The rapid advancement of artificial intelligence (AI) has highlighted its potential as a supportive tool in pulmonary function test (PFT) interpretation given the inherent biological variation, inter-rater variability, lack of confidence in result interpretation and restricted access within resource-constrained settings. This study aims to systematically review the published literature on the diagnostic accuracy of AI-based interpretation of PFTs and evaluate its implications for current and future clinical practice in healthcare. After screening, forty-seven publications met the inclusion criteria and were analysed to create a narrative summary. Four main over-arching themes were identified from the available literature. AI appears to consistently outperform non-specialists in diagnostic accuracy of PFTs and showed a synergistic effect when used as an adjunct in both specialist and non-specialist settings. Using AI software also had greater diagnostic accuracy than clinicians when presented with suboptimal or limited clinical information and investigations. It was also observed that the implementation of AI can address the issue of inter-rater variability by giving more consultant interpretations. Chronic obstructive pulmonary disease diagnosis saw the greatest accuracy with other conditions such as obstructive sleep apnoea showing limited evidence for the introduction of AI as a diagnostic tool. The evidence suggests that AI has the potential to play a significant role in the future of healthcare but should be used as an adjunctive tool as opposed to an independent diagnostic decision maker. One such way it could be utilised is as a triage/screening tool to help bridge the gap between primary and secondary care.

Background Chronic obstructive pulmonary disease (COPD) is a common and severely incapacitating respiratory illness that is characterized by ongoing, non-reversible airflow restrictions. Various medical treatment options include bronchodilators, anti-cholinergic drugs, and steroids. This study aimed to evaluate the effectiveness of oral roflumilast in addition to standard therapy among COPD patients to prevent exacerbations and improve pulmonary function tests (forced expiratory volume in one second (FEV1) and forced vital capacity (FVC)). Methodology This quasi-experimental study enrolled 80 moderate-to-severe COPD patients through non-probability sampling. They were divided into two groups. In Group A, participants received standard treatment as per the operational definition for six months. In Group B, participants received once-daily roflumilast, 500 µg, while maintaining background medications of COPD as per the operational definition for six months. Quantitative variables, including age, post-bronchodilator FEV1, and FVC, were expressed as mean ± SD. An independent-sample t-test was used to compare the outcome variables (FEV1 and FVC) between the two groups. The number of COPD exacerbations was analyzed using an appropriate statistical test, such as the Mann-Whitney U test. All the data were analyzed using SPSS version 28.0. Results Both groups showed a significant increment in mean FEV1 and FVC from day zero to six months; however, mean FEV1 and FVC were significantly higher for Group B patients from the fourth to sixth months. A decreasing trend was observed in the frequency of exacerbations in both groups. At the fifth and sixth months of treatment, Group B patients showed significantly lower frequency of exacerbations compared to Group A patients. Conclusions Oral roflumilast as an adjunct to standard COPD therapy improved clinical outcomes by enhancing pulmonary function (particularly FEV1) and reducing exacerbation frequency. Reduction in recurrent exacerbations may contribute to better symptom control, improved quality of life, and decreased healthcare burden. Therefore, roflumilast 500 µg once daily may be considered a useful add-on option in selected COPD patients, although larger studies with longer follow-up are warranted to establish long-term benefits.

This interdisciplinary longitudinal study examines the association between PM2.5 levels at sites downwind of a coal-fired thermal power plant (TPP) near the India-Bangladesh border and respiratory health in the exposed population, assessed using spirometry and fractional exhaled nitric oxide levels. Pulmonary function tests indicate significantly worse lung health at downwind sites in both India and Bangladesh compared with an upwind location. With averaged forced expiratory volume in one second (FEV1) values < 80% of predicted, evidence of preserved ratio impaired spirometry (PRISm), and significantly lower forced expiratory flow between 25% and 75% of vital capacity (FEF25-75), the population at the Indian downwind site is clearly at risk of developing obstructive pulmonary and related diseases. Although PM2.5 concentrations decline sharply during the monsoon across all sites, this does not translate into a recovery in lung health at the downwind location, consistent with chronic, irreversible effects potentially related to long-term exposure to TPP-associated PM2.5. Moreover, poorer socioeconomic conditions and exposure to emissions from biomass-based indoor cooking are associated with exacerbated respiratory effects. Overall, the study advocates transitioning to cleaner fuels for power generation and household use and recommends locating power plants away from densely populated areas to minimize health impacts.