Prevalence of chronic respiratory disease using case-finding tools in adults living with noncommunicable disease in low- and middle-income countries: a systematic review
Bibliographic record
Abstract
BACKGROUND: Chronic respiratory diseases (CRD) often coexist with other non-communicable diseases (NCD) and are responsible for nearly three-quarters of all deaths in low- and middle-income countries (LMIC). People living with NCD are considered at higher risk of having CRD, but the prevalence of CRD in those with other NCD in LMIC is not well described. This study aimed to identify the prevalence of CRD and/or abnormal spirometry identified through case-finding tools in adults living with NCD in LMIC. METHODS: This systematic review followed the PRISMA guidelines and included Lilacs, PubMed, Scielo, Embase and Web of Science databases. Two reviewers independently examined the titles and abstracts of studies identified from the search to determine eligibility for inclusion. Searching was carried out until May 16, 2024, and was updated in February 2025. Cross-sectional studies that used case finding tools to identify CRD in adults living with other NCD in LMIC were eligible. The studies were exported to Rayyan software, and duplicates were manually removed. Data were extracted including study characteristics, and quality was assessed using the modified Newcastle-Ottawa Scale risk of bias tool. A descriptive analysis of the prevalence of respiratory diseases and spirometric abnormalities was reported considering 95% confidence intervals. RESULTS: A total of 8,939 citations were screened based on titles and abstracts. Thirteen full-text articles were assessed for eligibility. Five studies were excluded for not providing sufficient data, two for inadequate outcome ascertainment, two for being conducted in developed countries, and one for only including patients with a previous COPD diagnosis. Three cross-sectional studies met the inclusion criteria, one conducted in India, and two in Brazil. Considering studies with a low risk of bias, the prevalence of CRD was between 1% and 5.2% in patients with hypertension. The prevalence of abnormal spirometry was between 11% and 17% in patients with coronary artery disease. CONCLUSION: The prevalence of CRD identified through case-finding tools in adults with NCD in LMIC varies according to the NCD in which it was investigated. These findings highlight the opportunity to case-find CRD by assessing people accessing care for other NCD. REGISTRATION: PROSPERO 2024 CRD42024534734.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.087 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.022 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".