Controlled Ovarian Hyperstimulation with Intrauterine Insemination Is More Successful After r-hCG Administration Than Spontaneous LH Surge.
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to evaluate whether clinical pregnancy rate is affected by timing intrauterine insemination (IUI) according to serum LH surge, r-hCG trigger, or a combination of LH surge and r-hCG trigger in controlled ovarian hyperstimulation (COH) cycles for patients with a variety of infertility etiologies. METHODS: The last 365 consecutive COH-IUI cycles performed at ONE Fertility Burlington in 2014 were reviewed and categorized according to method of IUI timing. Associations between categorical variables were analyzed using a combination of Chi-square and Fisher's Exact tests, and between continuous variables using independent sample t-tests and logistic regression to a level of significance of p<0.05. RESULTS: . 2.1%, p=0.01). CONCLUSION: In subfertile couples undergoing COH-IUI, r-hCG administration was associated with an increased clinical pregnancy rate compared with spontaneous serum LH surge. When r-hCG was administered concomitantly with a serum LH surge, this benefit was amplified. The effect appears to be of particular importance in r-FSH-medicated cycles.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".