Predictors of critical care-related complications in colectomy patients using the National Surgical Quality Improvement Program
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Colectomy patients experience a broad set of adverse outcomes. Complications requiring critical care support are common in this group. We hypothesized that as frailty increases, the risk of Clavien class IV and V complications will increase in colectomy patients. METHODS: Using the National Surgical Quality Improvement Program (NSQIP) participant use files for 2005-2009, we identified patients who underwent laparoscopic and open colectomies by Current Procedural Terminology code. Using the Clavien classification for postoperative complications, we identified NSQIP data points most consistent with Clavien class IV requiring intensive care unit (ICU) care or class V complications (death). We used a modified frailty index with 11 variables based on mapping the Canadian Study of Health and Aging Frailty Index and existing NSQIP variables. Logistic regression was performed to acuity adjust the findings. RESULTS: A total of 58,448 colectomies were identified. As frailty index increased from 0 to 0.55, the proportion of those experiencing Clavien class IV or V complications increased from 3.2% at baseline to 56.3%. Variables found to be significant by logistic regression (odds ratio) were frailty index (14.4; p = 0.001), open procedure (2.35; p < 0.001), and American Society of Anesthesiologists class 4 (3.2; p = 0.038) or 5 (7.1; p = 0.001) while emergency operation and wound classification 3 or 4 were not. CONCLUSIONS: Complications requiring ICU care represent a significant morbidity in the colectomy patient population. Frailty index seems to be an important predictor of ICU-level complications and death, and laparoscopy seems to be protective.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it