Analgesia for emergency laparotomy: a systematic review
Bibliographic record
Abstract
Aims/Background Poorly controlled pain is common after emergency laparotomy. It causes distress, hinders rehabilitation, and predisposes to complications: prolonged hospitalisation, persistent pain, and reduced quality of life. The aim of this systematic review was to compare the relative efficacies of pre-emptive analgesia for emergency laparotomy to inform practice. Methods We performed a search of MEDLINE, MEDLINE In-Process, Embase, PubMed, Web of Science and SCOPUS for comparator studies of preoperative/intraoperative interventions to control/reduce postoperative pain in adults undergoing emergency laparotomy (EL) for general surgical pathologies. Exclusion criteria: surgery including non-abdominal sites; postoperative sedation and/or intubation; non-formal assessment of pain; non-English manuscripts. All manuscripts were screened by two investigators. Results We identified 2389 papers. Following handsearching and removal of duplicates, 1147 were screened. None were eligible for inclusion, with many looking at elective and/or laparoscopic surgeries. Conclusion Our findings indicate there is no evidence base for pre-emptive analgesic strategies in emergency laparotomy. This contrasts substantially with elective cohorts. Potential reasons include variation in practice, management of physiological derangement taking priority, and perceived contraindications to neuraxial techniques. We urge a review of contemporary practice, with analysis of clinical data, to generate expert consensus.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".