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Record W4381619609 · doi:10.1093/humrep/dead093.016

O-016 Sperm motility has declined between 2017 and 2022 among candidate sperm donors in Denmark

2023· article· en· W4381619609 on OpenAlexaff
Robert Montgomerie, E. Duane Lassen, A B Skytte, Allan Pacey

Bibliographic record

VenueHuman Reproduction · 2023
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsQueen's University
Fundersnot available
KeywordsSpermSemenSperm qualityFertilityBiologySperm motilitySemen analysisSemen qualityAndrologySperm bankReproductionDemographyMedicineInfertilityPopulationEcologyGeneticsPregnancy

Abstract

fetched live from OpenAlex

Abstract Study question Has sperm quality among candidate sperm donors in Denmark changed in recent years (2017-2022)? Summary answer Although sperm concentration of candidate donors did not change, sperm quality (motility) declined by ∼35% after controlling for age and other potential confounds. What is known already Questions remain about whether human sperm quality has declined in recent decades. Whilst some studies support this trend, others dispute it due to potential biases in the populations studied or the different methodological approaches to measuring sperm quality. Resolution of this issue is important because of the implications for human fertility, as well as for those involved in the recruitment of donors for use in Medically Assisted Reproduction. Study design, size, duration We analyzed the semen quality of 6,774 candidate sperm donors attending for their first semen analysis at Cryos International from 2017 to 2022 at four cities in Denmark: Aarhus, Aalborg, Copenhagen, and Odense. We analyzed only the first sperm sample, whether or not the candidate was eventually accepted as a donor. All donor candidates were between 18 and 46 years old and lived in or near these four cities. Participants/materials, setting, methods Ejaculates were examined within one hour of production. Semen volume (mL) was estimated by weight and both total sperm concentration (106/mL) and the concentration of grade A and B spermatozoa were measured using the same protocols and CASA-system across all years at each site. Analyses were controlled for age, site, ejaculate volume, and the average monthly temperature when the ejaculate was produced. We used longitudinal data from accepted donors to test for methodological biases. Main results and the role of chance From 2017 to 2022, there was no evidence of changes in either semen volume (median = 3.5 mL) or sperm concentration (median = 58 million/mL) in the ejaculates of candidate donors. There was, however, clear evidence of a decline in the concentration (and total number) of grade A and B motile sperm. For the average candidate sperm donor that we studied, the concentration of grade A sperm declined from 5.15 [95% CL: 4.18, 6.34] million/mL in 2018 to 3.33 [2.71, 4.08] million/mL in 2022. This corresponds, for example, to a predicted decline in sperm quality of ∼35% for a 25-year-old candidate from Aarhus in a month when the average daily high temperature was 18.5 °C. The same pattern was evident from all four cities, but candidates at Aarhus had lower overall sperm quality (grade A sperm motility) than candidates at the other three cities. Analysis of the longitudinal data from repeated donations from all 'accepted' donors during this same period (2017 – 2022), allowed us to rule out methodological factors (sperm collection, CASA, statistical anomalies) that might have influenced these findings. Limitations, reasons for caution We cannot rule out the possibility that men with poor sperm quality were more likely to apply to be donors during the global pandemic, or that the lifestyles of candidate donors had changed during this period because of lockdowns or changes in work patterns. Wider implications of the findings Candidate sperm donors are a useful population in which to monitor changes in human semen quality over time. The results may have implications for human fertility and the recruitment of sperm donors, where motile sperm concentration is an essential selection criterion. Trial registration number not applicable

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.761

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.087
GPT teacher head0.351
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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