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Record W2548290049 · doi:10.1093/humrep/dew276

Use of testicular sperm for ICSI in oligozoospermic couples: how far should we go?

2016· review· en· W2548290049 on OpenAlexaff
Armand Zini, Phil Bach, Ahmed Almalki, Peter N. Schlegel

Bibliographic record

VenueHuman Reproduction · 2016
Typereview
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsMcGill University
Fundersnot available
KeywordsSpermSperm RetrievalIntracytoplasmic sperm injectionAndrologyTesticular sperm extractionMale infertilityInfertilitySemenGynecologyPregnancyMedicineBiologyObstetricsGenetics

Abstract

fetched live from OpenAlex

In 1992 and subsequently, several reports indicated that ICSI was a successful technique to achieve clinical pregnancy and live birth using spermatozoa with severely impaired characteristics. The initial optimism over the ability of ICSI to overcome significant sperm abnormalities was later tempered by the findings of more recent publications suggesting that some sperm deficits may not be as effectively treated with ICSI. In search for effective treatment for couples with severe male factor, a number of small retrospective and prospective studies have reported high pregnancy and live birth rates using testicular sperm for men with necrozoospermia, cryptozoospermia and oligozoospermia with or without elevated sperm DNA damage. Although the data suggest that there may be some benefit in performing testicular sperm retrieval (TSR)-ICSI in select groups of non-azoospermic infertile men, there are potential risks involved with TSR. Clinicians should balance these risks prior to the recommendation of TSR-ICSI on the result of a semen analysis or sperm DNA test alone. Careful evaluation and management of male factor infertility is important. The use of TSR-ICSI in the absence of specific sperm DNA defects is still experimental.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
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 head0.235
GPT teacher head0.374
Teacher spread0.140 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations37
Published2016
Admission routes1
Has abstractyes

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