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Original Research: PULMONARY FUNCTION TESTING |

Discordance in Spirometric Interpretations Using Three Commonly Used Reference Equations vs National Health and Nutrition Examination Study III FREE TO VIEW

Jacob Collen, CPT, MC, USA; David Greenburg, CPT, MC, USA; Aaron Holley, MAJ, MC, USA; Christopher S. King, CPT, MC, USA; Oleh Hnatiuk, COL, MC, USA, FCCP
Author and Funding Information

*From the Departments of Internal Medicine (Drs. Collen and Greenburg), and Pulmonary/Critical Care Medicine (Drs. Holley, King, and Hnatiuk), Walter Reed Army Medical Center, Washington, DC.

Correspondence to: Christopher S. King, CPT, MC, USA, Walter Reed Army Medical Center, Department of Medicine, 6900 Georgia Ave NW, Washington, DC 20350; e-mail: christopher.king@na.amedd.army.mil


Presented at Combined Army-Air Force American College of Physicians Conference November 18, 2007.

The views expressed in this article are those of the authors and do not reflect the official policy of the Department of the Army, Department of Defense, or the US Government.

The authors have reported to the ACCP that no significant conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (www.chestjournal.org/misc/reprints.shtml).


Chest. 2008;134(5):1009-1016. doi:10.1378/chest.08-0614
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Background:  Spirometry plays an essential role in the diagnosis and management of pulmonary diseases. The accurate interpretation of spirometric data depends on comparison to a reference population to identify abnormalities in ventilatory function. National guidelines recommended the use of the National Health and Nutrition Examination Study (NHANES) III data set as the preferred reference population for those persons 8 to 80 years of age in the United States.

Objectives:  To determine the effect of using NHANES III reference equations, compared to those of Crapo et al (Crapo), Knudson et al (Knudson), or Morris et al (Morris), on spirometric interpretations in non-Hispanic white patients.

Methods:  We conducted a cross-sectional study of all white patients undergoing spirometry testing at our hospital from January 2000 through May 2007. Patients were classified as normal, restricted, obstructed, or mixed, based on the American Thoracic Society (ATS)/European Respiratory Society (ERS) guidelines, using the Crapo, Knudson, Morris, and NHANES III prediction equations. Differences in the classifications based on the reference data set were evaluated.

Results:  At total of 8,733 subjects (62.4% male subjects) were identified, with a mean age of 53 years. Discordance was most common when the results from prediction equations by Knudson and Morris were compared to those of NHANES III (45.5% and 35.3%, respectively). Diagnostic recategorizations occurred less frequently when the prediction equations by Crapo were compared with those of NHANES III (15.9%). Relative to NHANES III, the prediction equations by Knudson, Crapo, and Morris tend to overclassify obstruction and underclassify restriction.

Conclusions:  There is significant discordance between the prediction equations put forth by Crapo, Knudson, Morris, and the NHANES III. Our data suggest that the diagnostic reclassification of many patients undergoing pulmonary function testing will occur when ATS/ERS guidelines are implemented. Pulmonologists and other physicians interpreting spirometry need to be aware of the presence and nature of these changes.

Figures in this Article

Clinicians, researchers, and patients all benefit from the accurate interpretation of spirometry. Accurate interpretation depends on the comparison of acquired spirometric data with appropriate reference standards. Until recently, the recommendation regarding choice of reference equations was left up to individual pulmonary function test (PFT) laboratories.1 Reference equations published by Crapo et al2 (Crapo), Knudson et al3 (Knudson), and Morris et al4 (Morris) were used commonly in past years.5 In 2005, the American Thoracic Society (ATS) and the European Respiratory Society (ERS) published new combined guidelines recommending the use of reference values from the National Health and Nutrition Examination Study (NHANES) III population data set7 in the United States.6 At present, it is unclear how many laboratories follow the ATS/ERS recommendations. However, this switch has the potential to lead clinicians and researchers to change disease classifications (eg, normal, obstruction, and restriction) or severities (eg, mild, moderate, or severe) without changes in actual disease status.8 This may subsequently result in changes in diagnoses, in alterations in diagnostic evaluations and therapies, as well as in different populations being included or excluded from new research protocols.

