Impact of medical therapy on patients with Crohn’s disease requiring surgical resection
Bibliographic record
Abstract
AIM: To evaluate the impact of medical therapy on Crohn’s disease patients undergoing their first surgical resection.METHODS: We retrospectively evaluated all patients with Crohn’s disease undergoing their first surgical resection between years 1995 to 2000 and 2005 to 2010 at a tertiary academic hospital(St. Paul’s Hospital, Vancouver, Canada). Patients were identified from hospital administrative database using the International Classification of Diseases 9 codes. Patients’ hospital and available outpatient clinic records were independently reviewed and pertinent data were extracted. We explored relationships among time from disease diagnosis to surgery, patient phenotypes, medication usage, length of small bowel resected, surgical complications, and duration of hospital stay.RESULTS: Total of 199 patients were included; 85 from years 1995 to 2000(cohort A) and 114 from years 2005 to 2010(cohort B). Compared to cohort A, cohort B had more patients on immunomodulators(cohort A vs cohort B: 21.4% vs 56.1%, P < 0.0001) and less patients on 5-aminosalysilic acid(53.6% vs 29.8%, P = 0.001). There was a shift from inflammatory to stricturing and penetrating phenotypes(B1/B2/B3 38.8% vs 12.3%, 31.8% vs 45.6%, 29.4% vs 42.1%, P < 0.0001). Both groups had similar median time to surgery. Within cohort B, 38 patients(33.3%) received anti-tumor necrosis factor(TNF) agent. No patient in cohort A was exposed to anti-TNF agent. Compared to patients not on anti-TNF agent, ones exposed were younger at diagnosis(anti-TNF vs without anti-TNF: A1/A2/A3 39.5% vs 11.8%, 50% vs 73.7%, 10.5% vs 14.5%, P = 0.003) and had longer median time to surgery(90 mo vs 48 mo, P = 0.02). Combination therapy further extended median time to surgery. Using timedependent multivariate Cox proportional hazard model, patients who were treated with anti-TNF agents had a significantly higher risk to surgery(adjusted hazard ratio 3.57, 95%CI: 1.98-6.44, P < 0.0001) compared to those without while controlling for gender, disease phenotype,
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".