Original Research

Measuring Restrictive Lung Disease Severity Using FEV1 vs TLC

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Background: No clear parameters currently exist to grade severity in restrictive lung disease as for other ventilatory diseases. This article evaluates whether total lung capacity (TLC) or forced expiratory volume in 1 second (FEV1) better correlates with the symptomatology of patients with restrictive lung disease.

Methods: A retrospective review of 6461 patient records at Veterans Affairs Caribbean Healthcare System in Puerto Rico was conducted, and 414 patients met the inclusion criteria. Pulmonary function test, Modified Medical Research Council Dyspnea Scale, FEV1, and TLC data were collected for each patient.

Results: We identified a stronger correlation between FEV1 (r = 0.25, P < .001) vs TLC (r = 0.15, P < .001) when related to the degree of dyspnea as measured with the Modified Medical Research Council Dyspnea Scale.

Conclusions: Results of this study suggest that compared with TLC, FEV1 may provide a more accurate measure of restrictive lung disease severity. Further research should look for more accurate measures of patient dyspnea in restrictive lung disease.


 

References

Respiratory diseases have varied clinical presentations and are classified as restrictive, obstructive, mixed, or normal. Restrictive lung diseases have reduced lung volumes, either due to an alteration in lung parenchyma or a disease of the pleura, chest wall, or neuromuscular apparatus. If caused by parenchymal lung disease, restrictive lung disorders are accompanied by reduced gas transfer, which may be portrayed clinically by desaturation after exercise. Based on anatomical structures, the causes of lung volume reduction may be intrinsic or extrinsic. Intrinsic causes correspond to diseases of the lung parenchyma, such as idiopathic fibrotic diseases, connective-tissue diseases, drug-induced lung diseases, and other primary diseases of the lungs. Extrinsic causes refer to disorders outside the lungs or extra-pulmonary diseases such as neuromuscular and nonmuscular diseases of the chest wall.1 For example, obesity and myasthenia gravis can cause restrictive lung diseases, one through mechanical interference of lung expansion and the other through neuromuscular impedance of thoracic cage expansion. All these diseases eventually result in lung restriction, impaired lung function, and respiratory failure. This heterogenicity of disease makes establishing a single severity criterion difficult.

Laboratory testing, imaging studies, and examinations are important for determining the pulmonary disease and its course and progression. The pulmonary function test (PFT), which consists of multiple procedures that are performed depending on the information needed, has been an essential tool in practice for the pulmonologist. The PFT includes spirometry, lung volume measurement, respiratory muscle strength, diffusion capacity, and a broncho-provocation test. Each test has a particular role in assisting the diagnosis and/or follow-up of the patient. Spirometry is frequently used due to its range of dynamic physiological parameters, ease of use, and accessibility. It is used for the diagnosis of pulmonary symptoms, in the assessment of disability, and preoperatory evaluation, including lung resection surgery, assisting in the diagnosis, monitoring, and therapy response of pulmonary diseases.

A systematic approach to PFT interpretation is recommended by several societies, such as the American Thoracic Society (ATS) and the European Respiratory Society (ERS).2 The pulmonary function test results must be reproducible and meet established standards to ensure reliable and consistent clinical outcomes. A restrictive respiratory disease is defined by a decrease in total lung capacity (TLC) (< 5% of predicted value) and a normal forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC) ratio.2 Although other findings—such as a decrease in vital capacity—should prompt an investigation into whether the patient has a possible restrictive respiratory disease, the sole presence of this parameter is not definitive or diagnostic of a restrictive impairment.2-4 The assessment of severity is typically determined by TLC. Unfortunately, the severity of a restrictive respiratory disease and the degree of patient discomfort do not always correlate when utilizing just TLC. Pulmonary sarcoidosis, for example, is a granulomatous lung disease with a restrictive PFT pattern and a disease burden that may vary over time. Having a more consistent method of grading the severity of the restrictive lung disease may help guide treatment. The modified Medical Research Council (mMRC) scale, a 5-point dyspnea scale, is widely used in assessing the severity of dyspnea in various respiratory conditions, including chronic obstructive pulmonary disease (COPD), where its scores have been associated with patient mortality.1,5 The goal of this study was to document the associations between objective parameters obtained through PFT and other variables, with an established measurement of dyspnea to assess the severity grade of restrictive lung diseases.

Methods

This retrospective record review at the Veterans Affairs Caribbean Healthcare System (VACHS) in San Juan, Puerto Rico, wasconducted using the Veterans Health Information Systems and Technology Architecture to identify patients with a PFT, including spirometry, that indicated a restrictive ventilator pattern based on the current ATS/ERS Task Force on Lung Function Testing.2 Patients were included if they were aged ≥ 21 years, PFT with TLC ≤ 80% predicted, mMRC score documented on PFT, and documented diffusing capacity of the lung for carbon monoxide (DLCO). Patients were excluded if their FEV1/vital capacity (VC) was < 70% predicted using the largest VC, or no mMRC score was available. All patients meeting the inclusion criteria were considered regardless of comorbidities.

The PFT results of all adult patients, including those performed between June 1, 2013, and January 6, 2016, were submitted to spirometry, and lung volume measurements were analyzed. Sociodemographic information was collected, including sex, ethnicity, age, height, weight, and basal metabolic index. Other data found in PFTs, such as smoking status, smoking in packs/year, mMRC score, predicted TLC value, imaging present (chest X-ray, computed tomography), and hospitalizations and exacerbations within 1 year were collected. In addition, we examined the predicted values for FEV1, DLCO, and DLCO/VA (calculated using the Ayer equation), FVC (calculated using the Knudson equation), expiratory reserve volume, inspiratory VC, and slow VC. PaO2, PaCO2, and Alveolar-arterial gradients also were collected.6-9 Information about heart failure status was gathered through medical evaluation of notes and cardiac studies. All categorical variables were correlated with Spearman analysis and quantitative variables with average percentages. P values were calculated with analysis of variance.

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