We conducted a cross-sectional study of all white patients who were undergoing spirometry testing at our tertiary care center from January 2000 through May 2007. All spirometry testing was performed according to ATS standards (Pulmonary Function Testing Equipment; SensorMedics; Yorba Linda, CA).9 Prior to 2005, spirometry end-of-test criteria were based on the 1994 ATS standards.10 Measured spirometric indexes for individual patients were interpreted in comparison to reference values that were calculated based on demographic data using the reported equations for the respective reference equations. All patients were reclassified using an algorithm that was similar to the ATS/ERS recommended algorithm for spirometric interpretation (Fig 1).6

Figure Jump LinkFigure 1 Spirometric interpretive strategy.Grahic Jump Location

Patients whose measured FVC fell below the lower limit of the normal range as determined using the equations by Crapo, Knudson, Morris, or NHANES III were classified as having a restrictive pattern. The severity of restriction was graded based on the degree of decrement in FVC below the lower limit of normal (LLN), in accordance with the 1986 ATS guidelines.11 Patients whose measured FEV1/FVC ratio fell below the LLN as defined by Crapo, Knudson, or NHANES III were classified as obstructed. The study by Morris did not include an equation for the predicted FEV1/FVC. For Morris, we defined obstruction as an FEV1/FVC of < 0.70. Obstructive severity was based on the degree of decrement in FEV1 determined according to the ATS/ERS 2005 guidelines.6 Patients with both obstructive and restrictive defects were categorized as having a mixed pattern. This protocol was approved by the Department of Clinical Investigation at our hospital.

Due to a concern that discordance between spirometric interpretations may be isolated to individuals who were near thresholds for reclassification, we performed a post hoc analysis of discordance in which we calculated the number of patients whose predicted FVC using the equations of Knudson, Crapo, and Morris differed from the predicted FVC using the equations of the NHANES III. Significant differences in predicted FVC between the prediction equations were defined as being greater than the ATS criteria for repeatability (change in FVC ≥ 150 mL or ≥ 3% predicted). Significant differences in the predicted FEV1 were also defined as a change of ≥150 mL or ≥3% predicted.

Statistical Analysis

Relationships between continuous and categoric variables were assessed using the Student t test and χ2 test, respectively. Agreement on the interpretation of spirometric patterns (ie, normal, obstructive, restrictive, or mixed) between predictive models was assessed using the κ statistic. Agreement on the severity of obstruction and restriction was assessed using the quadratic κ statistic. The reported p values are two sided. Statistical significance was defined as p < 0.05. All analyses were performed using a statistical software package (STATA, version 9.2; StataCorp LP; College Station, TX). Multivariate logistic regression was used to calculate the adjusted odds ratios for discordance between interpretative strategies using equations by Crapo, Knudson, and Morris in comparison against those from the NHANES III. Covariates included in the logistic regression models included sex, age (< 25, 25 to 34.9, 35 to 49.9, 50 to 64.9, 65 to 79.9, and > 80 years), body mass index (BMI) [< 18.5, 18 to 24.9, 25 to 29.9, 30 to 40, and ≥ 40 kg/m2], being short (ie, height in the lowest 2.5% for gender), or being tall (ie, height in the highest 2.5% for gender).

During the study period, a total of 14,390 PFTs were performed at our facility. The majority of subjects were white (n = 8,733; 60.7%) with the remainder categorized as African American (n = 4,463; 31.0%), Hispanic (n = 667; 4.6%), and Asian (n = 527; 3.7%). This study was limited to exploring spirometric discordance among whites. Demographic information on the patients included in our study is listed in Table 1. A histogram of patient ages is provided in Figure 2.

