ArticleJournal of family medicine and primary care2025
A study to correlate the association of Gender, Age, Physiology (GAP) index and radiological patterns in interstitial lung disease.
Article in Journal of family medicine and primary care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Interstitial lung disease (ILD) encompasses a heterogeneous group of disorders characterized by inflammation and fibrosis of lung tissue, leading to impaired gas exchange and respiratory failure. The GAP index, based on gender, age, and pulmonary function, predicts mortality and disease severity in patients with ILD. High-resolution computed tomography (HRCT) is a critical diagnostic tool that provides detailed information on lung morphology and disease extent. This study aims to investigate the relationship between HRCT patterns and the GAP index in patients with ILD, enhancing disease staging and prognostication. Objectives: 1. To identify various radiological patterns in ILD patients using HRCT of the thorax. 2) To correlate these radiological patterns with the GAP index and verify the relationship mentioned above. Materials and Methods: This retrospective observational study analyzed data from 154 patients with ILD treated at Victoria Hospital, Bangalore Medical College and Research Institute, from January 2021 to September 2023. The inclusion criteria included patients aged ≥ 18 years diagnosed with ILD based on the ATS/ERS criteria. Thoracic HRCT was performed using a Philips Ingenuity 128-slice CT scanner, and pulmonary function tests (PFTs) were conducted using a Power cube Diffusion Plus spirometer. The GAP score was calculated, and the HRCT patterns were compared with the GAP stages. Statistical analyses were performed using IBM SPSS Statistics software. Results: The study population had a mean age of 55.5 years, consisting of 68 males and 86 females. Shortness of breath (97.4%) and cough (87.7%) were the most common symptoms. Hypertension (31.2%) and diabetes mellitus (28.6%) were the most common comorbidities observed. The prevalence of definitive UIP sharply increased in stage 3 (58.8%) compared to stage 1 (9.5%) and stage 2 (41.5%), with a highly significant Conclusion: This study revealed a significant correlation between particular HRCT patterns and GAP index stages in patients with ILD, highlighting the importance of honeycombing and traction bronchiectasis as indicators of advanced disease. This approach is advantageous in both resource-limited settings, where HRCT availability is limited, and in advanced medical centers, as it can help minimize the need for frequent CT scans.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.