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Record W4391886341 · doi:10.1093/jcag/gwad061.220

A220 MORTALITY IN PATIENTS WITH ULCERATIVE COLITIS UNDERGOING COLECTOMY (2016-2020)

2024· article· en· W4391886341 on OpenAlexaff
Najwa Sh. Ahmed, S Krawchuk, Katherine A Buhler, Igor Stukalin, J Besney, Abdel Aziz Shaheen, Cynthia H. Seow, Kerri L. Novak, R Ingram, Cathy Lu, Gilaad G. Kaplan, Remo Panaccione, Christopher Ma

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of TorontoUniversity of Calgary
Fundersnot available
KeywordsUlcerative colitisColectomyMedicineInternal medicineGastroenterologyColitisGeneral surgeryDisease

Abstract

fetched live from OpenAlex

Abstract Background Despite an expanding armamentarium of medical treatment options, the 10-year cumulative risk of colectomy for patients with ulcerative colitis (UC) remains 5-10%. Surgery for UC is associated with a substantial burden of mortality. A previous meta-analysis of population-based studies found that postoperative mortality was 0.7% of patients undergoing elective surgery and 5.3% of patients undergoing emergent colectomy. Aims Given improvements in managing acutely ill patients with UC, we aimed to evaluate contemporary rates of postoperative mortality following colectomy. Methods We analyzed data in the National Inpatient Sample (NIS) for 2016-2020. The NIS is an all-payer administrative health database, capturing information from ampersand:003E7 million inpatient admissions at ampersand:003E1000 hospitals across the United States annually. All analyses were weighted to account for the complex stratified survey design. Adult patients (≥18 yrs) with a primary diagnosis of UC undergoing colectomy were identified with ICD-10 coding. Rates of in-hospital postoperative mortality were calculated, and predictors of mortality were evaluated in survey-adjusted logistic regression. Results A total of 8570 hospitalizations for patients with UC undergoing colectomy were included. Mean age at colectomy was 44.5 years and 47% of patients were female. Emergency colectomy was performed in 38.2% [95% CI: 35.9%, 40.7%] of patients, and was attempted laparoscopically in 55.9% [53.1%, 58.7%]. Overall mortality from 2016-2020 was 1.2% [0.8%, 1.9%], but was 0.2% [0.1%, 0.8%] for elective surgery and 2.9% [1.9%, 4.5%] for emergent surgery. Stratified rates of mortality are summarized in Table 1. In multivariable analysis, age was not an independent predictor of mortality but laparoscopic surgery (adjusted odds ratio 0.24 [0.06-0.98], p=0.047) and elective resection (aOR 0.16 [0.04-0.68], p=0.01) were associated with a lower risk of postoperative death. Conclusions Approximately 1 in 100 patients undergoing colectomy for UC will die postoperatively. This risk is highest in comorbid patients undergoing open laparotomy or emergency colectomy. The risk of mortality in both emergent and elective settings is lower than previously reported. Table 1. Stratified risks of mortality after colectomy for ulcerative colitis Funding Agencies None

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.003
GPT teacher head0.204
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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