Table Graphic Jump Location
Table 1 Patient Demographics

Comparing spirometric classifications identified using equations by Crapo, Knudson, and Morris to those identified by the NHANES III, we found multiple discordant categories (Fig 3). Three discordance patterns were the most common and likely to have a substantial impact on patient care and research. These include patients who were classified as normal by the equations of Crapo, Knudson, or Morris but were reclassified as restrictive by those of the NHANES III; patients who were classified as obstructive by the equations of Crapo, Knudson, and Morris but were reclassified as normal by those of the NHANES III; and patients who were classified as obstructive by the equations of Crapo, Knudson, and Morris but were reclassified as restrictive by those of the NHANES III. Concordant classification was observed in 76.3%, 68.5%, and 59.6% of patients, respectively, when comparing classifications made by the equations of Crapo, Morris, and Knudson to those by NHANES III. The Crapo predictive equations classified 4,096 patients as normal. Of these patients, 9.9% (n = 406) were reclassified as restrictive by the equations of the NHANES III. Of the 2,257 test results that were classified as obstructive, 23.5% (n = 530) and 2.2% (n = 50), respectively, were reclassified by the equations of the NHANES III as normal and restrictive. The Morris predictive equations classified 5,625 test results as normal. Of these results, 26.1% (n = 1,467) were reclassified as restrictive by the equations of the NHANES III. Of the 2,700 test results classified as being obstructive, 13.7% (n = 371) and 7.2% (n = 193), respectively, were reclassified by the equations of the NHANES III as normal and restrictive. The Knudson predictive equations classified 4,294 test results as normal. Of these, 30.0% (n = 1,290) were reclassified as restrictive. Of the 4,249 patients who were classified as obstructive, 30.1% (n = 1,277) and 11.5% (n = 488), respectively, were reclassified by NHANES III as normal and restrictive (Table 2. The severity of restriction was found to be mild for all patients who were reclassified from normal by the equations of Crapo, Knudson, or Morris to restrictive by NHANES III. Of the patients who were reclassified from obstructed by the equations of Crapo, Knudson, or Morris, the vast majority fell into the mildly obstructed categories.

Table Graphic Jump Location
Table 2 Patterns of Discordance*

*Values are given as No. (%).

Evaluation of the diagnostic classification between the equations of NHANES III and Crapo was excellent (κ = 0.77), was fair with the equations of Morris (κ = 0.43), and was poor with the equations of Knudson (κ = 0.32). Comparisons of measures of obstruction and restriction severity were excellent between the equations of Crapo, Knudson, and Morris and the NHANES III (Table 3.

Table Graphic Jump Location
Table 3 Agreement Among Crapo, Morris, and Knudson, and the Severity of Obstructive and Restrictive Defects

The average predicted FVCs were slightly lower for all prediction equations relative to the FVCs predicted by the NHANES III equations (Table 4). The mean difference in FVC compared to those predicted by NHANES III equations ranged from 0.7% predicted (SD, 4.7% predicted) with the Crapo equations to 6.2% predicted (SD, 4.7% predicted) with the Knudson equations. Meaningful differences in predicted FVCs were observed between most individuals regardless of the choice of prediction equations when compared against FVCs predicted using equations from the NHANES III (Crapo, 6,003 L [69% predicted]; Knudson, 6,708 L [77% predicted]; and Morris, 8,262 L [95% predicted]). The vast majority of the discordance observed across all comparison equations occurred in patients with clinically important differences in predicted FVCs. These results suggest that the large degree of discordance observed was not due to individuals being near a diagnostic classification threshold.

Table Graphic Jump Location
Table 4 Differences in Predicted FVC Between Crapo, Morris, and Knudson, and NHANES III*

*Values are given as the mean (SD), unless otherwise indicated.

†Compared to NHANES III (> 150 mL or 3% predicted).

‡Values are given as No. (%).

The mean difference in FEV1 (in liters) was lower for Crapo equations than for the NHANES III equations (−0.04), while it was greater for both the Knudson equations (0.08) and the Morris equations (0.27) [Table 5]. A difference of ≥ 150 mL or ≥ 3% predicted was observed in a large percentage of patients for all studies, ranging from 49% for Crapo to 99% for Morris. Depending on the change in FVC, these differences may not have resulted in discordant PFT interpretation; however, they could potentially impact the interpretation of severity of obstruction.

Table Graphic Jump Location
Table 5 Differences in Predicted FEV1 Between Crapo, Morris, and Knudson, and NHANES III*

*Values are given as mean (SD), unless otherwise indicated.

†Compared to NHANES III.

‡Values are given as No. (%).

