Agreement Between Fixed-Ratio and Lower Limit of Normal Spirometry Interpretation Protocols Decreases With Age: Is There a Need for a New GOLD Standard?

Different Case Finding Approaches to Optimise COPD Diagnosis: Evidence from the RADICALS Trial

Aim

Diagnosis of COPD in primary care is hindered by underuse of spirometry. Case finding using validated symptom and health status questionnaires, and simple handheld devices in high-risk populations may improve diagnosis. This study aimed to determine the best combination of measures to optimise COPD diagnosis in the primary care setting.

Methods

We recruited 335 current or ex-smokers, including those with an established diagnosis of COPD from general practices. Participants' FEV1 and FEV6 were measured using a handheld spirometry device (COPD-6®). Each completed the COPD assessment test (CAT), a modified Medical Research Council (mMRC) dyspnoea scale, St George's Respiratory Questionnaire (SGRQ) and smoking history questionnaire. From these data we calculated the predictive validity for spirometry-confirmed diagnosis of COPD. Area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, positive and negative predictive values (PPV, NPV) were calculated for each. Kappa coefficient was used to measure the agreement between the Fixed-Ratio (FR) and Lower Limit of Normal (LLN) spirometric criteria in diagnosing COPD.

Results

FEV1/FEV6 <0.70 alone showed significant association (p<0.0001) with COPD diagnosis and good predictive accuracy (AUROC=0.725). However, no further improvement was found after combining SGRQ, CAT and mMRC with FEV1/FEV6. FEV1/FEV6 <0.70 using the COPD-6® handheld device had moderate sensitivity (65.7%) and high PPV (90.1%), high specificity (79.3%) and NPV (44.8%). There was good agreement between FR and LLN definitions (κ=0.70).

Conclusion

Handheld micro-spirometers can facilitate case finding of COPD in smokers and ex-smokers attending general practice. The fixed ratio criterion currently recommended by COPD-X guidelines offers the simplest method for diagnosing COPD in Australian primary care.

Restrictive spirometry pattern among construction trade workers

BACKGROUND

Spirometry-based studies of occupational lung disease have mostly focused on obstructive or mixed obstructive/restrictive outcomes. We wanted to determine if restrictive spirometry pattern (RSP) is associated with occupation and increased mortality.

METHODS

Study participants included 18,145 workers with demographic and smoking data and repeatable spirometry. The mortality analysis cohort included 15,445 workers with known vital status and cause of death through December 31, 2016. Stratified analyses explored RSP prevalence by demographic and clinical variables and trade. Log-binomial regression models explored RSP risk factors while controlling for important confounders such as smoking, obesity, and comorbidities. Cox regression models explored mortality risk by spirometry category.

RESULTS

Prevalence of RSP was very high (28.6%). Mortality hazard ratios for RSP were 1.50 for all causes, 1.86 for cardiovascular diseases, 2.31 for respiratory diseases, and 1.66 for lung cancer. All construction trades except painters, machinists, and roofers had significantly elevated risk for RSP compared to our internal reference group. RSP was significantly associated with both parenchymal and pleural changes seen by chest X-ray.

CONCLUSIONS

Construction trade workers are at significantly increased risk for RSP independent of obesity. Individuals with RSP are at increased risk for all-cause mortality as well as mortality attributable to respiratory diseases, cardiovascular diseases, and lung cancer. RSP deserves greater attention in occupational medicine and epidemiology.

A quantitative analysis of biomechanical lung model consistency using 5DCT datasets

PURPOSE

Lung biomechanical models are important for understanding and characterizing lung anatomy and physiology. A key parameter of biomechanical modeling is the underlying tissue elasticity distribution. While human lung elasticity estimations do not have ground truths, model consistency checks can and should be employed to gauge the stability of the estimation techniques. This work proposes such a consistency check using a set of 10 subjects.

