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Record W4242837428 · doi:10.1093/jcag/gwz006.079

A80 ADHERENCE TO GUIDELINES AND BEST PRACTICES FOR IBD FLARE MANAGEMENT AND CORTICOSTEROID ADMINISTRATION: A RETROSPECTIVE CHART REVIEW

2019· article· en· W4242837428 on OpenAlexaffabout
Reed T. Sutton, Ellina Lytvyak, David Pincock, Daniel C. Baumgart, Daniel Sadowski, Richard N. Fedorak, Karen I. Kroeker

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsRoyal Alexandra HospitalAlberta Health ServicesUniversity of Alberta
Fundersnot available
KeywordsMedicineInflammatory bowel diseaseGuidelineRetrospective cohort studyMedical recordConfidence intervalUlcerative colitisInternal medicineCrohn's diseaseDiseasePediatrics

Abstract

fetched live from OpenAlex

Induction and maintenance of remission is a primary treatment goal for inflammatory bowel disease (IBD). Active disease is often treated with corticosteroids (CS). Although effective, CS have significant negative effects, and not recommended for long term or frequent use, especially when safer medications are now available. Nonetheless, literature suggests that cumulative exposure to CS in IBD patients has not changed. Gaps in clinician adherence to international guidelines for IBD care have also been identified. We aim to: (1) assess adherence of practitioners to guidelines for CS use and treatment of disease flares, and (2) associate guideline adherence with outcomes at 12 months. A retrospective, single-center study using data collected from outpatients of the University of Alberta IBD Clinic, receiving >1 dispensation of CS from an IBD practitioner between March 2014–2016. Data for CS dispensations including and for 18 months following the initial dispensation were extracted from provincial databases. Other data was manually extracted from the region-specific electronic medical record (EMR). Regression analyses were performed with clinical remission as the dependent variable (95% confidence). Of 345 charts identified, 244 met inclusion. The majority, 157 (64.3%), had Crohn’s disease (CD). At the initial dispensation, median age was 40 (IQR: 28–50) years. Maintenance medications: 72 (29.5%) on no IBD medication, 75 (30.7%) 5-ASA only, 34 (13.9%) immunomodulators, and 63 (25.8%) biologic therapy. CS were prescribed in clinic for 125 (51.2%), at endoscopy for 54 (22.1%), in hospital for 29 (11.9%), and by telephone for 36 (14.8%). The majority of CS prescribed were prednisone (176, 72.1%), the remainder budesonide. Figure 1 shows adherence to flare and CS guideline indicators. On analysis of outcomes, visit type and steroid type were not associated with increased steroid use within 12 months. In regression models for predicting clinical remission at 12 months following dispensation, the most significant predictor was <2 additional CS prescriptions (OR, 6.86; p=0.016). Interestingly, vitamin D supplementation showed increased likelihood of remission (OR, 2.61; p=0.064), while documentation of clinical scores showed decreased likelihood of remission (OR, 0.34; p=0.013). There are gaps between guidelines and clinical practice for some aspects of IBD patient care, particularly documentation and fecal calprotectin. Providers seem more likely to document clinical scores when patients have severe disease. Making better use of EMR functionality may be of utility to automate and improve clinical documentation and testing. Additionally, prescribing of steroids beyond an initial flare does not appear to be associated with better outcome. CCC, CIHRUniversity of Alberta

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)0.005
metaresearch head score (Gemma)0.017
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 score0.093
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.011
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.297
Teacher spread0.275 · 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
Published2019
Admission routes2
Has abstractyes

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