Surgical Management of Lower Gastrointestinal Hemorrhage: An Analysis of the ACS NSQIP Database
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Despite advances in diagnostics for lower gastrointestinal bleeding, colorectal resection remains the only option when non-surgical management fails. This study examines a cohort of patients who underwent surgery for this indication to determine the effect of procedure type on postoperative outcomes. Methods: We identified all patients who underwent colorectal resection for bleeding in the ACS NSQIP Participant Use Data File and the Procedure Targeted PUF for colectomy from 2012 to 2013. We compared patients who underwent partial versus total colectomy using univariate analyses and multivariable logistic regression. Results: Of 38,486 colorectal resections performed for bleeding, 85.3% underwent a partial colectomy and 14.7% underwent total colectomy. Patients who had total colectomy were more likely to receive more than four units of blood prior to surgery and have operative times longer than 180 min. Patients who had partial colectomy were more likely to have laparoscopic procedures and to have a stoma created during surgery. On univariate analysis, total colectomy was associated with increased risk of postoperative ileus, cardiac and renal complications, and mortality. On multivariate analysis, total colectomy was associated with increased risk of cardiac and renal complications. Conclusion: The most common procedure performed for lower gastrointestinal hemorrhage was partial colectomy. J Curr Surg. 2017;7(1-2):4-6 doi: https://doi.org/10.14740/jcs307w
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 it