The Predictive Impact of Frailty Index on Outcomes Following Emergency Colectomy for Obstructing and Perforated Colon Cancer
Bibliographic record
Abstract
This study aimed to analyze the predictive impact of frailty index and patterns of outcomes in patients with obstructing and perforated colon cancer who had emergency surgery. The nighty-nine patients who underwent right and left hemicolectomy were retrospectively evaluated within emergency conditions such as obstruction or perforation of tumor between February 2017 and October 2020. The 5-mFI (modified frailty index) score was measured by multiplying each number of frailty features (1 point per each existence; 0 - 5 points) and categorized into three groups (mFI=0, mFI=1, and mFI ≥ 2). The average age of the patient population was 65.21±13.84 years old. The male patients were 60 (60%). Albumin level was seen lower in patients who had higher mFI (3.86±0.63vs. 3.51±0.76 vs. 3.51±0.65, p=0.045). The predictive outcomes regarding the mFI potentially showed increased Clavien Dindo classification (CDC) [OR: 1.49, 95%CI: 0.82-2.75, p=0.2], morbidity [OR: 2.43, 95%CI: 0.50-13.98, p=0.3], and leakage [OR: 2.02, 95%CI: 0.63-6.65, p=0.2]. The morbidity (16, 24.6% vs. 16, 47.1%), p=0.041) and mortality (10, 15.4% vs. 9, 26.5%, p=0.289) were more likely seen for right sided tumors. Stoma formation was seen more likely for left sided tumors (29, 60% vs. 8, 23.5%, p=0.001). The 5-mFI score might be assumed as a preoperative prognostic tool for emergency colon surgery considering morbidity, mortality, prolonged hospitalization, and reoperation. Although morbidity and mortality in right-sided tumors and stoma formation are higher in left-sided tumors, 5-mFI score can be evaluated in patients regardless of colon cancer location.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".