Thromboembolism following cesarean section: a retrospective study
Bibliographic record
Abstract
OBJECTIVES: As thromboembolism (TE) continues to be one of the principal causes of death in obstetrical patients and as the postpartum period is associated with the highest risk for TE, we sought to determine the risk factors associated with TE following cesarean section (CS). METHODS: A retrospective analysis of patients who had CS at a large tertiary referral center was conducted. Patients were identified through hospital medical records and were contacted approximately 1 year following their CS. Medical records and a questionnaire were used to identify features that were potentially associated with TE. Univariate analysis was used to determine the risk associated with these characteristics. RESULTS: A total of 2206 patients had a CS, of which 1377 (62%) participated. Of the respondents, 137 patients received heparin (94% received a prophylactic dose, 6% received a therapeutic dose) and the remainder, 1233 patients, did not receive heparin. Seven patients (0.5%) developed a TE and 86% developed a TE within 7 days of CS. The odds ratio (OR) for TE for women with hypertension prior to pregnancy compared to patients who did not receive anticoagulation was 21.28 [95% confidence interval (CI) 4.64-90.13] and for patients who had varicose veins with superficial thrombophlebitis when compared to patients who had received heparin postpartum was 21.01 (95% CI 1.55-288.24). DISCUSSION: Hypertension and the presence of varicose veins were associated with TE following CS. Larger cohort analyses are required to confirm these associations so that risk scores incorporating these characteristics may accurately predict the occurrence of TE.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".