The Impact of COVID‐19 Vaccines on Male Semen Parameters: A Retrospective Cohort Study
Why this work is in the frame
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Bibliographic record
Abstract
The emergence of SARS‐CoV‐2 and the subsequent COVID‐19 pandemic necessitated the development of adequate vaccines. Despite vaccines being demonstrated to be safe and effective for preventing severe disease and death, vaccine hesitancy remains. Reasons include concerns over adverse effects on male fertility, which have not been widely investigated. Therefore, this study is aimed at determining the impact of COVID‐19 vaccination on semen parameters in a retrospective cohort study of South African males undergoing fertility assessment. The patients for this study were adult men who have previously undergone routine semen analysis for fertility assessment at Androcryos Andrology Laboratory (Johannesburg, South Africa) between March 2021 and March 2022. They also received vaccination within 3 months following a semen analysis and underwent a second semen analysis any time post‐COVID‐19 vaccination. From 277 records analysed, 46 patients met the inclusion criteria, receiving the Pfizer‐BioNTech (BNT162b1) (63%), Johnson and Johnson (JNJ‐78436735/Ad26.COV2S) (34.8%), and the AstraZeneca (AZD1222) (2.2%) vaccines. Sperm concentration significantly increased postvaccination ( P = 0.0001), with no significant changes in semen pH, volume, total sperm count, progressive motility, normal sperm morphology, or chromatin condensation. Results were not influenced by age, type of vaccine received, and the number of days following vaccination, as depicted by multiple regression analysis. In conclusion, there is no evidence of a negative impact of COVID‐19 vaccination on male semen parameters, which is consistent with the emerging literature on COVID‐19 vaccination and male fertility. COVID‐19 vaccinations should not be dismissed based on fear of adverse effects on male fertility parameters.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it