Exacerbation of Migraines Following Robotic Surgery for Endometrial Carcinoma
Bibliographic record
Abstract
Objective: Robotic hysterectomies are becoming increasingly common in the United States. Although benefits exist, risks are also present. The purpose of this study was to see what percentage of women with migraine headaches had a post-operative exacerbation.Study design: Records were examined for the diagnosis of migraine headaches as well as post-operative diagnosis of a headache. Records were also examined for age, estimated blood loss, total skin to skin operative time and body mass index.Results: Surgeries and records for 100 women were examined. Only 6% of women complained of post-operative headaches. However, 45% of women with history of migraines complained of post-operative headaches (p <0.001). Age was the only significant factor with women having post-operative headaches being significantly younger (p = 0.009).Conclusion: Post-operative headaches were more common in women with a pre-operative history of migraine headaches than in those without a history. Patients with a history of migraines should be warned of this risk.
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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 | 0.000 | 0.002 |
| 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) | 0.003 | 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".