response as airway obstruction become more severe. As a way of mitigating these problems the article recommends looking at the post-bronchodilator change as a percent of predicted rather than as a percent of baseline.

    The article is notable (and its authors are to be commended) because it studied 31,528 pre- and post-spirometry records from both clinical and epidemiological sources from around the world. For the post-bronchodilator FEV1 and FVC:

    • the actual change in L
    • the percent change from baseline
    • the change in percentage of predicted
    • the Z-score

    were determined.

    The results were analyzed by various sub-groups and those for healthy non-smokers were interesting because they show the normal range of response to bronchodilators in a non-symptomatic population. Specifically the median post-bronchodilator increase in FEV1 was 0.071 L (+2.7% from baseline) while the median post-BD FVC showed a decrease of 0.019 L (-0.51% from baseline). The top 5th percentile (ULN) had an increase in both FEV1 and FVC of 0.32 L (+13.3% and +12.0% of baseline respectively). The bottom 5th percentile (LLN) was also instructive since it showed decrease in FEV1 of 0.118 L (-4.3% of baseline) and in FVC of 0.324 L (-9.5% of baseline) which is a reminder (which you will find on the product inserts when you read the fine print) that bronchodilators can cause bronchoconstriction in some individuals.

    Since a bronchodilator response is most important for individuals with airway obstruction the results for sub-groups based on the degree of airway obstruction are particularly informative. For both males and females the greatest absolute change in FEV1 occurred in moderate and moderately severe airway obstruction (+ 0.240 L and + 0.242 L respectively) and was lowest in the very severe category (+0.155 L). The absolute increase in FVC however, increased as the level of airway obstruction increased, being lowest in mild obstruction (+0.070 L) and highest in individuals with very severe airway obstruction (+0.343 L).

    When bronchodilator responsiveness was assessed using the ATS/ERS criteria for FEV1, the number of individuals who improved significantly was greatest in the moderately severe and severe categories (46.8% and 44.5% respectively for males and 27.1% and 26.8% for respectively for females) and lowest in mild and very severe airway obstruction (22.1% and 27.9% respectively for males and 23.2% and 16.0% for females).

    FVC improvement on the other hand, showed that the post-bronchodilator change increased with the severity of airway obstruction, with the lowest increase in those with mild airway obstruction (4.0% for males and 4.6% for females) and largest in those with very severe airway obstruction (47.9% in males, 41.2% in females).

    The article notes however, that one quarter of the subjects with a low baseline FEV1 (primarily elderly and children) had a >12% increase from the baseline FEV1 but that the increase was less than 200 ml. It also points out that the FEV1 increased by >12% from baseline in only 20% of individuals with mild airway obstruction but 55% of the individuals with very severe airway obstruction and that this change was inconsistent with the structural changes in the airways and the lung that occur in chronic airway obstruction (i.e. airways should be become less responsive as airway obstruction increases). For both these reasons the article recommends assessing bronchodilator response as a percent change of predicted (or the z-score) rather than from baseline.

    The effect of this recommendation however, is that it decreases the number of individuals who would be considered to have a positive bronchodilator response, although this depends on the selected threshold. When compared to the current ATS/ERS criteria a 12% increase in percent predicted of the FEV1 causes the number of individuals with very severe airway obstruction to decrease from 27.9% to 7.0% in males and from 16.0% to 8.3% in females. When a threshold increase of 8 percent predicted in FEV1 is used (based on survival statistics from Ward et al) however, the number of individuals that show a positive response were 17.4% in males and 18.1% in females.

    Interestingly, the increase in FVC based on 12% increase of the predicted FVC, although decreased from the ATS/ERS criteria, was still greater in individuals with very severe airway obstruction (28.7% in males, 24.1% in females) and lowest in individuals with mild airway obstruction (4.3% in males, 5.0% in females).

