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Record W2792735726 · doi:10.1093/jcag/gwy009.037

A37 ASTHMA IS NOT ASSOCIATED WITH THE NEED FOR SURGERY IN CROHN’S DISEASE WHEN CONTROLLING FOR SMOKING STATUS: A POPULATION-BASED COHORT STUDY

2018· article· en· W2792735726 on OpenAlexaffabout
M Ellen Kuenzig, Mohsen Sadatsafavi, A. Aviña-Zubieta, Rebecca Burne, Michał Abrahamowicz, Marie‐Eve Beauchamp, Gilaad G. Kaplan, Eric I. Benchimol

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicEosinophilic Esophagitis
Canadian institutionsUniversity of CalgaryMcGill University Health CentreMcGill UniversityUniversity of British ColumbiaChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsMedicineAsthmaConfoundingCohortProportional hazards modelPopulationCohort studyEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Growing evidence suggests that asthma and Crohn’s disease (CD) commonly co-occur. The impact of asthma on the prognosis of CD is not known. Studies evaluating the risk of surgery in CD patients using health administrative data are limited by their inability to adjust for confounding variables not included in these data, such as smoking. The aim of our study was to assess the impact of asthma on the need for intestinal resection in CD adjusting for smoking status, despite smoking status being unmeasured in health administrative data, using a secondary dataset and novel methodology. Using population-based health administrative data from Alberta, we conducted a cohort study to assess the impact of asthma on the need for surgery in patients with CD diagnosed between April 1, 2002 and March 31, 2008 (n=2,113). Validated algorithms were used to identify incident CD cases, patients with co-occurring asthma, and intestinal resection surgeries. The association between asthma and intestinal resection was estimated using Cox proportional hazards regression. Smoking status was imputed using a method based on martingale residuals, leveraging information from a secondary dataset in which smoking status was measured. This second dataset included patients enrolled in the Alberta IBD Consortium between 2007 and 2014 who completed environmental questionnaires (n=485). All analyses were adjusted for age, sex, rural/urban status, and mean neighbourhood income quintile. Asthma did not increase the risk of surgery in either the health administrative data unadjusted for smoking status (HR 1.03, 95% CI 0.81 to 1.29) or in the secondary data adjusted for smoking status (HR 0.74, 95% CI 0.50 to 1.37). The association remained non-significant after using the secondary data to impute smoking status in the health administrative data (HR 0.92, 95% CI 0.75 to 1.15). Although asthma is associated with an increased risk of CD, co-occurring asthma was not associated with the risk of surgery in patients with CD. This null association persisted after adjusting for smoking status. This study also demonstrates a novel method to adjust for smoking status in research using health administrative data when it is measured in a smaller secondary dataset. CAG, CCC, CIHR

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)0.002
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 score0.172
Threshold uncertainty score0.343

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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
Published2018
Admission routes2
Has abstractyes

Explore more

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