Risk factors of erectile dysfunction among diabetes patients in Africa: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Erectile dysfunction in men is a common underestimated complication of diabetes mellitus, which is becoming a significant public health problem both in developing and developed countries. Erectile dysfunction threatens the well-being of clients, hence determining its risk factors and controlling it at an early stage is vital to preventing serious consequences and the burden of the disease. Therefore, this study aimed to systematically evaluate erectile dysfunction risk factors in patients with diabetes mellitus in Africa. METHODS: statistic was used to check heterogeneity between the studies. DerSimonian and Laird random-effects model was applied to estimate pooled effect size, odds ratios, and 95% confidence interval across studies. STATA version 14 statistical software was used for the meta-analysis. RESULT: Overall, 17 studies with 6002 study participants were included to identify risk factors of erectile dysfunction among diabetic patients. Duration of diabetes mellitus >10 years (AOR = 2.63; 95% CI 1.27, 5.43), age >40 years (AOR = 1.24; 95% CI: 1.03, 1.51), peripheral neuropathy (AOR = 2.34; 95% CI: 1.51, 10.72), no physical exercise (AOR = 1.63; 95% CI: 1.49, 1.78), testosterone level <8 nmol/l (AOR = 2.83; 95% CI: 1.06, 12.86), and peripheral vascular disease (AOR = 2.85, 95% CI: 1.54-5.27) were significantly associated with erectile dysfunction among diabetic patients. CONCLUSIONS: This study found that long duration of diabetes mellitus, age >40 years, testosterone deficiency, peripheral neuropathy, not involved in physical exercise, peripheral vascular disease, were significantly associated with increased risk of erectile dysfunction among diabetic patients Therefore, situation-based interventions and country context-specific preventive strategies should be developed to decrease the risk factors of erectile dysfunction among patients with diabetes mellitus.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.029 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".