S0884 A Retrospective Review of Factors Associated With Recurrent Ileocolonic Resection in Patients With Crohn's Disease
Bibliographic record
Abstract
INTRODUCTION: Additional ileocolonic resection(s) (ICR) in Crohn’s Disease (CD) patients undergoing the first ICR represents an important source of morbidity and complications. The factors that predict time to recurrent ICR are not well defined. Here we reviewed patients with stricturing CD who have had at least two ICRs to inquire if any clinical factors are associated with a short period of time between ICRs. METHODS: A cohort was designed using surgical billing codes for patients with CD who had an ICR between 2007 and 2018 at one institution and validated by manual chart review. Independent variables included age, sex, race, smoking, family history of IBD, duration of disease, Montreal phenotype, perianal involvement, biologic medications, total number of resections, and indication for surgery. The variables were tested independently for association with time between the first and second ICR (T1-2) using a multivariate linear regression model. Rutgeerts score between first and second ICR was tested using one-way ANOVA (using i0 and >=i1, compared to T1-2) for the 29 patients with endoscopic data. RESULTS: From the initial cohort of 365 patients, 294 patients were excluded due to surgical indication other than stricture, location not ileocecum, only one ICR, extreme outlier results (n = 2) and incomplete charts. Demographic data is shown in Table 1. A total of 14 patients used biologic medications prior to index ICR, and an additional 42 patients were started on biologics between first and second ICR. Taking biologics before the first resection was associated with a shorter T1-2 (5.2 vs 10.8 years, P = 0.0009). Starting biologics after index surgery did not impact T1-2. The remainder of the variables tested did not show a significant association with T1-2. The average amount of time for T1-2 was 9.5 years. CONCLUSION: In patients who underwent recurrent ICR, being prescribed biologics before index resection is significantly associated with a shorter time from index to subsequent resection (P < 0.001). However, this variable only explains 12% of the variability, suggesting additional variables affect T1-2. This association may be explained by a confounding factor such as disease activity/more aggressive CD phenotype. It is also possible that in a substrata of CD patients, taking biologics before index ICR accelerates pro-fibrogenic mechanisms. Future studies are needed to identify more clinical and/or molecular factors that would further explain and predict need for subsequent ICRs in CD patients.Table 1.: Demographics
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".