Does using testicular sperm retrieval rather than ejaculated spermatozoa improve reproductive outcomes in couples with previous <scp>ART</scp> failure and poor ovarian response? A case‐controlled study
Bibliographic record
Abstract
The objective of this study was to assess whether testicular-retrieved spermatozoa improve reproductive outcomes compared to fresh ejaculate in women with poor ovarian response and a history of previous ART failure. The study was performed as a retrospective case-control study at a university-based reproductive center in Montreal, Quebec, Canada. Eighteen poor-responder patients were matched 3 : 1 with 54 controls. Poor responders were defined as those with ≤3 oocytes retrieved at oocyte pickup. Cases were identified as poor responders, and only those with previous IVF failure(s) as an indication for testicular-retrieved spermatozoa were included. Controls were age and cycle attempt number matched. All patients were included only once. From January 1, 2009 to December 31, 2015, all patients and controls underwent an IVF cycle using ICSI with either testicular spermatozoa or ejaculated spermatozoa, respectively. Outcomes included live birth rate, pregnancy rate, miscarriage rate, oocyte number, and embryo transfer (ET) day. The results showed live birth rates, pregnancy rates, and miscarriage rates were similar. There were fewer day 2 ETs (8.5% vs. 48.6%, p = 0.01) and more day 5 blastocyst transfers (25.0% vs. 5.4%, p = 0.05) in the testicular sperm retrieval group compared to controls and thus an overall suggestion of better embryo quality in the testicular sperm group. Overall, however, the use of testicular sperm retrieval appears to add little. Women with poor ovarian response typically have a poor prognosis with respect to live birth rates, and this is further supported in this study. The suggestion of better embryo quality in the testicular-retrieved sperm group would need to be further assessed in a larger multicentered study.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".