    The effects of assessing changes in FEV1 as a percent of the predicted are less clear than might be initially expected. Using a 75 year old, 185 cm Caucasian male as an example, up until a normal baseline FEV1 of 100% of predicted, a 12 percent predicted change in FEV1 always requires a larger increase in FEV1 than does the ATS/ERS threshold. Using an 8 percent of predicted as a criteria however, up until a baseline FEV1 of 65% of predicted, the increase in FEV1 has to be somewhat larger than the ATS/ERS threshold but from 65% of predicted upwards, a significant change in FEV1 by 8 precent predicted is less than the ATS/ERS threshold.

    However, when a 75 year old 160 cm Caucasian female is used as an example, one of the problems of the ATS/ERS criteria becomes more evident since the 200 ml minimum is greater than a 12% increase from baseline until the baseline FEV1 is slightly greater than the predicted FEV1.

    The article also points out the importance of changes in FVC in individuals with more severe airway obstruction. Most specifically, a much larger number of individuals with severe airway obstruction had a positive response to bronchodilator based on their increase in FVC than they did for FEV1. I am disappointed however, that the effect of expiratory time on FVC was not analyzed or discussed. Although a number of researchers have indicated that an increase in expiratory time is a clinically relevant effect of bronchodilators, changes in expiratory time and FVC have not been subjected to the same survival analysis that Ward et al made on FEV1.

    It is past time that the ATS/ERS criteria for a positive bronchodilator response was updated and the findings presented in this article will likely influence the next ATS/ERS statement on interpretation (when and if it is published). Assessing changes in FEV1 and FVC based on a percent of predicted makes a great deal of sense, particularly since it does away with age and height biases imposed by the 200 ml threshold. The 200 ml threshold was based mostly on the need to differentiate a clinically significant increase from the “noise level” of poorly reproducible results but this tends to be influenced by a small number of individuals and as already noted makes no allowances for height or age. Comparing changes as a percent of the predicted makes a 200 ml threshold unnecessary.

    In addition the 8% threshold for FEV1 advocated by Ward et al (discussed previously) appears to have a significant level of clinical relevance. Although the number of individuals considered to have a positive bronchodilator response would decrease in those with severe airway obstruction, it would increase in those with mild airway obstruction.

    One final note is that the terminology involved in using a percent of the predicted is often confusing. It’s easy to get mixed up when you try to discuss FVC and FEV1 and then post-bronchodilator changes in FEV1 or FVC either as an absolute values or a percent of baseline or as a percent of predicted. In particular it becomes hard to say “there was a 12% increase in FEV1” without clarifying whether the increase is from the baseline or when compared to the predicted. Some standardization of the terms used would help clarify this. The authors bypassed this problem to some extent by frequently discussing the results in terms of their z-score but despite their underlying connection to statistics (and maybe because of it) z-scores are not as well understood as percent predicted and remain underutilized.

    References:

    Brusasco V, Crapo R, Viegi G. ATS/ERS task force: Standardisation of lung function testing. Interpretive strategies for lung function tests. Eur Respir J 2005(6); 26: 948-968.

    Quanjer P, Ruppel GL, Langhammer A, et al. Bronchodilator response in FVC is larger and more relevant than FEV1 is severe airflow obstruction. Chest 2017; 151(5): 1088-1098.

    Ward H, Cooper BG, Miller MR. Improved criteria for assessing lung function reversibility. Chest 2015; 148(4): 877-886.

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  • What do you do when the predicted is zero?

    A very strange spirometry report came across my desk a couple of days ago.

    Observed: Predicted: %Predicted:
    FVC: 3.07 0 29767
    FEV1: 2.15 0 37586
    FEV1/FVC: 70 71 101%

    My first thought was that some of the demographics information had been entered incorrectly but when I checked the patient’s age, height, gender and race all were present, all were reasonably within the normal range for human beings in general and more importantly, all agreed with what was in the hospital’s database for the patient. I tried changing the patient’s height, age, race and gender to see if it would make a difference and although this made small changes in the percent predicted when I did this the predicteds were still zero.

    Or were they? They actually couldn’t have been zero, regardless of what was showing up on the report, since the observed test values are divided by the predicted values and if the predicted were really zero, then we’d have gotten a “divide by zero” error, and that wasn’t happening. Instead the predicted values had to be very close to zero, but not actually zero, and the software was rounding the value down to zero for the report. Simple math showed me the predicted value for FVC was (very) approximately 0.0103 liters, but why was this happening?

