Examining hypoglycemia risk with systemic fluoroquinolone use: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: Hypoglycemia associated with fluoroquinolone use has been observed in several case reports and observational studies. Study Design: Systematic review and meta-analysis. Methods: Two independent reviewers screened studies identified from a literature search conducted using PubMed (Medline), Cochrane Library, and Ovid Embase databases from inception to June 24, 2024. Eligible studies included randomized controlled trials (RCTs), cohort studies, and case-control studies that reported quantitative findings regarding hypoglycemia and had a non-fluoroquinolone antimicrobial comparator. Random effects models were used to estimate pooled odds ratios (ORs) and 95 % confidence intervals (CIs) for the occurrence of hypoglycemia in people prescribed fluoroquinolones (at a class and individual agent level) versus active comparators for RCTs and observational studies. Subgroup analysis by diabetes status, concurrent use of hypoglycemic agents, renal impairment, and age were conducted. Results: There were 1771 citations screened of which 21 studies (9 RCTs and 12 observational) were included. Compared to other antimicrobials, fluoroquinolones were associated with an overall significantly increased risk of hypoglycemia across the RCTs (9 studies, Pooled OR = 1.84; 95 % CI 1.05–3.21; I2 = 0 %). Findings from observational studies showed an increased risk of hypoglycemia with gatifloxacin (5 studies, Pooled OR = 2.87; 95 % CI 1.65–4.99; I2 = 65 %) and levofloxacin (7 studies, Pooled OR = 1.90; 95 % CI 1.46–2.47; I2 = 75 %), but not with ciprofloxacin (6 studies, Pooled OR = 1.24; 95 % CI 0.97–1.59; I2 = 76 %) nor moxifloxacin (5 studies, Pooled OR = 1.28; 95 % CI 0.83–1.97; I2 = 67 %) compared to non-fluoroquinolone antimicrobials. Limitations: Inconsistencies in the definition of hypoglycemia, heterogeneity between observational studies, and hypoglycemia was not a primary outcome in any RCTs. Conclusion: The results of this systematic review and meta-analysis showed a significant association between fluoroquinolones and an increased risk of hypoglycemia, although there appears to be intraclass variation. As hypoglycemia is a serious adverse drug event associated with cognitive and cardiovascular complications, fluoroquinolones should be prescribed cautiously, particularly when safer antibiotic alternatives are available.
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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 | 0.020 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.051 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".