An assessment of the predictors of discordance was undertaken (Table 6). Relative to men, women experienced less discordance between all three prediction equation and those of the NHANES III. Compared to those persons aged 35 to 49.9 years, less discordance was observed in those persons < 25 years old when using equations by Crapo (odds ratio [OR], 0.65; 95% confidence interval [CI], 0.51 to 0.83) or Knudson (OR, 0.56; 95% CI, 0.47 to 0.66), but not those by Morris. An age of 65 to 74.9 years predicted less discordance between the equations of Crapo and the NHANES III (OR, 0.64; 95% CI, 0.54 to 0.76), whereas increased discordance was observed among those > 65 years of age with the equations by Knudson and Morris. Being underweight (BMI, < 18.5 kg/m2) or overweight (BMI, > 40 kg/m2) increased the odds of discordance relative to being of normal weight for all prediction equations. Short stature increased the odds of discordance with all of the prediction equations. Tall stature was protective from discordance when spirometry interpretations from the equations of Crapo were compared to those from the equations of the NHANES III (OR, 0.37; 95% CI, 0.24 to 0.59).

Table Graphic Jump Location
Table 6 Predictors of Discordance*

Short = lowest 2.5% in height for gender; Tall = top 2.5% in height for gender; ROC = receiver operating characteristic.

Our primary finding was the presence of significant discordance between standardized spirometric interpretations using NHANES III data compared to older reference equations in non-Hispanic white patients. This particular population was chosen because the older studies predominantly enrolled whites. Pulmonary function laboratories currently using Knudson may experience reclassification of nearly one half of their spirometric interpretations when implementing the new ATS/ERS guidelines, depending on the amount and severity of disease in their population. Laboratories currently using Crapo or Morris will experience reclassifications to a lesser degree. The most common patterns of reclassification are normal to restrictive, obstructive to normal, and obstructive to restrictive, using Knudson, Morris, or Crapo vs NHANES III, respectively.

A recent article by Sood and colleagues8 compared prior reference spirometry sets (Kory et al,11 Crapo et al,3 Morris et al,4 Knudson et al (1976),12 and Knudson et al3) against NHANES III data in 1,106 patients who had been referred for spirometry at their institution in central Illinois. Sood et al8 evaluated patients for the presence or absence of obstructive and restrictive abnormalities, and measured agreement among prediction equations. They found that agreement was poor between Crapo and NHANES III at identifying the presence of these defects (weighted κ, 0.13). Agreement between Knudson and Morris and data from NHANES III was similar (weighted κ, 0.46 and 0.44, respectively). Similar to our study, Sood et al8 reported good to excellent agreement on the severity of obstructive and restrictive defects between Crapo, Morris, and Knudson and NHANES III. The differences in results between their study and ours likely represent differences in the methodologies and samples between the studies. In the present study, we offer the benefit of looking at a significantly larger study population with a wider geographic distribution. In addition, instead of categorizing patients in two domains on the presence or absence of abnormalities, we classified patients as having a normal, obstructive, restrictive, or mixed pattern. We feel that this distinction is of more utility for clinicians who are interpreting these data. However, the overall conclusion of their study and ours is that changes in the interpretations of PFTs after converting from older reference equations to NHANES III will be common.

Both the number of reclassifications and the change in interpretation patterns are clinically important. Although it is difficult to predict the exact number of patients affected, it is undoubtedly large. In patients who are already being followed up with serial spirometry, original diagnoses may be reconsidered, leading to additional diagnostic testing and, potentially, to altered courses of therapy. Unless all laboratories are currently using NHANES III prediction equations, individuals undergoing initial spirometric evaluations may experience unnecessary referrals or will not be referred when needed.

Screening spirometry has been advocated for smokers over the age of 45 years and patients with respiratory symptoms.13 In addition, data on the utility of office-based testing in the primary care setting continues to accumulate.14,15 With increases in use by providers who are not specifically trained in interpretation, unexpected changes in reference standards could have a large impact on missed diagnoses, and inappropriate referrals, tests, and treatments.

From the researcher's perspective, the widespread implementation of the ATS/ERS guidelines using percent predicted as a selection criterion will result in different patient populations being studied now compared with those in previous studies. The results from populations defined by the older criteria may not be applicable to current patient populations. Additionally, changing the guidelines may have a broader public impact. Because spirometric measures presented as percent predicted are used in a variety of settings, changes will affect disability ratings,16 lung transplantation referrals,17 and preoperative risk assessments,18 as well as many other areas.

