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S948 Relationship Between Hospitalization, Surgery and Achievement of Clinical Remission or Clinical Response in Moderate to Severe Crohn’s Disease Patients: Results From the UNITI/IM-UNITI Trials

2022· article· en· W4316077490 on OpenAlexaff
Zhijie Ding, Sumesh Kachroo, James Izanec, Dominik Naessens, Claire Fischer, Aline Gauthier

Bibliographic record

VenueThe American Journal of Gastroenterology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsEspace pour la vie
Fundersnot available
KeywordsMedicineCrohn's diseaseDiseaseInternal medicineClinical trialRandomized controlled trialMaintenance therapyGastroenterologySurgeryChemotherapy

Abstract

fetched live from OpenAlex

Introduction: Crohn’s disease (CD) is a chronic disease with high burden for patients and payers. Treatment aims include induction and maintenance of clinical remission (CRem). Understanding the relationship between rates of hospitalization and surgery and health states can help determine the economic burden. This analysis used results from the UNITI/IM-UNITI trials (CNTO1275CRD3001-3) of patients with moderate to severe CD, to determine the relationship between hospitalization and surgery rates and each health state over 1 year. Methods: Hospitalization and surgery data from UNITI/IM-UNITI were pooled across arms and across induction and maintenance phases. Based on CRem and response achieved at each visit (weeks 0-52), patients’ exposure time were classified into three health states (HS) using the Crohn's Disease Activity Index score: CRem, clinical response without clinical remission (CResp) and active CD. Hospitalization and surgery events were assigned based on the HS at the visit prior to the event. The base case (BC) analysis included CD-related hospitalizations and surgeries only, a first sensitivity analysis was performed including both CD- and non-CD-related hospitalizations and surgeries, and a second sensitivity analysis was performed on patients randomized to maintenance only. Annualized rates were estimated by HS adjusting for the exposure time in each health state. Results: The analysis included a total of 773 patients in CRem, 723 in CResp and 1,255 in active CD. BC results showed significantly fewer hospitalizations per 100 patient-years (PY) in CRem (6.50), and numerically fewer per 100 PY in CResp (14.37) compared to active CD (20.82). Similarly, patients in CRem had significantly fewer surgeries per 100 PY vs active CD (4.18 vs 15.57), and the difference was not statistically significant vs patients in CResp, who incurred 11.35 surgeries/100 PY. P-values are reported in Figure. CRem (9.11 days) and CResp (9.86 days) also had a numerically shorter mean duration of hospitalization compared to active CD (15.77 days). These results were consistent with those from both sensitivity analyses. Conclusion: Annualized hospitalization and surgery rates from the UNITI/IM-UNITI trials were significantly lower for patients in CRem and lower but non-significantly for patients in CResp, compared to patients in active CD. CRem and CResp had a numerically shorter mean duration of hospitalization compared to active CD.Figure 1.: Annualized CD-related hospitalization and surgery rates in UNITI/IM-UNITI in each health state

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)0.028
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.038
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.010
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.072
GPT teacher head0.358
Teacher spread0.285 · 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 designNon-randomized trial
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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