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Record W4407285594 · doi:10.1093/jcag/gwae059.205

A205 IMPACT OF THE PANDEMIC ON BUDESONIDE MMX DISPENSING AND TREATMENT FAILURE IN ULCERATIVE COLITIS

2025· article· en· W4407285594 on OpenAlexaffabout
Stephanie Coward, Karen J. B. Martins, Scott Klarenbach, Karen I. Kroeker, Chaoran Ma, Remo Panaccione, Lawrence Richer, Cynthia Seow, Laura E. Targownik, Gilaad G. Kaplan

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of TorontoUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsMMXBudesonideUlcerative colitisMedicinePandemicInternal medicineGastroenterologyCoronavirus disease 2019 (COVID-19)DiseaseCorticosteroidComputer science

Abstract

fetched live from OpenAlex

Abstract Background Budesonide MMX is a locally acting corticosteroid with reduced side effects compared to prednisone. During the pandemic, budesonide MMX may have been preferred due to its favourable side effect profile. Aims To analyze rates of budesonide MMX dispensing and treatment failure before / during the pandemic. Methods We analyzed population-based administrative healthcare data from Alberta to identify people dispensed budesonide MMX who met three criteria: 1. incident cases of ulcerative colitis (UC) after January 1, 2018; 2. ≥18 years old; 3. not concurrently on prednisone. We defined failure of budesonide MMX as subsequent prednisone dispensing within 30 days. We calculated rates of budesonide MMX dispensing per 1000 incident UC cases. We calculated average monthly percentage change (AMPC) in dispensing and failure rates with 95% confidence intervals (CI) by Poisson or negative binomial models. An interaction term tested differences between pre-pandemic rates (prior to April 2020) and pandemic rates (April 2020 to March 2023). We used Cox proportional hazard models to compare budesonide MMX failure before vs during the pandemic, with hazard ratios (HR) and 95%CIs—a sensitivity analysis was done to extend the follow-up time to 90 days. Results Overall, 320 incident UC cases were dispensed budesonide MMX with 30-days follow-up. Of those, 14.06% (95%CI: 10.25, 17.87) received prednisone within 30 days. Mean time to failure was 17 days. There was a significant difference in the AMPC in dispensing rates was observed pre-pandemic vs during the pandemic (p=0.037) (Table 1). After the pandemic onset, budesonide MMX dispensing significantly decreased (AAPC: −2.43%; 95%CI: −3.77, −1.08). For the 30 days, the HR for budesonide MMX failure was 1.92 (95%CI: 0.95, 3.88). When the follow-up was extended to 90 days the HR was significant at 1.68 (95%CI: 1.05, 2.71), suggesting a significantly increased hazard of budesonide MMX failure during the pandemic compared to pre-pandemic. Conclusions Budesonide MMX dispensing was stable pre-pandemic but significantly decreased during. The pandemic may have been associated with an increased failure rate of budesonide MMX—particularly within 90 days—as more patients required prednisone to manage their UC. Analysis of Rates per 1000 Individuals with Incident UC Funding Agencies Ferring Pharmaceuticals

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: yes
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.006
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 score0.123
Threshold uncertainty score0.246

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.236
Teacher spread0.231 · 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

Labeled directly by 2 models reading the full record.

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
Published2025
Admission routes2
Has abstractyes

Explore more

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