Impact of Ramadan fasting on kidney function and related outcomes in patients with chronic kidney disease: a systematic review protocol
Bibliographic record
Abstract
INTRODUCTION: Fasting during the month of Ramadan is a significant Islamic religious practice that involves abstinence from food, drink and medication from dawn to dusk. As just under a quarter of the world's population identifies as Muslim, the effect of fasting on chronic conditions, such as chronic kidney disease (CKD) is a topic of broad relevance. To date, the information in this area has been mixed, with many limitations of previous studies. This study aims to synthesise the evidence of the effect of Ramadan fasting on changes on kidney function, risk factors, episodes of acute kidney injury and impact on the quality of life in patients with CKD or kidney transplant. METHODS AND ANALYSIS: A systematic review of the literature will be conducted, using electronic databases such as MEDLINE, Embase, Global Health, CINAHL and Scopus. Original research and grey literature on the effect of Ramadan fasting in adult patients with CKD or renal transplantation will be included. Two reviewers will independently screen articles for inclusion in the review and independently assess the methodology of included studies using a customised checklist. Mean difference or risk ratio will be reported for continuous or dichotomous outcomes and results will be pooled using a random-effects model where heterogeneity is reasonable. If possible, subgroups (CKD status, setting, season and risk of bias) will be analysed for effect modification with fasting and the outcomes of interest. Risk of bias will be assessed using the Downs and Black checklist. ETHICS AND DISSEMINATION: The results will be disseminated using a multifaceted approach to engage all stakeholders (patients, practitioners and community leaders). Research ethics board approval is not required as this is a systematic review of previously published research. PROSPERO REGISTRATION NUMBER: CRD42018088973.
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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 | 0.070 | 0.071 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.021 | 0.016 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.064 | 0.008 |
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".