    Fortunately, my lab’s database can be viewed and manipulated via MS Access. Although I am far from an expert in SQL itself MS Access makes it relatively easy to write database queries and I’ve been doing this for at least the last 20 years or so. For example, there are several pulmonary physician researchers that look for patients that meet certain age, gender and FEV1 and FEV1/FVC ratio criteria for possible enrollment in different studies. I wrote a rather complicated query for this (it calculates predicted FVC, FEV1 and FEV1/FVC ratio using the NHANESIII reference equations) about 15 years ago, and have updated it every time it needed a new test date range, new patient age range, new FEV1 range or whatever. I’ve written numerous other types of queries off and on for years and I’m reasonably familiar with the lab database and its structure. This meant that if there was a problem with the data being used to calculate the predicteds, there was only a limited set of inter-related files that the error could be in, and I had a good idea which ones they were.

    I wrote a quick query that selected the patient’s records and started paging through them. After a bit of searching I finally found the data field that was causing the problem. I corrected the value I found in it, and when I did and re-generated the report, it finally came out looking a lot more normal.

    Observed: Predicted: %Predicted:
    FVC: 3.07 3.41 90%
    FEV1: 2.15 2.36 91%
    FEV1/FVC: 70 71 101%

    So what was the data field? It was labeled prediction_correction_factor and as best I can understand it, it appears to be a value that is used modify the predicted after it has been calculated. The value that was in the field was 21757 and all other patients tested on the same day had a no value at all in that field (i.e. the same field was empty for everybody else even for those with the same ethnicity). Since this is the first time I can remember ever seeing this problem it was most probably a computer glitch of some kind

    So, problem solved and maybe I could go back to other things? Well, sort of yes, since as I said this problem doesn’t seem to have happened before and I’ve been reviewing reports for over 25 years. But I got to thinking about it and the only reason that it was obvious was that the value in that field was so large. It might never have been noticed if it had been a smaller value that made only a small change to a predicted value. Just as importantly there are also some issues about where this field is located in the database and how it can affect the predicted values for not just one visit, but all of the visits a patient makes to the lab.

    First, why is there a field like this in the first place? My best guess (and it will probably remain a guess since the company we acquired our test systems from hasn’t answered any of the questions I’ve had about the database in over 10 years) is that it is a holdover from the time when it was more common to perform racial corrections using 85% of the predicted value for Caucasians for Blacks and 92% for Asians (or thereabouts, anyway). Since the 2005 ATS/ERS standards for interpretation were published however, the recommendation has been that that ethnicity-specific equations be used instead and that is the way our software is currently organized; there are different sets of equations for different ethnicities and the software selects which set is to be used based on the ethnicity entered in patient demographics. But our database goes back well before 2005 and there has to be be a way to bridge the difference between older and newer test records and this may have been one of the ways that this was done.

    But our lab database actually stores records in several files to maintain a patient’s demographic information. For example, values that can and do change from one visit to another such as weight, height and age are kept in one file and information that doesn’t change such as ethnicity and date of birth is kept in another. There is in fact, only one record kept for a patient’s non-changing information no matter how many visits they make to the PFT Lab. Since this record contains the patient’s ethnicity, it shouldn’t be a surprise that it also contains the prediction_correction_factor as well. What this means is that if this field is somehow altered it will affect all patient visits, not just the current one.

    There is no general fix for this kind of problem since realistically we are completely dependent on our test system software to calculate predicted and percent predicted values (not to mention making the test measurements in the first place). It’s just not possible to check all of the calculations by hand. We don’t have the manpower and we don’t have the time. I could write a query that regularly looks for odd values in the prediction_correction_factor field, but that’s not something that many other labs could do.

    Still, it was somewhat disconcerting to find that our lab database contains a single field that is able to wreak as much havoc on predicted calculations as it appears that this one is able to.