METHODS

We hypothesize that lung dynamics will be stable over a 2-3 min time period and that this stability can be employed to check biomechanical estimation stability. For this purpose, two sets of 12 fast helical free breathing computed tomography scans (FHFBCT) were acquired back-to-back for each of the subjects. A published breathing motion model [five-dimensional CT (5DCT)] was generated from each set. Both of the models were used to generate two biomechanical modeling input sets: (a) The lung geometry at the end-exhalation, and (b) the voxel displacement map that mapped the end-exhalation lung geometry with the end-inhalation lung geometry. Finite element biomechanical lung models were instantiated using the end-exhalation lung geometries. The models included voxel-specific lung tissue elasticity values and were optimized using a gradient search approach until the biomechanical model-generated displacement maps matched those of the 5DCT voxel displacement maps. Finally, the two elasticity distributions associated with each of the patient 5DCTs were quantitatively compared. Because the end-exhalation geometries differed slightly between the two scan datasets, the elasticity distributions were deformably mapped to one of the exhalation datasets.

RESULTS

For the 10 patients, on average, 90% of parenchymal voxels had <2 kPa Young's modulus difference between the two estimations, with a mean voxel difference of only 0.6 kPa. Similarly, 97% of the parenchymal voxels had <2 mm displacement difference between the two models with a mean difference of 0.48 mm. Furthermore, overlapping elasticity histograms for voxels between -600 and -900 HU (parenchymal tissues) showed that the histograms were consistent between the two estimations.

CONCLUSION

In this paper, we demonstrated that biomechanical lung models can be consistently estimated when using motion-model based imaging datasets, even though the models were created from scans acquired at different breaths.

Fractional Exhaled Nitric Oxide as an Inflammatory Biomarker in Chronic Obstructive Pulmonary Disease (COPD) with or without Concurrent Diagnosis of Asthma: The Canadian Cohort Obstructive Lung Disease (CanCOLD)

We studied whether fractional exhaled nitric oxide (F _ENO) can differentiate chronic obstructive pulmonary disease (COPD) with concurrent diagnosis of asthma from COPD-only as well as its ability to predict disease severity and progression. This study was embedded in the Canadian Cohort Obstructive Lung Disease (CanCOLD). Subjects of ≥40 years old completed F _ENO measurements were subdivided into four groups, including COPD (N = 86 [COPD-only (N = 35) and COPD with concurrent diagnosis of asthma (N = 51)], healthy (N = 72), and at risk (N = 151). Three of the most common clinical definitions were used for characterizing COPD with concurrent diagnosis of asthma: 1) atopy and self-reported physician diagnosis of asthma, 2) ≥12% and ≥200 ml post-bronchodilator FEV1; 3) self-reported physician diagnosis of asthma. F _ENO values were classified using quartiles and the American Thoracic Society (ATS) guideline 2011. Compared to COPD-only, more COPD with concurrent diagnosis of asthma had a significant F _ENO50 level of [Formula: see text] 33.5 ppb (fourth quartile) than COPD-only (p = 0.045, 0.011, and 0.006, for definition 1, 2, and 3, respectively). Considering the ATS guideline 2011, fewer COPD with concurrent diagnosis of asthma had F _ENO50 < 25 than COPD-only, which was statistically significant with definition 1 and 3 (p = 0.038 and 0.026, respectively). F _ENO as a biomarker has the potential to be used as a complementary value for differentiating COPD with concurrent diagnosis of asthma from COPD-only. Further studies should be conducted on validated definitions of COPD with concurrent diagnosis of asthma, which may include a reference to the type of airway inflammation in addition to the clinical definition.

NR, Make BJ, Marchetti N, Martinez FJ, Maselli DJ, Mathews AM, McCormack MC, McDonald MLN, McEvoy CE, Moll M, Molye SS, Murray S, Nath H, Newell Jr. JD, Occhipinti M, Paoletti M, Parekh T, Pistolesi M, Pratte KA, Putcha N, Ragland M, Reinhardt JM, Rennard SI, Rosiello RA, Ross JC, Rossiter HB, Ruczinski I, San Jose Estepar R, Sciurba FC, Sieren JC, Singh H, Soler X, Steiner RM, Strand MJ, Stringer WW, Tal-Singer R, Thomashow B, Vegas Sánchez-Ferrero G, Walsh JW, Wan ES, Washko GR, Michael Wells J, Wendt CH, Westney G, Wilson A, Wise RA, Yen A, Young K, Yun J, Silverman EK, Crapo JD. COPDGene® 2019: Redefining the Diagnosis of Chronic Obstructive Pulmonary Disease

