Sperm Vitality and Necrozoospermia: Diagnosis, Management, and Results of a Global Survey of Clinical Practice
Bibliographic record
Abstract
Sperm vitality testing is a basic semen examination that has been described in the World Health Organization (WHO) Laboratory Manual for the Examination and Processing of Human Semen from its primary edition, 40 years ago. Several methods can be used to test sperm vitality, such as the eosin-nigrosin (E-N) stain or the hypoosmotic swelling (HOS) test. In the 6th (2021) edition of the WHO Laboratory Manual, sperm vitality assessment is mainly recommended if the total motility is less than 40%. Hence, a motile spermatozoon is considered alive, however, in certain conditions an immotile spermatozoon can also be alive. Therefore, the differentiation between asthenozoospermia (pathological decrease in sperm motility) and necrozoospermia (pathological decrease in sperm vitality) is important in directing further investigation and management of infertile patients. The causes leading to necrozoospermia are diverse and can either be local or general, testicular or extra-testicular. The andrological management of necrozoospermia depends on its etiology. However, there is no standardized treatment available presently and practice varies among clinicians. In this study, we report the results of a global survey to understand current practices regarding the physician order of sperm vitality tests as well as the management practices for necrozoospermia. Laboratory and clinical scenarios are presented to guide the reader in the management of necrozoospermia with the overall objective of establishing a benchmark ranging from the diagnosis of necrozoospermia by sperm vitality testing to its clinical management.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".