    What is particularly concerning is that this field is not accessible through any the regular lab software functions (which I suppose makes sense if it is a vestigial function) but is only by looking directly at the database. If we weren’t able to do this the only possible fix would have been to delete all of the patient’s records (for all of their visits, including their demographic records) and re-enter the numerical values manually, losing all of the graphical information (flow-volume loops and volume-time curves) along the way. And it would have taken a while to figure out that this was our only option because I know I would have tried a lot of other things before I thought about deleting and re-entering everything.

    This problem a reminder that we still need to check calculated values whenever we think something is “off”. There’s no guarantee that our systems are always correct and as complicated as they are, errors of one kind or another are probably inevitable.

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  • The effects of anemia on exercise

    Last week I was reviewing the exercise test results from a patient that appeared to have a relatively straightforward cardiovascular limitation when I noticed the patient also had severe anemia (Hgb = 7.1). Once that fact came up it was no longer clear the patient actually had a cardiac limitation at all.

    First the results:

    Rest: %Predicted: AT: %Predicted: Max: %Predicted:
    VO2 (LPM): 0.33 13% 0.73 28% 1.45 56%
    VO2 (ml/kg/min): 5.0 11.0 21.6
    VCO2 (LPM) 0.26 0.63 1.81
    RER: 0.73 0.83 1.24
    SaO2: 98% 97% 97%
    PetCO2: 35.2 38.6 31.8
    Ve/VO2: 34 26 43
    Ve/VCO2: 47 31 35
    Ve (LPM): 11.6 8% 19.2 13% 62.9 44%
    Vt (L): 0.78 1.29 2.19
    RR: 15 15 29
    HR (BPM): 61 35% 92 52% 152 85%
    BP (mmHg): 92/62 102/64
    O2 Pulse (ml/beat): 5.8 39% 8.2 55% 9.8 66%

    Other values calculated from the data include:

    Ve-VCO2 (rest to AT): 23.8
    Ve-VCO2 (rest to peak): 31.6
    Chronotropic Index: 1.54

    The maximum VO2 of 1.45 LPM (56% of predicted) indicates a moderate reduction in exercise capacity but overall the patient gave a good exercise test effort and this shown by the elevated RER at peak exercise (1.24) and the maximum heart rate (85% of predicted).

    The test results show a cardiovascular limitation fairly clearly. This is in part because any significant pulmonary limitations are ruled out by:

    • Normal SaO2 throughout exercise
    • Maximum Ve was 44% of predicted
    • Ve/VCO2 at AT <35 and Ve-VCO2 slope (rest to AT) <34.

    On the other hand, the typical features of a cardiovascular limitation are present:

    • Low VO2 at AT (28% of predicted)
    • Low maximum O2 pulse (66% of predicted)
    • Elevated Chronotropic Index (1.54)

    These kind of results are usually the result of a low cardiac output. Specifically, anaerobic threshold will occur early when the heart is unable to deliver enough oxygen to the exercising muscles. O2 pulse is a product of stroke volume and the A-v O2 content difference and when SaO2 is normal, it is a reasonable (although certainly not exact) index of stroke volume so a reduced O2 pulse suggests that the stroke volume is also reduced. Something similar is being said by the chronotropic index, since an elevated value (above 1.30) says that heart rate is advancing faster than oxygen consumption which would also be expected if the stroke volume is low.

    But all of this assumes that the amount of oxygen being carried by the blood is reasonably normal and this is not true when anemia is present. Remember the O2 content of blood is determined by:

    (Hgb x 1.36 x SaO2) + (0.0031 x PaO2)

    So the amount of oxygen that can be carried by the blood is directly related to the hemoglobin concentration:

    Strictly speaking therefore, when hemoglobin is 7.1, blood can only carry about 9.7 ml/decaliter of oxygen which is slightly less than half it could carry if the hemoglobin was normal (19.7 ml/decaliter), which in turn means that the heart has to pump twice as much blood to deliver the same amount of oxygen.