BACKGROUND

Chronic obstructive pulmonary disease (COPD) remains a major cause of morbidity and mortality. Present-day diagnostic criteria are largely based solely on spirometric criteria. Accumulating evidence has identified a substantial number of individuals without spirometric evidence of COPD who suffer from respiratory symptoms and/or increased morbidity and mortality. There is a clear need for an expanded definition of COPD that is linked to physiologic, structural (computed tomography [CT]) and clinical evidence of disease. Using data from the COPD Genetic Epidemiology study (COPDGene®), we hypothesized that an integrated approach that includes environmental exposure, clinical symptoms, chest CT imaging and spirometry better defines disease and captures the likelihood of progression of respiratory obstruction and mortality.

METHODS

Four key disease characteristics - environmental exposure (cigarette smoking), clinical symptoms (dyspnea and/or chronic bronchitis), chest CT imaging abnormalities (emphysema, gas trapping and/or airway wall thickening), and abnormal spirometry - were evaluated in a group of 8784 current and former smokers who were participants in COPDGene® Phase 1. Using these 4 disease characteristics, 8 categories of participants were identified and evaluated for odds of spirometric disease progression (FEV1 > 350 ml loss over 5 years), and the hazard ratio for all-cause mortality was examined.

RESULTS

Using smokers without symptoms, CT imaging abnormalities or airflow obstruction as the reference population, individuals were classified as Possible COPD, Probable COPD and Definite COPD. Current Global initiative for obstructive Lung Disease (GOLD) criteria would diagnose 4062 (46%) of the 8784 study participants with COPD. The proposed COPDGene® 2019 diagnostic criteria would add an additional 3144 participants. Under the new criteria, 82% of the 8784 study participants would be diagnosed with Possible, Probable or Definite COPD. These COPD groups showed increased risk of disease progression and mortality. Mortality increased in patients as the number of their COPD characteristics increased, with a maximum hazard ratio for all cause-mortality of 5.18 (95% confidence interval [CI]: 4.15-6.48) in those with all 4 disease characteristics.

CONCLUSIONS

A substantial portion of smokers with respiratory symptoms and imaging abnormalities do not manifest spirometric obstruction as defined by population normals. These individuals are at significant risk of death and spirometric disease progression. We propose to redefine the diagnosis of COPD through an integrated approach using environmental exposure, clinical symptoms, CT imaging and spirometric criteria. These expanded criteria offer the potential to stimulate both current and future interventions that could slow or halt disease progression in patients before disability or irreversible lung structural changes develop.

Joint Indian Chest Society-National College of Chest Physicians (India) guidelines for spirometry

Although a simple and useful pulmonary function test, spirometry remains underutilized in India. The Indian Chest Society and National College of Chest Physicians (India) jointly supported an expert group to provide recommendations for spirometry in India. Based on a scientific grading of available published evidence, as well as other international recommendations, we propose a consensus statement for planning, performing and interpreting spirometry in a systematic manner across all levels of healthcare in India. We stress the use of standard equipment, and the need for quality control, to optimize testing. Important technical requirements for patient selection, and proper conduct of the vital capacity maneuver, are outlined. A brief algorithm to interpret and report spirometric data using minimal and most important variables is presented. The use of statistically valid lower limits of normality during interpretation is emphasized, and a listing of Indian reference equations is provided for this purpose. Other important issues such as peak expiratory flow, bronchodilator reversibility testing, and technician training are also discussed. We hope that this document will improve use of spirometry in a standardized fashion across diverse settings in India.

Lower limit of normal based spirometric abnormalities associated with radiographic abnormality in an elderly cohort at low risk for exposure

BACKGROUND

Although the relation between radiographic abnormalities and spirometric impairment in people with asbestosis has been studied extensively, the extent of spirometric impairment associated with milder radiographic abnormalities is not established.

OBJECTIVE

To test associations between mild radiographic abnormalities and Lower Limit of Normal (LLN)-based spirometry interpretation.

METHODS

Spirometry and CXRs were collected for 1,026 at low risk of exposure to pneumoconiotic agents participants in a medical screening program.

