An evaluation of changes over time in the semen parameters data used for the World Health Organization semen analysis reference ranges
Bibliographic record
Abstract
BACKGROUND: Previous meta-analyses concluded that there is a decline in sperm parameters over time. This conclusion might be incorrect due to inherent biases or focusing only on a single parameter - sperm concentration. OBJECTIVE: To study trends in sperm parameters over the past 20 years using data from the trials that defined the reference ranges of the World Health Organization manual. MATERIALS AND METHODS: Retrospective evaluation of the data used to define the World Health Organization reference ranges. The data from 11 studies, including 3589 participants between 1996 and 2016, were divided into three period groups based on the decade of study. Differences in semen parameters' distribution were presented in boxplot. p-values were calculated by the Kruskal-Wallis rank-sum test followed by Dunn post hoc test. Analyses were conducted using the R programming language. RESULTS: A small decrease was noted in mean sperm concentrations (88.1 million/ml, 87.6 million/ml, and 77.2 million/ml for the first, second, and third decades, respectively) (p < 0.01). However, the 5th percentile of sperm concentration for the third decade was higher than the first or second decades (18 million/ml versus 14.9 million/ml and 15 million/ml, respectively). No significant differences were noted in progressive motility over the years (p = 0.32). The percent of morphologically normal sperm decreased between the first (24.2%) and the second (12.6%) periods of the study (p < 0.001) and then increased in the third decade (14.2%) (p < 0.01). Total motile sperm count (TMC) declined between the second and third decades (189 million and 153.9 million, respectively, p < 0.001), at levels unlikely to decrease fertility. However, the 5th percentile of the TMC remained stable at 24.9, 20.8, and 20.6 million, for the first, second, and third decades respectively (p = 0.36). DISCUSSION AND CONCLUSION AND RELEVANCE: Trends in sperm parameters over the last three decades do not seem to be clinically significant.
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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 | 0.119 | 0.143 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.015 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".