Hospitalization Rates in Patients with Crohnʼs Disease and Deep Remission: Data from the 56-week CHARM Trial
Bibliographic record
Abstract
Purpose: Deep remission (DR), an emerging treatment goal in Crohn's disease (CD), may be associated with improved patient outcomes. Methods: We assessed all-cause and CD-related hospitalization rates among patients (both ADA- and PBO- treated) in the 56-week CHARM trial (NCT00077779) who achieved predicted DR vs. those who did not. Predicted DR was defined as having both predicted mucosal healing (using an index comprised of non-invasive biomarkers and symptomatology1) and clinical remission (Crohn's Disease Activity Index [CDAI] total score <150) at week 12 in CHARM. Hospitalization rates were compared in predicted DR achievers vs. non-achievers from week 12 to week 56 using chi-square tests. Logistic regression was used to compare the odds of being hospitalized from week 12 to week 56, adjusting for adalimumab treatment and CD disease duration at week 12. Analyses were performed as observed and with non-responder imputation (NRI) for patients with missing predicted DR data. Results: At week 12 in CHARM, 193 of 686 patients achieved predicted DR at week 12 in CHARM. From week 12 to week 56, hospitalizations for any reason (11% vs. 18%; odds ratio [OR] 0.59; 95% confidence interval [CI] 0.36, 0.98; P=.04) as well as those specifically related to CD (6% vs. 13%; OR 0.43; 95% CI 0.23, 0.83; P=.01) were significantly less among predicted DR achievers vs. non-achievers (Table, as observed). In the NRI analysis, CD-related hospitalizations were significantly less in DR achievers vs. non-achievers (6% vs. 12%; OR 0.68; 95% CI 0.25, 0.93; P=.03).Table: Table. Hospitalization rates in predicted DR achievers vs. non-achieversConclusion: Hospitalizations for any reason or specifically related to CD were fewer in patients with CD who achieved predicted DR compared with those who did not.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".