Should Delayed Cholecystectomy Following Acute Calculous Cholecystitis be Discouraged in a Resource-restricted Setting?
Bibliographic record
Abstract
BACKGROUND: Early cholecystectomy for acute calculous cholecystitis (ACC) reduces hospital stay and complications during the waiting period. The purpose of this study is to establish the patterns of management of ACC at the University Hospital of the West Indies (UHWI) and to evaluate the advantages of early versus delayed cholecystectomy. METHODS: This was a retrospective chart review of patients admitted with a diagnosis of ACC. Data collection included demographics, management strategy, timing to cholecystectomy, significant events while awaiting cholecystectomy and duration of hospital stay. Mann-Whitney U and Chi-squared tests were used for analysis. P-value of < 0.05 was considered significant. RESULTS: A total of 102 patient charts were extracted, 59 of which were managed conservatively and 43 managed with early cholecystectomy. The mean time to surgery after conservative management was 173 days. About 30% of persons managed conservatively had significant attacks while awaiting surgery, which included need for re-admission and earlier intervention. There was a trend toward longer mean total hospital stay in the conservative group (xsx = 5.03, xCons = 6.12; p = 0.054). CONCLUSION: Conservative management of ACC results in significant delays in definitive management and risks of complications during the waiting period. Early cholecystectomy should be encouraged even in a resource-restricted setting.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".