While the reasons for the discordance between reference equations cannot be defined with complete certainty, we propose several potential reasons. One potential reason may be differences between the reference populations studied. The populations in Crapo and Morris consisted primarily of members of The Church of Jesus Christ of Latter Day Saints (Mormons). These individuals may have had less exposure to air pollution and cigarette smoke than the population studied in NHANES III. Additionally, this white population predominately consisted of individuals of Northern and Middle European descent but may differ biologically from white Americans as a whole. If individuals studied by NHANES III had more smoke and pollution exposure resulting in mild obstructive lung disease, this could potentially explain the large number of individuals reclassified from obstructive to normal by NHANES III in comparison to all three older reference equations. Technical differences may have contributed to discordance among equations as well. Morris utilized a volume threshold rather than the back extrapolation that is currently recommended by the ATS in determining the start of a test.9 This may result in a falsely low FEV1 and an increased number of patients being reclassified from normal to obstructive. Knudson utilized a pneumotachometer, which may have terminated maneuvers early, resulting in a decreased FVC.8 The Crapo reference equation utilized the largest FVC and FEV1 sum rather than the largest value from separate efforts, as recommended by the ATS. This may result in a 50-mL reduction in the FVC.8 Finally, NHANES III required a five-maneuver minimum and provided computer-generated feedback to the technician that a 1-s plateau had been reached.7 All of the above reasons may explain the large number of patients reclassified from normal to restrictive who were observed in our study.

We found several demographic factors that make discordance more likely. Age > 50 years was associated with an increased likelihood of discordance between the Knudson and Morris equations and NHANES III data. Obesity was associated with an increased likelihood of discordance in all three older reference equations when compared to NHANES III. Jones and Nzekwu19 demonstrated a linear decrease in vital capacity with increasing BMI. It is likely that obese patients who are classified as normal by older reference equations for the reasons listed above fell below the LLN when compared to those classified by the NHANES III reference equation. Finally, patients in the lowest 2.5% of height had an increased risk of discordance for all reference populations compared to NHANES III. Female sex was protective against discordance for all reference equations.

Although our study was not designed to identify the optimal reference equation for this population, we believe the NHANES III equations are the best available to date. The NHANES III equations are based on a sample size that was 10-fold greater than those in any of the prior studies and included a heterogeneous population that was enrolled from 1988 to 1994. These equations are less subject to cohort effect in comparison to those derived by the Crapo, Morris, and Knudson studies, which enrolled patients in earlier decades (ie, the 1960s and 1970s).

Our study has several limitations. We purposefully limited our study to non-Hispanic white patients. The affect of race on the discordance between various reference equations will require further study. Additionally, our study was performed at a military institution. The patient population included active-duty soldiers, their dependents, and retirees. It is possible that this population may not be generalizable to the population of a civilian hospital. Another limitation of our study was the use of a fixed FEV1/FVC ratio of < 0.7 for the determination of obstruction for the Morris equation. We elected to use this technique as no formula for LLN was listed in the original Morris article. We also felt that this was consistent with the interpretive strategy utilized by the majority of PFT laboratories utilizing the Morris reference equation. Studies20 have shown a tendency to “overcall” obstruction in extremes of age and height with this technique, so it is likely that using a fixed ratio overestimated the number of patients who were classified with obstruction by the Morris equation. Only 17.9% of the discordance observed between NHANES III and Morris is explained by reclassification from obstructive to normal or restrictive; so, while the use of a fixed FEV1/FVC ratio may have exaggerated the rate of discordance, it was not the primary cause of discordance among these reference equations. It should also be noted that the thresholds utilized for the interpretation of ventilatory pattern are based on sharp, predetermined LLNs. If patients fall just below the LLN, it is possible that test-retest variability may result in interpretive changes in these “borderline” patients. This may eliminate discordance in an individual patient; however, it does not invalidate the overall finding of discordance among reference equations on a population level. Poor test quality may result in the misclassification of ventilatory patterns but should not affect a population-level comparison of reference equations. It may lead to a skewed subgroup analysis of demographic predictors of discordance if a disproportionate number of tests of poor quality are performed for one demographic group. We did not exclude patients based on the quality of spirometry, which is a limitation of our study.

In summary, physicians interpreting spirometry findings need to be familiar with the changes that will occur in interpretation, as outlined in our study, when adopting the new ATS/ERS guidelines. Physicians observing patients longitudinally should be aware that changes in interpretation may be due to changes in the reference standard even in the setting of equivalent spirometric measures. In this setting, the absolute values should be compared across tests instead of relying solely on the percent predicted values.21 Additionally, spirometric equipment manufacturers need to ensure that NHANES III reference equations and LLNs are part of the software package provided with their products. Last, pulmonary function laboratories and their medical directors need to ensure that all physicians relying on their services are aware of the potential impact of these changes.

