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Record W4213241612 · doi:10.1093/jcag/gwab049.151

A152 NATURAL HISTORY OF SMALL BOWEL STRICTURES IN CROHN’S DISEASE

2022· article· en· W4213241612 on OpenAlexaff
Dũng Chí Vũ, Gurmun Singh Brar, Kayla Dadgar, Jeffrey D. McCurdy

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsOttawa HospitalUniversity of TorontoUniversity of Ottawa
Fundersnot available
KeywordsMedicineNatural historyCrohn's diseaseHazard ratioRetrospective cohort studyProportional hazards modelInflammatory bowel diseaseMedical recordObservational studyDiseaseStenosisSurgeryRadiologyInternal medicineConfidence interval

Abstract

fetched live from OpenAlex

Abstract Background Crohn’s disease (CD) is a progressive inflammatory disease that often results in intestinal complications such as small bowel (SB) strictures. SB strictures are frequently associated with substantial morbidity and may require surgery. The natural history of SB strictures in the era of biologic treatments has not been well characterized. Aims To determine the proportion of patients with SB strictures who develop complicated stricturing disease and to identify clinical factors associated with this outcome. Methods We performed a retrospective observational study between January 1, 2009, and May 31, 2019. Adults (>17 years) with CD who underwent an abdominal CT scan or MRI were identified from our institutional data warehouse using the ICD-10 code K50* and local imaging codes. Reports were reviewed to determine the imaging protocol and the presence of SB strictures. We included CT or MR enterography studies that reported SB strictures and excluded encounters with incomplete records, diverting ostomies, ileal J-pouches, and patients evaluated for pre-surgical planning. Each imaging study was included as a separate encounter in our analysis. Our primary endpoint was the development of complicated stricturing disease defined as stricture-related hospitalization or surgery. Time to event was estimated using Kaplan–Meier analysis and associated factors were assessed by multivariable Cox proportional hazard models adjusted for age, sex, exposure to biologics and corticosteroids. Results A total of 6583 unique imaging studies were identified: 926 (14%) studies reported SB strictures without penetrating complications, and 568 (9%) studies reported penetrating complications. A total of 503 (8%) studies, performed on 330 patients, met our inclusion criteria: mean age 42 (SD, 15.1) years and 166 (50%) males. Overall, 144 (44%) patients developed complicated stricturing disease: 106 (32%) patients required surgery and 132 (40%) patients were hospitalized for stricture related complications. Of the patients who underwent surgery, the mean time to surgery was 13 months (SD, 18.3) and among patients who required hospitalization, mean time to hospitalization was 15 months (SD, 17.8) (Figure 1). On multivariable analysis, exposure to corticosteroids (aHR 2.11; 95% CI, 1.54–2.90; p<0.001) but not biologics (aHR 1.1; 95% CI, 0.84–1.43; p<0.48) at the time of the imaging study was independently associated with the development of complicated stricturing disease. Conclusions In our single center study, complicated stricturing disease occurred in 44% of patients with CD who had a SB stricture and was associated with corticosteroids but not biologics.These findings, along with additional clinical and radiologic factors may help in the development of clinical support tools to identify patients at highest risk of developing complicated stricturing disease. Figure 1. Kaplan-Meier estimates of the time to complicated stricturing disease (surgery or hospitalization) after an imaging encounter documenting SB stricture(s). 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)0.005
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.187
Teacher spread0.182 · 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
Published2022
Admission routes1
Has abstractyes

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