RESULTS

Individuals with each type of isolated or combined International Labour Organization (ILO) abnormalities had up to over sixfold statistically significant increase in odds of LLN-based restrictive pattern physiology (OR = 1.96, 95%CI 1.03-3.73 for parenchymal to OR = 6.09, 95%CI 1.94-19.10 for parenchymal and pleural) compared to those with normal films.

CONCLUSIONS

The findings from this study confirm the association of mild profusion abnormalities with clinically relevant, LLN-based lung function abnormalities.

Change in prevalence of restrictive lung impairment in the U.S. population and associated risk factors: the National Health and Nutrition Examination Survey (NHANES) 1988-1994 and 2007-2010

Background

Data for the U.S adult population from the National Health and Nutrition Examination Survey (NHANES) were used to evaluate risk factors for a restrictive pattern on spirometry and estimate the change in its prevalence from the 1988–1994 to 2007–2010 sampling periods. Several previous epidemiologic studies used the Global Initiative for Chronic Obstructive Lung Disease fixed forced expiratory volume in 1 second (FEV₁)/forced vital capacity (FVC) > 0.70 criteria for classifying restrictive pattern rather than the age-defined American Thoracic Society (ATS)/European Respiratory Society (ERS) lower limit of normal (LLN) criteria, which may lead to misclassification.

Methods

Spirometry measurements from NHANES data for the 1988–1994 and 2007–2010 periods were analyzed to estimate the age-standardized prevalence of a restrictive pattern on spirometry and the change in prevalence over time for adults aged 20–79. A restrictive pattern was defined based on ATS/ERS LLN criteria as FEV₁/FVC > LLN and FVC < LLN, and a moderate to more severe restrictive pattern was further evaluated using FEV₁ < 70% predicted. The associations between demographic and other individual risk factors for restrictive lung impairment were examined using multivariable logistic regression models for the two consecutive time periods.

Results

The overall age-standardized prevalence of restrictive pattern decreased significantly from 7.2% (1988–1994) to 5.4% (2007–2010) (p = 0.0013). The prevalence of moderate to more severe restrictive pattern also decreased significantly from 2.0% to 1.4% (p = 0.023). Factors positively associated with restrictive pattern on spirometry included age, female sex, white race, lower education, former and current smoking, and comorbidities including doctor-diagnosed cardiovascular disease, doctor-diagnosed diabetes, and abdominal obesity.

Conclusions

The overall prevalence of restrictive pattern and moderate to more severe restrictive pattern decreased between the 1988–1994 and 2007–2010 survey periods despite a population increase in the proportion of comorbidities associated with restrictive pattern (i.e. diabetes and abdominal obesity). This suggests a decline in individual risk factors for restrictive pattern and a need for future research.

Cardio-respiratory reference data in 4631 healthy men and women 20-90 years: the HUNT 3 fitness study

PURPOSE

To provide a large reference material on key cardio-respiratory variables in a healthy population of Norwegian men and women aged 20-90 years.

METHODS

Sub maximal and peak levels of cardio-respiratory variables were measured using cardiopulmonary exercise testing during treadmill running.

RESULTS

The highest peak ventilation among men (141.9±24.5 L·min-1) and women (92.0±16.5 L·min-1) was observed in the youngest age group (20-29 years, sex differences p<0.001) with an average 7% reduction per decade. The highest tidal volumes were observed in the 30-39 and 40-49 year age groups among men (2.94±0.46 L) and women (2.06±0.32 L) (sex differences p<0.001), with a subsequent average 6% reduction per decade. Ventilatory threshold and respiratory compensation point were observed at approximately 77% and 87% of peak oxygen uptake (VO2peak) among men and women, respectively. The best ventilatory efficiency (EqVCO2Than) was observed in the youngest age group (20-29 years) in both men (26.2±2.8) and woman (27.5±2.7) (sex differences p<0.001) with an average 3% deterioration in ventilatory efficiency per decade.

CONCLUSION

This is the largest European reference material of cardio-respiratory variables in healthy men and women aged 20-90 years, establishing normal values for, and associations between key cardio-respiratory parameters. This will be useful in clinical decision making when evaluating cardiopulmonary health in similar populations.