A study on the relationship of dyspnoea score, high-resolution computed tomographic scan, and pulmonary function tests in the evaluation of connective tissue disease-related interstitial lung disorders

Abstract

Background: Connective tissue diseases (CTDs) are one of the most common causes among the known etiologies of interstitial lung disorders (ILDs). Parenchymal involvement in CTDs confers a significant risk of mortality as well as morbidity with serious consequences. The present study aims to correlate dyspnoea scores with high-resolution computed tomography (HRCT) changes, spirometry, diffusing capacity for carbon monoxide (DLCO), and 6-Minute Walk Test (6MWT) among different types of CTD-ILDs. Methodology: The hospital-based observational, cross-sectional study was performed over 1 year among 60 patients with CTD-ILDs. The dyspnoea score (modified Medical Research Centre grade), HRCT thorax pattern with a percentage of involvement, and functional parameters (forced vital capacity (FVC), DLCO, 6-Minute Walking Distance (6MWD)) were compared among different CTD-ILD groups. Results were computed using Microsoft Excel. Results: Systemic sclerosis (SSc) was the most common cause of CTD-ILDs (43%) with a predominant nonspecific interstitial pneumonia pattern (71% of all SSc-ILDs), followed by rheumatoid arthritis (RA) (30%) with a predominance of usual interstitial pneumonia (55% of all RA-ILDs). Other cases included dermatomyositis (6%), mixed connective tissue disease (6%), and Sjögren disease (3%). Three percent of the patients remained unclassified. The difference in the HRCT pattern was seen between RA- and SSc-ILDs, which was statistically significant (p = 0.00035). The mean FVC was 1.68L and the mean 6MWD was 316 m. 6MWD showed a positive correlation with FVC and DLCO (r = 0.67 and 0.78). The percentage of the HRCT thorax involvement showed a negative correlation with FVC and 6MWD but not in linear regression (p = 0.000281 and 4.27e–08, r = –0.45 and −0.67, confidence interval (CI) 95%). DLCO had a negative linear regression with HRCT thorax involvement (r = –0.93, CI 95%) showing superiority over other functional parameters. Conclusion: The integration of clinical data, the extent of involvement in HRCT thorax, and physiological parameters, especially DLCO, provide a holistic approach to better understand CTD-ILDs.

Keywords

• ctd-ild; dlco; structural-functional corelation