Using preoperative C‐reactive protein levels to predict anastomotic leaks and other complications after elective colorectal surgery: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Aim While postoperative C‐reactive protein (CRP) is used routinely as an early indicator of anastomotic leak (AL), preoperative CRP remains to be established as a potential predictor of AL for elective colorectal surgery. The aim of this systematic review and meta‐analysis is to examine the association between preoperative CRP and postoperative complications including AL. Method MEDLINE, EMBASE, Web of Science, PubMed, Cochrane Library and CINAHL databases were searched. Studies with reported preoperative CRP values and short‐term surgical outcomes after elective colorectal surgery were included. An inverse variance random effects meta‐analysis was performed for all meta‐analysed outcomes to determine if patients with or without complications and AL differed in their preoperative CRP levels. Risk of bias was assessed with MINORS and certainty of evidence with GRADE. Results From 1945 citations, 23 studies evaluating 7147 patients were included. Patients experiencing postoperative infective complications had significantly greater preoperative CRP values [eight studies, n = 2421 patients, mean difference (MD) 8.0, 95% CI 3.77–12.23, p < 0.01]. A significant interaction was observed with subgroup analysis based on whether patients were undergoing surgery for inflammatory bowel disease (X2 = 8.99, p < 0.01). Preoperative CRP values were not significantly different between patients experiencing and not experiencing AL (seven studies, n = 3317, MD 2.15, 95% CI −2.35 to 6.66, p = 0.35), nor were they different between patients experiencing and not experiencing overall postoperative morbidity (nine studies, n = 2958, MD 4.54, 95% CI −2.55 to 11.62, p = 0.31) after elective colorectal surgery. Conclusion Higher preoperative CRP levels are associated with increased rates of overall infective complications, but not with AL alone or with overall morbidity in patients undergoing elective colorectal surgery.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.038 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".