Association of insulin resistance surrogate indices and erectile dysfunction: a systematic review and meta-analysis
Bibliographic record
Abstract
Erectile dysfunction (ED) has been linked to insulin resistance (IR), with various surrogate indices being used to assess this association. This systematic review and meta-analysis aimed to evaluate the relationship between IR indices and the incidence and severity of ED. A comprehensive search across PubMed, Embase, Web of Science, and Scopus was carried out. Required data were extracted and meta-analyzed. The Newcastle–Ottawa Scale (NOS) was employed to evaluate the studies' risk of bias. Sensitivity analyses and meta-regressions were conducted to explore heterogeneity and the impact of confounding variables. Seventeen studies with a total of 3810 patients with ED and 8252 without ED were included. Meta-analysis revealed that males with ED had significantly higher levels of Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) (SMD = 0.59, 95% CI [0.15, 1.03], I 2 = 82%, P < 0.01), Triglyceride-Glucose Index (TyG) (SMD = 0.53, 95% CI [0.31, 0.75], I 2 = 69%, P < 0.01), and Visceral Adiposity Index (VAI) (SMD = 0.45, 95% CI [0.25, 0.64], I 2 = 76%, P < 0.01) compared to those without ED. However, there was no significant correlation between a one-unit increase in HOMA-IR (OR = 0.63, 95% CI [0.03, 13.69], I 2 = 91%, P = 0.77) or TyG (OR = 0.53, 95% CI [0.02, 11.53], I 2 = 88%, P = 0.68) and the odds of ED. Additionally, a one-unit increase in VAI was associated with more severe ED (SMD = 0.34, 95% CI [0.03, 0.64], I 2 = 16%, P = 0.03). The diagnostic accuracy of these indices varied. The results indicate a significant connection between insulin resistance and erectile dysfunction, as shown by HOMA-IR, TyG, and VAI. Yet, their usefulness in predicting ED is restricted because of significant differences and inconsistencies in diagnostic precision. More research is required to determine the clinical importance of these indices in treating ED.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.038 |
| Bibliometrics | 0.007 | 0.008 |
| 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) | 0.003 | 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".