Oocyte retrieval of few follicles does not require analgesia: a large-scale multicentre pain analysis
Bibliographic record
Abstract
RESEARCH QUESTION: What is the pain intensity of oocyte retrieval (OCR) without anaesthesia and analgesia in women with a low or medium number of follicles? DESIGN: Multicentre observational study analysing IVF cycles without anaesthesia and analgesia in seven IVF centres in Germany and Switzerland between January 2022 and March 2023. In total, 2290 cycles of natural cycle IVF or minimal stimulation IVF from 1039 patients were recorded. Pain score was assessed using a VAS graded 0 to 10. A descriptive analysis was conducted, followed by a statistical evaluation using a linear mixed model to analyse the effect on the pain score of the number of oocytes retrieved and the number of repeated IVF cycles. RESULTS: The number of oocytes retrieved varied from 0 to 16 (IQR 1-2). Pain score varied from 0 to 10, with a median pain score of 3.0 (IQR 2-4), defined as 'mild' pain. Compared with a reference value of aspirations with one oocyte, the pain score increased slightly by 0.5 points if no oocyte was retrieved, by 0.42 points if two to five oocytes were retrieved and by 1.14 points if six or more oocytes were retrieved, all with little clinical relevance. Pain decreased slightly with repeated aspirations (-0.05 points per cycle) (P = 0.028). The complication rate requiring hospitalization per aspiration was less than 0.1%. CONCLUSION: Pain intensity during OCR of one or few follicles is mild. Therefore, OCR can be offered without anaesthesia and analgesia to reduce aspiration time and cost.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".