Timing of readmissions for complications following emergency colectomy: follow-up beyond post-operative day 30 matters
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Emergency colectomies are associated with a higher risk of complications compared to elective ones. A critical assessment of complications occurring beyond post-operative day 30 (POD30) is lacking. This study aimed to assess the readmission rate and factors associated with readmission 6-months following emergency colectomy. METHODS: A retrospective cohort study of adult patients who underwent emergency colectomy (2010-2018) was performed using the Nationwide Readmissions Database. The cohort was divided into two groups: (i) no readmission and (ii) emergency readmission(s) for complications related to colectomy (defined using ICD-9/10 codes). Readmissions were categorized as either "early" (POD0-30) or "late" (> POD30). Differences between groups were described and multivariable regression controlling for relevant covariates defined a priori were used to identify factors associated with timing of readmission and cost. RESULTS: Of 141,481 eligible cases, 13.22% (n = 18,699) were readmitted within 6-months of emergency colectomy for colectomy-related complications, 61.63% of which were "late" readmissions (> POD30). The most common reasons for "late" readmission were for bleeding, gastrointestinal, and infectious complications (20.80%, 25.30%, and 32.75%, respectively). On multiple logistic regression, female gender (OR 1.12; 95%CI 1.04-1.21), open procedures (OR 1.12, 95%CI 1.011-1.24), and sigmoidectomies (OR 1.51, 95%CI 1.39-1.65, relative to right hemicolectomies) were the strongest predictors of "late" readmission. On multiple linear regression, "late" readmissions were associated with a $1717.09 USD (95%CI $1717.05-$1717.12) increased cost compared to "early" readmissions. DISCUSSION: The majority of colectomy-related readmissions following emergency colectomy occur beyond POD30 and are associated with cases that are of overall higher morbidity, as well as open sigmoidectomies. Given the associated increased cost of care, mitigation of such readmissions by close follow-up prior to and beyond POD30 is advisable.
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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 | 0.001 |
| 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".