Management and outcomes of acute appendicitis in pregnancy—population‐based study of over 7000 cases
Bibliographic record
Abstract
OBJECTIVE: To compare outcomes and management practices among pregnant and nonpregnant women with acute appendicitis. DESIGN: Population-based matched cohort study. SETTING: United States of America. SAMPLE: A total of 7114 women with appendicitis among 7,037,386 births. METHODS: Logistic regression analyses to calculate the odds ratio (OR) and corresponding 95% confidence intervals (95% CIs) for variables and outcomes of interest. MAIN OUTCOME MEASURES: Maternal morbidities associated with appendicitis; management practices for pregnant and age-matched nonpregnant women with appendicitis. RESULTS: There was an overall incidence of 101.1 cases of appendicitis per 100,000 births. Appendicitis was diagnosed in 35,570 nonpregnant women during the corresponding time frame. Peritonitis occurred in 20.3% of pregnant women with appendicitis, with an adjusted OR of 1.3 (95% CI 1.2-1.4) when compared with nonpregnant women with appendicitis. In pregnancy, there was an almost two-fold increase in sepsis and septic shock, transfusion, pneumonia, bowel obstruction, postoperative infection and length of stay >3 days. Whereas 5.8% of appendicitis cases among pregnant women were managed conservatively, they were associated with a considerably increased risk of shock, peritonitis and venous thromboembolism as compared to surgically managed cases. CONCLUSIONS: Compared with nonpregnant women, pregnant women with acute appendicitis have higher rates of adverse outcomes. Conservative management should be avoided given the serious risk of adverse outcomes in pregnancy.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".