    So did this patient really have a cardiovascular limitation? Probably not, or at the very least, probably not nearly as much of one as these results would usually seem to indicate. The only way to be sure however, would be to repeat the test after the patient’s hemoglobin has returned to normal.

    I usually try to find recent hemoglobin results for our CPET patients, just as I would for DLCO patients. Our criteria however, is that a hemoglobin measurement needs to have been made within the last month to be relevant. This is admittedly arbitrary but neither the 2005 nor the 2017 ATS/ERS standards for DLCO testing state how recent a hemoglobin needs to be in order to be used for correction. Although hemoglobin measurements aren’t all that uncommon the fact that it needs to be recent means when it comes to either a CPET or a DLCO most of our patients don’t have one that we can use.

    The ability of hemoglobin to carry oxygen is a basic part of physiology. We’re all reasonably aware of the need to correct DLCO tests for hemoglobin but despite this anemia is an often overlooked factor in exercise tests. Because anemia lowers the oxygen carrying capacity of the blood it can mimic or exacerbate a cardiovascular limitation and this needs to be kept in mind when interpreting CPET results.

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  • Is there such a thing as a normal decrease when the FEV1 isn’t normal?

    I’ve mentioned before that my lab’s database goes back to 1990, so we now have 27 years of test results available for trending. At least a couple times a week we have a patient who was last seen 10 or even 20 years ago. When I review their results I try to see if there has been any significant change from their last tests. Since the last tests are often quite some time in the past the changes in an absolute sense are often noticeably large. The question then becomes whether or not these changes are normal.

    Although the ATS/ERS, NIOSH and ACOEM standards for spirometry address changes over time they don’t specifically discuss changes over a decade or longer. Instead, without indicating a time period (other than saying a year or more), the concensus is that a change greater than 15% in age-adjusted FVC or FEV1 is likely to be significant. A change in absolute values greater than:

    Or if the current FEV1 is less than:

    Then the change is likely significant.

    This sounds fairly reasonable and although we could quibble about the importance of how quickly or slowly this age-adjusted 15% change occurs and how well it applies when the patient’s latest age is beyond the reference equation’s study population (we have a fair number of 90+ year old patients nowadays) or when it’s across a developmental threshold (adolescent to adult), it’s still a good starting point.

    I’ve been more or less following these rules for the last several years, when the results for a patient whose last test was 18 years ago came across my desk. The FEV1 from the current spirometry was 71% of predicted and the FEV1 from 18 years ago was 70% of predicted. Strictly speaking the absolute change was about -15% (the FEV1 was 2.06 L in 1999 and 1.76 L in 2017, a 0.30 L change) but when adjusted for the change in age, that’s only 40% what a significant change would need to be:

    Given that the FEV1 percent predicted from both the older and newer test were essentially identical I automatically started to type “The change in FEV1 is normal for the change in age” when it suddenly occurred to me that neither FEV1 was normal in the first place so how could I be sure the change be normal?

    The first problem is that we don’t know what’s happened in between the two tests. The original spirometry test showed mild airway obstruction, but in the interim it could have been well controlled and normal the entire time. It could also be that the only reason that they’re seeing a pulmonary physician is that they are having an exacerbation and that it’s actually just chance that the FEV1 percent predicted is the same between the two tests.

    The second problem is that the way that the ATS/ERS, NIOSH and ACOEM assess changes over time come from occupational studies where the individuals studied were presumably normal to begin with and where the changes that occurred were expected to be due to occupational exposures. This may mean that it’s possible that we can use their criteria for change only when the baseline test was normal. When a patient has a lung disorder, regardless of whether it is obstruction or restriction, it isn’t clear at all that there is such a thing as a normal change over time. In fact an accelerated decline in FVC or FEV1 is actually the “norm” for certain lung diseases (i.e. COPD and IPF) and that means a change less than that (although probably acceptable to the individual in question) isn’t, strictly speaking, normal.

    This just may all be just an issue of semantics, however. Saying that a change isn’t significant (which is what the ATS/ERS, NIOSH and ACOEM standards are saying) isn’t the same as saying that it’s a normal change. That means there’s no reason not to say “the change in FEV1 isn’t significant”. My problem with this is that although it may be be statistically and semantically correct to say this it also somehow seems to be lacking in information content.

