Neoadjuvant Chemoradiation Increases the Risk of Pelvic Sepsis After Radical Excision of Rectal Cancer
Bibliographic record
Abstract
PURPOSE: This study was designed to examine the effect of neoadjuvant chemoradiation on pelvic sepsis after mesorectal excision for rectal cancer. METHODS: A retrospective chart review was conducted for all patients who underwent curative mesorectal excision for rectal cancer during an eight-year period. Demographic, preoperative, perioperative data were collected. Pelvic sepsis was defined as clinical or radiographically demonstrable leak or a pelvic abscess. Neoadjuvant chemoradiation included 5,040 Gy in conjunction with three cycles of 5-fluorouracil-based chemotherapy, followed by a one-month waiting period. RESULTS: From January 1994 to December 2002, 246 patients (151 males; mean age 68 (range, 36-97) years) underwent curative resection for rectal cancer. Procedures included 186 anterior resections, 52 abdominoperineal resections, and 8 Hartmann's. Of 60 patients (24.4 percent) who had neoadjuvant chemoradiation, 9 (15 percent) developed pelvic sepsis (3 leaks, 6 abscesses) compared with 9 of 186 (4.8 percent) after primary surgery (6 leaks, 3 abscesses; P < 0.01). Ninety-three patients had an anastomosis or=7 cm developed pelvic sepsis (5 leaks and 1 abscess), of whom 1 had preoperative radiation. Pelvic abscess developed in 3 of 24 patients after neoadjuvant chemotherapy and abdominoperineal resection. After primary abdominoperineal resection, none of the remaining 28 patients developed pelvic sepsis. A multivariable logistic regression model was constructed to determine predictors of sepsis. Neoadjuvant chemotherapy was the only variable that was predictive (odds ratio, 3.4; 95 percent confidence interval, 1.3-9). CONCLUSIONS: The addition of neoadjuvant chemoradiation to mesorectal excision significantly increased the rate of pelvic sepsis. This was particularly true for anastomoses in the lower third of the rectum. Fecal diversion should be considered in these patients.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".