Pregnant patients requiring emergency general surgery: a scoping review of diagnostic and management strategies
Bibliographic record
Abstract
BACKGROUND: About 1%-2% of pregnant patients develop conditions that require emergency general surgery (EGS). The diagnosis and management of these conditions can be challenging, as surgeons must carefully balance the needs of the pregnant patient and the developing fetus. We sought to summarize the latest literature guiding surgical management of appendicitis, benign biliary disease, bowel obstruction, and hemorrhoids in pregnant patients. METHODS: We performed a comprehensive scoping review using OVID Medline for articles published between January 2000 and June 2023 pertaining to EGS and pregnancy. RESULTS: Acute appendicitis, benign biliary disease, and bowel obstructions confer increased risk of adverse maternal and fetal obstetrical outcomes. In general, pregnant patients with acute appendicitis and cholecystitis should undergo appendectomy or cholecystectomy, respectively. The management of biliary colic has significant nuance depending on trimester. While an operative approach is favoured in the first 2 trimesters, the role of surgery in the third trimester is less clear. Nonoperative treatment of each of these diseases can result in significant maternal, and possibly fetal, morbidity. Operative management of bowel obstruction must be determined on a case-by-case basis. In all instances, a laparoscopic approach is preferred, if feasible. CONCLUSION: A thoughtful approach is crucial for surgeons and institutions caring for pregnant patients with EGS diseases. Treatment should be similar to that in nonpregnant patients, with some important considerations and modifications. Nonoperative or delayed operative management often increases adverse obstetrical events, including death.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".