The association between prediabetes and male sexual dysfunction: an updated meta-analysis
Bibliographic record
Abstract
BACKGROUND: Prediabetes, defined as impaired fasting glucose (IFG) or impaired glucose tolerance (IGT), is recognized as an increasing metabolic disorder globally. Although its vascular and metabolic implications are well established, the link between prediabetes and male sexual dysfunction is uncertain. This meta-analysis was performed to summarize available evidence on the relationship between prediabetes and sexual dysfunction in men. METHODS: A systematic literature search of PubMed, Embase, and Scopus from inception to July 2025 was undertaken to retrieve observational studies reporting sexual dysfunction outcomes (erectile dysfunction or premature ejaculation) in prediabetic men. The eligibility criteria were adult men with prediabetes and comparative data with normoglycemic controls. Studies were screened by two independent reviewers who also extracted data and evaluated study quality using the Newcastle-Ottawa Scale (NOS). Meta-analysis with random effects model was employed to combine effect sizes and assess heterogeneity on the basis of I² statistic. Funnel plots and Egger's test were employed to investigate publication bias. GRADE approach was applied to grade the certainty of the evidence according to risk of bias, inconsistency, indirectness, imprecision, and publication bias. RESULTS: A total of ten studies with 11,000 participants were available for analysis. Combined odds ratio (OR) of sexual dysfunction in prediabetic men compared to normoglycemic men was 2.50 (95% CI: 1.35-4.64), indicating significant association with high heterogeneity (I² = 87.9%, p<0.001). Funnel plot asymmetry was checked by visual inspection and confirmed by Egger's regression test for publication bias, which was not significant (p=0.275). According to GRADE, the quality of evidence was generally low, downgraded for high heterogeneity and imprecision but upgraded for large effect size. CONCLUSIONS: We found that men with prediabetes have approximately 2.5-fold higher odds of sexual dysfunction than men with normoglycemia. Due to the high pooled effect size, although with low certainty of evidence, additional high-quality prospective studies are needed to replicate findings and explore the underlying mechanisms.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.054 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| 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".