Ramadan fasting for patients with chronic respiratory diseases: a systematic review and consensus recommendations for healthcare professionals
Bibliographic record
Abstract
Background: Ramadan, observed by nearly 2 billion Muslims worldwide, involves fasting from dawn to sunset, which can present challenges for individuals with chronic respiratory diseases due to altered medication regimens and oral intake restrictions. This study aimed to synthesise current evidence and develop consensus recommendations for managing asthma, COPD, interstitial lung disease (ILD) and bronchiectasis during Ramadan. Methods: A comprehensive search of electronic databases including MEDLINE, Embase and Google Scholar was conducted following a pre-specified protocol (PROSPERO identifier number CRD42024532759) to identify studies on Ramadan fasting outcomes in individuals with chronic respiratory diseases. The findings informed consensus recommendations stratified by the risk of adverse outcomes using International Diabetes Federation and the Diabetes and Ramadan risk assessment criteria. An international expert group of medical and religious experts refined these guidelines, achieving consensus approval. Results: 11 studies met the inclusion criteria, primarily addressing asthma and COPD, with no relevant studies on ILD or bronchiectasis. The studies indicated that fasting did not significantly impact hospitalisation rates or lung function tests in individuals with stable asthma and COPD. However, small sample sizes and methodological limitations restricted generalisability. 19 recommendations were developed to support patients considering fasting, emphasising pre-Ramadan consultations, individualised risk assessments, and adjustments to medication regimens. Conclusion: This systematic review highlights the need for larger, well-designed studies to understand Ramadan fasting implications across chronic respiratory diseases. The developed recommendations provide a structured approach to assess fasting risks, ensuring informed and safe guidance during Ramadan. Future research should address identified gaps, supporting evidence-based guidelines that reconcile medical and religious considerations.
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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 | 0.051 | 0.144 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.017 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".