    And it’s also probably misleading. If the patient’s FEV1 had decreased from 2.06 L (70% of predicted) by 0.76 L to 1.30 L (52% of predicted), that would be less than a significant change by the ATS/ERS, NIOSH and ACOEM criteria, but it would also be a change from mild airway obstruction to moderately severe airway obstruction and I’m hard pressed not to think that’s significant. The problem is that the formula is dominated by the predicted normal values and this means a significant change has to be relatively large in an absolute sense and for this patient based on her initial FEV1, anything less than 0.77 L over 18 years would not be significant. This makes some sense if the FEV1 was originally normal, but if the FEV1 is already compromised then even small changes may be clinically significant.

    There needs to be some kind of middle ground here. I think it’s important to give an indication whether a change over a prolonged period of time is normal or abnormal and as a first approximation the ATS/ERS, NIOSH and ACOEM consensus is a reasonable approach. Where I think it tends to fail is in patients with severe reductions in FVC or FEV1. One possible way to correct this lies in the recognition that FVC and FEV1 have a floor, i.e. a lower limit beyond which mortality increases dramatically. For FEV1 at least this appears to be about 0.50 L so an amended formula could look something like this:

    For this patient this would change the acceptable change over 18 years from 0.77 L to 0.69 L. Not a big change, but for somebody that already had a severe decrease in FEV1 it lowers the threshold for what constitutes a significant change.

    This still doesn’t get around the fact that we don’t know what happened in the interim but realistically this is a problem no matter what time frame that tests occur. We’re likely to place more reliance on trends when testing is performed more frequently, but we still have to admit our ignorance of what happens between tests no matter how often they are performed.

    Note: This is why I don’t like graphical trend reports that draw lines between data points. The line implies what is happening in between tests and that’s just sheer conjecture.

    At the moment I think I’ll use my amended formula when trying to assess whether a change over a prolonged period of time is within normal limits. At the same time though, even if the change isn’t statistically significant but there is a significant change in diagnosis (i.e. say from mild obstruction to severe obstruction) then it’s probably worth stating that the change “is larger than expected for the change in age”. Saying that may not be statistically correct but it’s certainly correct in a clinical sense.

    References:

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

    Townsend, MC. ACOEM Guidance Statement. Spirometry in the occupational health setting – 2011 update. J Occup Env Med 2011; 53(5): 569-584

    U.S. Department of Health and Human Services. Public Health Service. Centers for Disease Control. National Institute for Occupational Safety and Health. Education and Information Division. Criteria for a recommended Standard. Occupational Exposure to Respirable Coal Mine Dust. 1995.

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  • What does an inverse I:E Ratio during exercise mean?

    Inspiration and expiration usually take different lengths of time, with inspiration almost always being shorter than exhalation. This is due to both to the physiology of breathing and to the pathophysiology of disease processes. During incremental exercise testing there are usually patterns to the way that inspiratory and expiratory times change and these are occasionally diagnostic.

    When I started in this field the relationship between inspiratory and expiratory time was usually expressed as the I:E ratio, which was most often written as something like 1:1.2. One of my medical directors pointed out to me that when talking about I:E ratio it was difficult to determine what you meant if you said it was increasing or decreasing. For this reason I started reporting the I:E ratio as the E/I ratio so that instead of 1:1.2 it’s just 1.2.

