A systematic review of the effect of COVID-19 on semen parameters
Bibliographic record
Abstract
Background and objectives: Since the outbreak of COVID-19, more and more studies have proved that it has an impact on the male reproductive system. The purpose of this article is to investigate the effects of COVID-19 on male semen parameters, further analyze the incidence and risk factors of diseases related to semen parameters, and put forward to corresponding preventive measures. Methods: Retrieved from PubMed, Embase, The Cochrane Library, Web of Science, Clinicaltrails, CNKI, CBM, Wanfang Database and VIP to collect research on the effects of COVID-19 on the male reproductive system. The literature search was conducted until January 2022. In strict accordance with the inclusion and exclusion criteria, two researchers independently screened the literature and comprehensively analyzed five cohort studies on the impact of COVID-19 on male reproductive system. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the included cohort studies, and Revman 5.4.1 was applied for statistical analysis. Results: Semen volume (RR = -0.10; 95% CI: 0.45, 0.26; P = 0.60), there was no significant difference between the test group and the control group; Sperm count (RR = -45.28; 95% CI: 66.38, 24.19; P = 0.0001), the sperm count of the COVID-19 test group was lower than that of the control group, and the difference was statistically significant; Sperm concentration (RR = -15.65 × 106; 95%CI: 31.52 × 106, 0.21 × 106; P = 0.05), there was no significant difference between the test group and the control group; progressive sperm motility (RR = 4.31; 95% CI: 4.62, 13.24; P = 0.34), there was no effect on progressive sperm motility in the COVID-19 test group compared with the control group. Conclusions: COVID-19 can reduce semen quality and affect male fertility. However, due to the limitations of this study, this conclusion needs to be further verified by large-sample, high-quality prospective cohort studies on the long-term effects of COVID-19 on male reproductive function.
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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 | 0.009 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".