ATS

American Thoracic Society

BMI

body mass index

CI

confidence interval

ERS

European Respiratory Society

LLN

lower limit of normal

NHANES

National Health and Nutrition Examination Study

OR

odds ratio

PFT

pulmonary function test

American Thoracic Society Lung function testing: selection of reference values and interpretative strategies. Am Rev Respir Dis. 1991;144:1202-1218. [PubMed] [CrossRef]
 
Crapo RO, Morris AH, Gardner RM. Reference spirometric values using techniques and equipment that meet ATS recommendations. Am Rev Respir Dis. 1981;123:659-664. [PubMed]
 
Knudson RJ, Lebowitz MD, Holberg CJ, et al. Changes in the normal maximal expiratory flow-volume curve with growth and aging. Am Rev Respir Dis. 1983;127:725-734. [PubMed]
 
Morris JF, Koski A, Johnson LC. Spirometric standards for healthy nonsmoking adults. Am Rev Respir Dis. 1971;103:57-67. [PubMed]
 
Ghio AJ, Crapo RO, Elliott CG. Reference equations used to predict pulmonary function: survey at institutions with respiratory disease training programs in the United States and Canada. Chest. 1990;97:400-403. [PubMed]
 
Pellegrino R, Viegi G, Brusasco V, et al. Interpretative strategies for lung function tests. Eur Respir J. 2005;26:948-968. [PubMed]
 
Hankinson JL, Odencrantz JR, Fedan KB. Spirometric reference values from a sample of the general US population. Am J Respir Crit Care Med. 1999;159:179-187. [PubMed]
 
Sood A, Dawson BK, Henkle JQ, et al. Effect of change of reference standard to NHANES III on interpretation of spirometric “abnormality.”. Int J Chron Obstruct Pulmon Dis. 2007;2:361-367. [PubMed]
 
Miller MR, Hankinson J, Brusasco V, et al. Standardisation of spirometry. Eur Respir J. 2005;26:319-338. [PubMed]
 
American Thoracic Society Standardization of spirometry, 1994 update. Am J Respir Crit Care Med. 1995;152:1107-1136. [PubMed]
 
Kory RC, Callahan R, Boren HG, et al. The Veterans Administration-Army cooperative study of pulmonary function: 1. Clinical spirometry in normal men. Am J Med. 1961;30:243-258
 
Knudson RJ, Slatin RC, Lebowitz MD, et al. The maximal expiratory flow-volume curve: normal standards, variability, and effects of age. Am Rev Respir Dis. 1976;113:587-600. [PubMed]
 
Ferguson GT, Enright PL, Buist AS, et al. Office spirometry for lung health assessment in adults: a consensus statement from the National Lung Health Education Program. Chest. 2000;117:1146-1161. [PubMed]
 
Dales RE, Vandemheen DL, Clinch J, et al. Spirometry in the primary care setting: influence on clinical diagnosis and management of airflow obstruction. Chest. 2005;128:2443-2447. [PubMed]
 
Yawn BP, Enright PL, Lemanske RF Jr, et al. Spirometry can be done in family physicians' offices and alters clinical decisions in management of asthma and COPD. Chest. 2007;132:1162-1168. [PubMed]
 
American Thoracic Society Evaluation of impairment/disability secondary to respiratory disorders. Am Rev Respir Dis. 1986;133:1205-1209. [PubMed]
 
Egan TM, Murray S, Bustami RT, et al. Development of the new lung allocation system in the United States. Am J Transplant. 2006;6:1212-1227. [PubMed]
 
Beckles MA, Spiro SG, Colice GL, et al. The physiologic evaluation of patients with lung cancer being considered for resectional surgery. Chest. 2003;123suppl:105S-114S. [PubMed]
 
Jones RL, Nzekwu MM. The effects of body mass index on lung volumes. Chest. 2006;130:827-833. [PubMed]
 
Roberts SD, Farber MO, Knox KS, et al. FEV1/FVC ratio of 70% misclassifies patients with obstruction at the extremes of age. Chest. 2006;130:200-206. [PubMed]
 
Cooper BG. Reference values in lung function testing: all for one and one for all? Int J Chron Obstruct Pulmon Dis. 2007;2:189-190. [PubMed]
 

Tables

Table Graphic Jump Location
Table 1 Patient Demographics
Table Graphic Jump Location
Table 2 Patterns of Discordance*

*Values are given as No. (%).

