Impact of Shorter Abstinence Periods on Semen Parameters: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
PURPOSE: The success of assisted reproductive technology (ART) relies heavily on semen parameters, and it is influenced by the length of the abstinence period. The World Health Organization (WHO) recommends a 2- to 7-day abstinence period. Even so, efficacy is still suboptimal. Thus, this study aims to determine whether shorter abstinence periods (<2 days) can improve semen parameters. MATERIALS AND METHODS: This study is a systematic review and meta-analysis. A literature search was performed across five databases: PubMed, Embase, ProQuest, Scopus, and Wiley Online Library using the PICO format. Retrieved articles were assessed according to eligibility criteria and the PRISMA flow diagram. Those eligible for quantitative analysis were assessed using forest plots. Risks of bias were tested using the Newcastle-Ottawa Scale. RESULTS: A total of 22 studies and 31,640 samples were included. Studies showed that short abstinence periods significantly reduced semen volume (mean difference [MD] -0.83, p<0.01), sperm concentration (MD -8.39, p<0.01), and DNA fragmentation (MD -3.82, p<0.01). No differences in sperm morphology were identified. Meanwhile, the overall effect for total (MD 2.30, p<0.05) and progressive motile sperm (MD 2.18, p<0.01) was significantly increased. Subgroup analysis on oligospermia patients revealed a significant increase in normal sperm morphology (MD 1.64, p<0.01) along with reduced DNA fragmentation (MD -3.30, p<0.05). However, no significant changes were seen among other sperm parameters. CONCLUSIONS: In conclusion, our findings suggest a shorter abstinence period could be beneficial due to its effect on sperm motility and DNA fragmentation. Additionally, oligospermia patients will benefit from improved sperm morphology. These findings can provide insight for future guidelines to promote a shorter abstinence period for improving ART outcomes.
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.031 |
| 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) | 0.004 | 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".