Effect of low-level creatinine clearance on short-term postoperative complications in patients with colorectal cancer
Bibliographic record
Abstract
Background: Renal function is closely related to cancer prognosis. Since preoperative renal insufficiency has been identified as a risk factor for postoperative complications, this study aimed to investigate the effect of preoperative creatinine clearance rate (CrCl) on short-term prognosis of patients undergoing colorectal surgery. Methods: A retrospective analysis was conducted of the electronic health records of 526 adult patients who underwent elective colorectal cancer (CRC) surgery from September 2014 to February 2019 at the First Affiliated Hospital of Wenzhou Medical University. Cases were divided into two groups according to CrCl level and clinical variables were compared. Risk factors associated with postoperative complications were evaluated through univariate and multivariate logistic regression analyses. Results: A total of 526 patients met the inclusion criteria. The overall rate of postoperative complications was 28.14%. Overall, the incidence of postoperative complications was significantly higher in the low CrCl patients. A low-level CrCl, multi-organ combined resection, and Charlson comorbidity index (CCI) were independent risk factors for short-term complications in patients with CRC. However, a low CrCl was identified as an independent risk factor for short-term postoperative complications in elderly, but not young patients in a subgroup analysis. Conclusions: Preoperative low-level CrCl, multi-organ combined resection, and CCI were significant risk factors of postoperative complications in CRC patients. Preoperative low-level CrCl and multi-organ combined resection has a poor prognostic impact for elderly patients with CRC. These findings should have important implications for health care decision-making among patients with CRC who are at higher risk for post-operative complications.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".