    Somewhere along the way however, for exercise testing at least, the most common way of expressing the I:E ratio seems to have morphed primarily into Ti/TTot (which is the Inspiratory Time/Total Inspiratory and Expiratory Time ratio), less commonly as Ti/Te and almost never as I:E. Even so, I still prefer the E/I ratio approach, partly because I’m used to it but mostly because it emphasizes the expiratory time component. For example:

    Ti/TTot: Ti/Te: E/I:
    0.50 1.00 1.0
    0.48 0.91 1.1
    0.45 0.83 1.2
    0.43 0.77 1.3
    0.42 0.71 1.4
    0.40 0.66 1.5
    0.38 0.63 1.6
    0.37 0.59 1.7
    0.36 0.56 1.8
    0.34 0.53 1.9
    0.33 0.50 2.0

    Anyway, at rest most subjects breathe with an E/I ratio somewhere between 1.2 and 1.5 (Ti/TTot 0.45 – 0.40). During exercise the E/I ratio usually decreases more or less steadily and usually reaches 1.0 (Ti/TTot 0.50) at or near peak exercise. When a subject has airway obstruction the E/I ratio often doesn’t decrease and in those with severe airway obstruction it often increases instead. E/I ratios above 2.0 aren’t all that uncommon in subjects with COPD. Occasionally a subject with normal baseline spirometry (i.e. a normal FEV1/FVC ratio) has an elevated and/or increasing E/I ratio throughout testing and this is a clue that they probably have some degree of airway obstruction that’s not otherwise evident, and possibly even EIA if it increases at peak exercise.

    Despite the fact that the I:E ratio often reflects underlying lung disorders, I could find no mention of the I:E ratio (or Ti/TTot) in the 2003 ATS/ACCP statement on exercise testing, the 2010 AHA guide to exercise testing, the 2012 EACPR/AHA Joint statement on cardiopulmonary exercise testing, Wasserman et al’s textbook on exercise testing or in Madama’s textbook. Ti/TTot was mentioned in one paragraph of the 1997 ERS statement on exercise testing and twice in Ward and Palange’s 2007 monograph on exercise testing where Ti/TTot was dismissed by saying “this measurement is not commonplace in clinical exercise testing and its diagnostic value is not proven.”

    Even so, when reviewing CPET results I always look at the progression of E/I ratio during exercise to see if it fits the other findings. The E/I ratio is almost always above 1.0 and only very rarely do I ever see it below 1.0 (which rightly or wrongly is what I call an inverse I:E ratio). When I do, most often it is during the baseline and most often in subjects that are hyperventilating (most likely anxiety or the fight-or-flight response). Once in a while I also see it dip slightly below 1.0 (like to around 0.95) at peak exercise, usually in relatively normal subjects. Other than that, E/I ratios below 1.0 (Ti/TTot > 0.50) are fairly unusual.

    So, you can imagine I was interested when a CPET came across my desk with an E/I ratio below 1.0 throughout testing.

    Time: Ve (L): Vt (L): RR: Ti/TTot: E/I:
    0:30 16.2 0.87 20 0.52 0.94
    1:00 17.2 1.04 16 0.52 0.94
    1:30 16.7 0.86 20 0.55 0.82
    2:00 19.5 1.05 20 0.56 0.80
    2:30 18.5 1.04 18 0.57 0.74
    3:00 22.1 1.07 22 0.53 0.90
    3:30 29.5 1.16 27 0.51 0.97
    4:00 34.0 1.28 27 0.53 0.88
    4:30 38.4 1.33 34 0.56 0.78
    5:00 48.5 1.49 33 0.55 0.82
    5:30 59.6 1.55 39 0.55 0.82

    The individual in question has IPF and was referred for the CPET as part of a pre-operative assessment by CT surgery.

    Observed: %Predicted:
    FVC: 3.24 79%
    FEV1: 2.54 87%
    FEV1/FVC: 78 108%
    DLCO: 11.32 47%
    VA: 3.67 55%

    Despite the subject’s reduced DLCO, the primary limitation turned out to be cardiovascular which was apparent because they never desaturated (SaO2 remained above 95% throughout testing); the VO2 at AT was reduced (39% of predicted); the Ve-VCO2 slope (rest to peak) was elevated (43.6); and the chronotropic index was reduced (0.76) without being on beta-blockers. The subject was also well below a ventilatory limitation (max Ve 59% of predicted) at peak exercise.

    I’d say that chronotropic incompetence (usually because of beta blocker medications but not always) is one of the more common diagnoses we see in our CPETs, so other than the reduced E/I ratio there wasn’t anything terribly unusual about the CPET.