Table Graphic Jump Location
Table 3 Agreement Among Crapo, Morris, and Knudson, and the Severity of Obstructive and Restrictive Defects
Table Graphic Jump Location
Table 4 Differences in Predicted FVC Between Crapo, Morris, and Knudson, and NHANES III*

*Values are given as the mean (SD), unless otherwise indicated.

†Compared to NHANES III (> 150 mL or 3% predicted).

‡Values are given as No. (%).

Table Graphic Jump Location
Table 5 Differences in Predicted FEV1 Between Crapo, Morris, and Knudson, and NHANES III*

*Values are given as mean (SD), unless otherwise indicated.

†Compared to NHANES III.

‡Values are given as No. (%).

Table Graphic Jump Location
Table 6 Predictors of Discordance*

Short = lowest 2.5% in height for gender; Tall = top 2.5% in height for gender; ROC = receiver operating characteristic.

References

American Thoracic Society Lung function testing: selection of reference values and interpretative strategies. Am Rev Respir Dis. 1991;144:1202-1218. [PubMed] [CrossRef]
 
Crapo RO, Morris AH, Gardner RM. Reference spirometric values using techniques and equipment that meet ATS recommendations. Am Rev Respir Dis. 1981;123:659-664. [PubMed]
 
Knudson RJ, Lebowitz MD, Holberg CJ, et al. Changes in the normal maximal expiratory flow-volume curve with growth and aging. Am Rev Respir Dis. 1983;127:725-734. [PubMed]
 
Morris JF, Koski A, Johnson LC. Spirometric standards for healthy nonsmoking adults. Am Rev Respir Dis. 1971;103:57-67. [PubMed]
 
Ghio AJ, Crapo RO, Elliott CG. Reference equations used to predict pulmonary function: survey at institutions with respiratory disease training programs in the United States and Canada. Chest. 1990;97:400-403. [PubMed]
 
Pellegrino R, Viegi G, Brusasco V, et al. Interpretative strategies for lung function tests. Eur Respir J. 2005;26:948-968. [PubMed]
 
Hankinson JL, Odencrantz JR, Fedan KB. Spirometric reference values from a sample of the general US population. Am J Respir Crit Care Med. 1999;159:179-187. [PubMed]
 
Sood A, Dawson BK, Henkle JQ, et al. Effect of change of reference standard to NHANES III on interpretation of spirometric “abnormality.”. Int J Chron Obstruct Pulmon Dis. 2007;2:361-367. [PubMed]
 
Miller MR, Hankinson J, Brusasco V, et al. Standardisation of spirometry. Eur Respir J. 2005;26:319-338. [PubMed]
 
American Thoracic Society Standardization of spirometry, 1994 update. Am J Respir Crit Care Med. 1995;152:1107-1136. [PubMed]
 
Kory RC, Callahan R, Boren HG, et al. The Veterans Administration-Army cooperative study of pulmonary function: 1. Clinical spirometry in normal men. Am J Med. 1961;30:243-258
 
Knudson RJ, Slatin RC, Lebowitz MD, et al. The maximal expiratory flow-volume curve: normal standards, variability, and effects of age. Am Rev Respir Dis. 1976;113:587-600. [PubMed]
 
Ferguson GT, Enright PL, Buist AS, et al. Office spirometry for lung health assessment in adults: a consensus statement from the National Lung Health Education Program. Chest. 2000;117:1146-1161. [PubMed]
 
Dales RE, Vandemheen DL, Clinch J, et al. Spirometry in the primary care setting: influence on clinical diagnosis and management of airflow obstruction. Chest. 2005;128:2443-2447. [PubMed]
 
Yawn BP, Enright PL, Lemanske RF Jr, et al. Spirometry can be done in family physicians' offices and alters clinical decisions in management of asthma and COPD. Chest. 2007;132:1162-1168. [PubMed]
 
American Thoracic Society Evaluation of impairment/disability secondary to respiratory disorders. Am Rev Respir Dis. 1986;133:1205-1209. [PubMed]
 
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  • CHEST Journal
    Print ISSN: 0012-3692
    Online ISSN: 1931-3543