Ramadan fasting among adolescents with type 1 diabetes: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: This systematic review and meta-analysis assess the effects of Ramadan fasting in adolescents with type 1 diabetes mellitus (T1DM), on blood sugar factors such as hemoglobin A1C and problems caused by its lack of control such as hypoglycemia and DKA, and metabolic outcomes. METHODS: Electronic databases including MEDLINE, Embase, and SINOMED were searched up to February 13, 2024, without language, region, or publication time restrictions. The outcomes were Acute complications, changes in Hemoglobin A1c (HbA1c) and weight changes. Meta-analyses used random-effects models to compute weighted Relative risk (RR) and standard mean differences (SMD). And to check the risk of bias of included studies, the Newcastle-Ottawa scale was used. RESULTS: Nine studies were included, comprising 458 participants, with studies varying in quality from high to low. Meta-analysis showed no significant reduction in HbA1c levels post-Ramadan (SMD: -0.12; 95% CI: -0.38 to 0.14), indicating minimal impact on long-term glycemic control. The incidence of hypoglycemia was notably high (50.79 events per 100 observations), with hyperglycemia and diabetic ketoacidosis (DKA) also reported but less frequently. The variability in complication rates among studies was significant, reflecting the high heterogeneity across the data. Weight changes during Ramadan were minimal and not statistically significant, suggesting fasting's negligible effect on body weight among participants. CONCLUSIONS: Ramadan fasting among adolescents with T1DM does not significantly alter HbA1c levels, suggesting potential feasibility under careful monitoring and management. However, the high incidence of hypoglycemia underscores the need for vigilant glucose monitoring and tailored adjustments to diabetes management plans during fasting periods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.041 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".