Background: Inflammatory bowel disease (IBD) presents unique challenges in elderly patients due to comorbidities and treatment-related risks. Objectives: This study evaluates ustekinumab (UST) and vedolizumab (VDZ) efficacy and safety in elderly Crohn’s disease (CD) patients. Design: A retrospective cohort study at a tertiary medical center. Methods: CD patients aged ⩾60 years (elderly) treated with UST, compared to non-elderly (<60 years) patients treated with UST and elderly patients treated with VDZ. Clinical response was evaluated using the Harvey–Bradshaw index (HBI) and clinical biomarkers, alongside monitoring steroid use, hospitalization rates, treatment persistence, and surgical interventions. Results: The study included 166 CD patients: 32 elderly and 65 non-elderly patients treated with UST, and 69 elderly patients treated with VDZ. The mean duration of follow-up was 10.8 ± 2.8 months in the non-elderly group, 9.97 ± 3.28 months in the elderly UST group, and 10.0 ± 3.29 months in the VDZ group. Elderly UST patients were more likely to receive corticosteroids at initiation than non-elderly UST patients (44% vs 14%, p = 0.001). At 12 months, clinical response rates did not significantly differ between elderly and non-elderly UST groups, respectively (48% vs 40%, p = 0.5). However, elderly UST patients exhibited higher hospitalization rates over time compared to non-elderly UST patients (6-month: 19% vs 6.2%, p = 0.077; 12-month: 19% vs 4.6%, p = 0.055; log-rank p = 0.004). No significant differences were observed in clinical response and remission rates between elderly UST and elderly VDZ patients at 6 and 12 months. At 6 months, a higher hospitalization rate was observed in the UST group (19% vs 4.3% p = 0.027), but this difference did not persist over time. Conclusion: UST and VDZ are effective and safe treatments for elderly CD patients, despite higher hospitalization rates compared to non-elderly patients, likely due to age-related complications.

(1) Background: Predicting which patients with upper gastro-intestinal bleeding (UGIB) will receive intervention during urgent endoscopy can allow for better triaging and resource utilization but remains sub-optimal. Using machine learning modelling we aimed to devise an improved endoscopic intervention predicting tool. (2) Methods: A retrospective cohort study of adult patients diagnosed with UGIB between 2012–2018 who underwent esophagogastroduodenoscopy (EGD) during hospitalization. We assessed the correlation between various parameters with endoscopic intervention and examined the prediction performance of the Glasgow-Blatchford score (GBS) and the pre-endoscopic Rockall score for endoscopic intervention. We also trained and tested a new machine learning-based model for the prediction of endoscopic intervention. (3) Results: A total of 883 patients were included. Risk factors for endoscopic intervention included cirrhosis (9.0% vs. 3.8%, p = 0.01), syncope at presentation (19.3% vs. 5.4%, p < 0.01), early EGD (6.8 h vs. 17.0 h, p < 0.01), pre-endoscopic administration of tranexamic acid (TXA) (43.4% vs. 31.0%, p < 0.01) and erythromycin (17.2% vs. 5.6%, p < 0.01). Higher GBS (11 vs. 9, p < 0.01) and pre-endoscopy Rockall score (4.7 vs. 4.1, p < 0.01) were significantly associated with endoscopic intervention; however, the predictive performance of the scores was low (AUC of 0.54, and 0.56, respectively). A combined machine learning-developed model demonstrated improved predictive ability (AUC 0.68) using parameters not included in standard GBS. (4) Conclusions: The GBS and pre-endoscopic Rockall score performed poorly in endoscopic intervention prediction. An improved predictive tool has been proposed here. Further studies are needed to examine if predicting this important triaging decision can be further optimized.