Effect of SARS-CoV-2 infection on semen parameters
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Bibliographic record
Abstract
INTRODUCTION: In this study, we aimed to assess the effect of SARS-CoV-2 infection on semen parameters in one group of patients before and after infection. METHODS: Patients were screened if they had a semen analysis performed between October 1, 2019, and December 1, 2020, in the assisted reproduction unit and later had positive polymerase chain reaction (PCR) test for SARS-CoV-2 infection. The patients' semen parameters were recorded before and after SARS-CoV-2 infection, along with degrees of SARS-CoV-2 infection, dates of SARS-CoV-2 infection, durations between the treatment for SARS-CoV-2 infection and the second semen analysis, time of symptom onset, duration of their symptoms, ages, comorbidities, and any medications patients were taking. RESULTS: Forty-one patients were included in the study. The mean age of the patients was 31.29±5.95 years. The mean duration from first semen analysis to the PCR test was 7.74±3.03 months. The mean duration between the PCR test and later semen analysis was 2.35±1.35 months. The median sperm concentration for the patients before and after SARS-CoV-2 infection were 24 mil/ml and 13 mil/ml, respectively (p<0.001). The normal morphology percentage before infection was 3.16±0.92, while it was 2.44±1.04 after infection (p=0.011). In 26 patients, the period from the time of infection to the second semen analysis was over 70 days, while this period was less than 70 days in the other 15 patients. In both patient groups, a significant decrease was detected in the sperm concentrations and total sperm count. CONCLUSIONS: In the semen samples we assessed, we observed a significant decrease in the mean sperm concentration, total sperm count, and mean percentage of samples with normal morphology after SARS-CoV-2 infection.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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