    So why was the E/I ratio reduced?

    As already mentioned this can happen during the baseline period, usually when an individual is hyperventilating but this almost always disappears and the E/I ratio reverts to more normal values within a minute or so after exercise starts. When it persists during exercise however, it’s most often a sign of inspiratory airway obstruction. This can be due to a variety of causes, which can include vocal cord dysfunction, but the primary sign that this is occurring is that there is an inspiratory plateau in the flow-volume loops (we obtain these when we have subjects perform an inspiratory capacity maneuver in order to measure changes in their EELV). In this case however, this didn’t appear to be happening,

    Inspiratory loops from the last two exercise levels

    The subject’s peak inspiratory flow was more than -4.0 L/sec and there was no apparent plateau whatsoever. There really aren’t any normal values available for peak inspiratory flow during exercise, but this really doesn’t look like there’s any significant inspiratory flow limitation.

    This individual does has IPF however, and for this reason I searched the literature as best as I could looking for any association between interstitial diseases and inverse I:E ratios. What I found was that the I:E ratio or Ti/TTot are only rarely reported in studies of ILD and exercise. Where it is reported however, the majority indicate that the I:E ratio and/or Ti/TTot usually were not significantly different from normal subjects or that there were actually small decreases in Ti/TTot (small increases in E/I ratio).

    Even though there doesn’t appear to be a general association between IPF and an inverse I:E ratio I have to wonder there may be one in this case. IPF causes lungs to become “stiffer” and harder to expand which should increase the work of breathing during inspiration. As part of the pre-CPET assessment we always record breath sounds and for this patient they were “loud inspiratory crackles”. Although inspiratory crackles (particularly “velcro” crackles) are often seen (well, heard actually) in IPF, their cause is unclear. In chronic bronchitis however, they are an indication that small atelectatic airways are popping open and since atelectasis is often seen in IPF I’m going to go out on a limb as say that the cause of inspiratory crackles in IPF is probably similar.  If that’s the case, then opening atelectatic airways has to increase the inspiratory work of breathing even more.

    This is going a long way around to say that my best guess is that this subject’s inverse I:E ratio is occurring because their inspiratory work of breathing is much higher than it is for expiration, and that this is causing them to have a slower inspiration than expiration. If we could measure compliance it might be possible to show that this is the case but we don’t have the ability to do this (and I don’t know of any clinical PFT Labs that does) so given the lack of any apparent inspiratory obstruction, other than an elevated inspiratory work of breathing it’s hard to imagine what else the cause could be.

    The I:E ratio (or Ti/TTot) is an often overlooked measurement in cardiopulmonary exercise testing. Realistically it only rarely adds something to the diagnostic interpretation, but it still should always be reviewed and this is because unexpectedly elevated E/I ratios (reduced Ti/TTot) can show that there is a component of expiratory airway obstruction in subjects with normal spirometry and reduced E/I ratios (elevated Ti/TTot) can show the presence of inspiratory airway obstruction.

    The E/I ratio is usually mildly elevated at rest and decreases to 1.0 at peak exercise in normal subjects. An E/I ratio slightly below 1.0 at rest or at peak exercise isn’t all that unusual but an E/I ratio that remains below 1.0 (or a Ti/TTot that remains above 0.50) throughout testing is unusual and deserves further investigation.  In this particular instance an inverse I:E ratio, although interesting, didn’t really contribute to the final diagnosis, which was a cardiovascular limitation.  If the reason(s) for the cardiovascular limitation can be addressed and the CPET repeated however, it’s possible the patient would reach a ventilatory limitation instead, in which case the inverse I:E ratio might end up playing a role after all.

    References:

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    Balady GJ, Arena R, Sistema K, et al. Clinicians guide to cardiopulmonary exercise testing in adults: A scientific statement from the American Heart Association. Circ 2010; 122: 191-225.

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    Wasserman K, Hansen JE, Sue DY, Stringer WW, Whipp BJ. Principles of exercise testing and interpretation, Fourth Edition. Lipincott, Williams & Wilkins. Published 2005.

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