Bibliographic record
Abstract
BACKGROUND: The objective of our analysis was to determine the optimal timing of cholecystectomy during admission for acute cholecystitis. METHODS: All patients from the American College of Surgeons National Surgical Quality Improvement Program Participant User Files from 2005 through 2010 who underwent emergency cholecystectomy within 7 days of hospital admission for acute cholecystitis were included for analysis. The association between timing of cholecystectomy and postoperative outcomes was determined using multivariate logistic regression analyses after adjustment for patient demographics, acute and chronic comorbid medical conditions, preoperative sepsis classification, American Society of Anesthesiologists physical status classification, and preoperative liver function tests. RESULTS: A total of 5,268 patients were included for analysis. The timing of operation was day of admission for 49.7% of these patients, 1 day after admission for 33.4%, 2 days after admission for 9.5%, 3 days after admission for 3.9%, and 4 days to 7 days after admission for 3.6%. Multivariate logistic regression analyses revealed no significant association between timing of operation and 30-day postoperative mortality or overall morbidity. Patients who underwent operation later in the course of admission were more likely to require an open procedure and sustained significantly longer postoperative and overall lengths of hospitalization. Similar findings were demonstrated for a subgroup of patients who exhibited characteristics that placed them at higher risk for surgical intervention. CONCLUSION: Immediate cholecystectomy is preferred for patients who require hospitalization for acute cholecystitis. LEVEL OF EVIDENCE: Economic/decision analysis, level III.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.079 | 0.008 |
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".