Network Meta-Analysis of the Efficacy of Acupuncture, Alpha-blockers and Antibiotics on Chronic Prostatitis/Chronic Pelvic Pain Syndrome
Bibliographic record
Abstract
Alpha-blockers and antibiotics are most commonly used to treat chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) in clinical practice. Currently, increasing evidence also suggests acupuncture as an effective strategy. This network meta-analysis intended to assess the comparative efficacy and safety of acupuncture, alpha-blockers and antibiotics for CP/CPPS. Twelve trials involving 1203 participants were included. Based on decreases in the National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) score, a network meta-analysis indicated that electro-acupuncture (standard mean difference [SMD]: 4.29; 95% credible interval [CrI], 1.96-6.65), acupuncture (SMD: 3.69; 95% CrI, 0.27-7.17), alpha-blockers (SMD: 1.85; 95% CrI, 1.07-2.64), antibiotics (SMD: 2.66; 95% CrI, 1.57-3.76), and dual therapy (SMD: 3.20; 95% CrI, 1.95-4.42) are superior to placebo in decreasing this score. Additionally, electro-acupuncture (SMD: 2.44; 95% CrI, 0.08-4.83) and dual therapy (SMD: 1.35; 95% CrI, 0.07-2.62) were more effective than alpha-blockers in decreasing the total NIH-CPSI total score. Other network meta-analyses did not show significant differences between interventions other placebo. The incidence of adverse events of acupuncture was relatively rare (5.4%) compared with placebo (17.1%), alpha-blockers (24.9%), antibiotics (31%) and dual therapy (48.6%). Overall, rank tests and safety analyses indicate that electro-acupuncture/acupuncture may be recommended for the treatment of CP/CPPS.
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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 | 0.015 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.042 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| 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".