The safety and efficacy of antitumour necrosis factor‐alpha therapy for inflammatory bowel disease in patients post liver transplantation: a case series
Bibliographic record
Abstract
BACKGROUND: The role of antitumour necrosis factor-alpha (anti-TNF) therapy for inflammatory bowel disease (IBD) among liver transplant recipients is largely unknown given the rarity of this population and the paucity of literature on the subject. AIM: To investigate the safety and efficacy of anti-TNF therapy for refractory IBD in the post liver transplant population. METHODS: The liver transplant database at London Health Sciences Centre was searched to identify adult patients with IBD treated with anti-TNF therapy post transplantation. RESULTS: Six patients (five men, one woman) were identified, aged 28-65. All patients had cadaveric orthotopic liver transplants. Four patients required transplantation due to primary sclerosing cholangitis, one due to autoimmune hepatitis, and one due to biliary atresia. Five patients suffered from Crohn's disease and the remaining patient from indeterminate colitis. All patients were treated with infliximab 5 mg/kg every 8 weeks after undergoing induction at weeks 0, 2 and 6, with the exception of one patient. The duration of infliximab therapy ranged from 8 weeks to 4 years. Four patients treated with infliximab experienced sustained improvement of their IBD symptoms post transplantation, as documented by Harvey-Bradshaw Index scores demonstrating clinical remission. Of the remaining two patients, neither had sustained improvement of their IBD with infliximab or subsequent adalimumab. One patient was diagnosed with systemic lupus erythematosus and another with colorectal adenocarcinoma following anti-TNF therapy. Otherwise, no side effects were attributed to anti-TNF therapy. CONCLUSIONS: Based on this case series, anti-TNF therapy appears to be safe and effective for treating refractory IBD in patients post liver transplantation. These patients respond to anti-TNF therapy similar to those who have not been previously transplanted.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".