Postoperative Nonsteroidal Anti-inflammatory Drug Use and Intestinal Anastomotic Dehiscence: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Nonsteroidal anti-inflammatory drugs are commonly used analgesics in colorectal surgery. Controversy exists regarding the potential association between these drugs and anastomotic dehiscence. OBJECTIVE: This study aimed to determine whether postoperative nonsteroidal anti-inflammatory drug use is associated with intestinal anastomotic dehiscence. DATA SOURCES: PubMed, EMBASE, CENTRAL, and references of included articles were searched without date or language restriction. STUDY SELECTION: Randomized controlled trials and observational studies that compared postoperative nonsteroidal anti-inflammatory drug use with nonuse and reported on intestinal anastomotic dehiscence were selected. INTERVENTION: The use of postoperative nonsteroidal anti-inflammatory drugs relative to placebo or nonuse was investigated. MAIN OUTCOME MEASURES: Risk ratios and adjusted or unadjusted odds ratios for anastomotic dehiscence were pooled across randomized controlled trials and observational studies using DerSimonian and Laird random-effects models. RESULTS: Among 4395 citations identified, 6 randomized controlled trials (n = 473 patients) and 11 observational studies (n > 20,184 patients) were included. Pooled analyses revealed that nonsteroidal anti-inflammatory drug use was nonsignificantly associated with anastomotic dehiscence in randomized controlled trials (risk ratio, 1.96; 95% CI, 0.74-5.16; I = 0%) and significantly associated with anastomotic dehiscence in observational studies (OR, 1.46; 95% CI, 1.14-1.86; I = 54%). In stratified analyses of observational study data, the pooled OR for anastomotic dehiscence was statistically significant for studies of nonselective nonsteroidal anti-inflammatory drug use (6 studies; > 4900 patients; OR, 2.09; 95% CI, 1.65-2.64; I = 0%), but was not statistically significant for studies of cyclooxygenase-2 selective nonsteroidal anti-inflammatory drug use (3 studies; >697 patients; OR, 1.34; 95% CI, 0.78-2.31; I = 0%). LIMITATIONS: Studies varied by patient selection criteria, drug exposures, and definitions of anastomotic dehiscence. Analyses of randomized controlled trials and cyclooxygenase-2 selective nonsteroidal anti-inflammatory drugs were potentially underpowered. CONCLUSIONS: Pooled observational data suggest an association between postoperative nonsteroidal anti-inflammatory drug use and intestinal anastomotic dehiscence. Caution may be warranted in using these medications in patients at risk for this complication.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| 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 | 0.000 |
| 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".