ABSTRACT
INTRODUCTION: Patients with ulcerative colitis (UC) receiving immunosuppressive drugs are at substantial risk of colectomy. We aimed to assess the risk of postoperative complications of tofacitinib exposure before colectomy in comparison with biologics. METHODS: A multicenter, retrospective, observational study was conducted in patients with UC who underwent total colectomy for medically refractory disease, exposed to tofacitinib or a biologic before surgery. Primary outcome was the occurrence of any complication within 30 (early) and 90 (late) days after surgery. Secondary outcomes were the occurrence of infections, sepsis, surgical site complications, venous thromboembolic events (VTE), hospital readmissions, and redo surgery within the same timepoints. RESULTS: Three hundred one patients (64 tofacitinib, 162 anti-tumor necrosis factor-α agents, 54 vedolizumab, and 21 ustekinumab) were included. No significant differences were reported in any outcome, except for a higher rate of early VTE with anti-tumor necrosis factor-α agents ( P = 0.047) and of late VTE with vedolizumab ( P = 0.03). In the multivariate analysis, drug class was not associated with a higher risk of any early and late complications. Urgent colectomy increased the risk of any early (odds ratio [OR] 1.92, 95% confidence interval [CI] 1.06-3.48) complications, early hospital readmission (OR 4.79, 95% CI 1.12-20.58), and early redo surgery (OR 7.49, 95% CI 1.17-47.85). A high steroid dose increased the risk of any early complications (OR 1.96, 95% CI 1.08-3.57), early surgical site complications (OR 2.03, 95% CI 1.01-4.09), and early redo surgery (OR 7.52, 95% CI 1.42-39.82). Laparoscopic surgery decreased the risk of any early complications (OR 0.54, 95% CI 0.29-1.00), early infections (OR 0.39, 95% CI 0.18-0.85), and late hospital readmissions (OR 0.34, 95% CI 0.12-1.00). DISCUSSION: Preoperative tofacitinib treatment demonstrated a postoperative safety profile comparable with biologics in patients with UC undergoing colectomy.
ABSTRACT
BACKGROUND AND AIMS: No consensus exists on optimal strategy to prevent postoperative recurrence (POR) after ileocecal resection (ICR) for Crohn's disease (CD).We compared early medical prophylaxis versus expectant management with treatment driven by findings at elective endoscopy 6-12 months after ICR. METHODS: A retrospective, multicentric, observational study was performed. CD-patients undergoing first ICR were assigned to cohort1 if a biologic or immunomodulator was (re)started prophylactically after ICR, or to cohort2 if no postoperative prophylaxis was given and treatment was started as reaction to elective endoscopic findings. Primary endpoint was rate of endoscopic POR (Rutgeerts>i1). Secondary endpoints were severe endoscopic POR (Rutgeerts i3/i4), clinical POR, surgical POR and treatment burden during follow-up. RESULTS: Of 346 included patients, 47.4% received prophylactic postoperative treatment (proactive/cohort1) and 52.6% did not (reactive/cohort2).Endoscopic POR (Rutgeerts>i1) rate was significantly higher in cohort2 (41.5% vs 53.8%, OR1.81, P=0.039) at endoscopy 6-12 months after surgery. No significant difference in severe endoscopic POR was found (OR1.29, P=0.517). Cohort2 had significantly higher clinical POR rates (17.7% vs 35.7%, OR3.05, P=0.002) and numerically higher surgical recurrence rates (6.7% vs 13.2%, OR2.59, P=0.051). Cox proportional hazards regression analysis showed no significant difference in time to surgical POR of proactive versus expectant/reactive approach (HR2.50, P=0.057). Quasi-Poisson regression revealed a significantly lower treatment burden for immunomodulator use in cohort2 (mean ratio 0.53, P=0.002), but no difference in burden of biologics or combination treatment. CONCLUSIONS: The PORCSE study showed lower rates of endoscopic POR with early postoperative medical treatment compared to expectant management after first ileocecal resection for Crohn's disease.
ABSTRACT
Assess the predictive accuracy of the WHO COVID-19 severity classification on COVID-19 hospitalized patients. The secondary aim was to compare its predictive power with a new prediction model, named COVID-19 EPI-SCORE, based on a Bayesian network analysis. Methods: We retrospectively analyzed a population of 295 COVID-19 RT-PCR positive patients hospitalized at Epicura Hospital Center, Belgium, admitted between March 1st and April 30th, 2020. Results: Our cohort's median age was 73 (62-83) years, and the female proportion was 43%. All patients were classified following WHO severity classification at admission. In total, 125 (42.4%) were classified as Moderate, 69 (23.4%) as Severe, and 101 (34.2%) as Critical. Death proportions through these three classes were 11.2%, 33.3%, and 67.3%, respectively, and the proportions of critically ill patients (dead or needed Invasive Mechanical Ventilation) were 11.2%, 34.8%, and 83.2%, respectively. A Bayesian network analysis was used to create a model to analyze predictive accuracy of the WHO severity classification and to create the EPI-SCORE. The six variables that have been automatically selected by our machine learning algorithm were the WHO severity classification, acute kidney injury, age, Lactate Dehydrogenase Levels (LDH), lymphocytes and activated prothrombin time (aPTT). Receiver Operation Characteristic (ROC) curve indexes hereby obtained were 83.8% and 91% for the models based on WHO classification only and our EPI-SCORE, respectively. Conclusions: Our study shows that the WHO severity classification is reliable in predicting a severe outcome among COVID-19 patients. The addition to this classification of a few clinical and laboratory variables as per our COVID-19 EPI-SCORE has demonstrated to significantly increase its accuracy.
