Mobile monitoring system detects the disease activity pattern and shows the association with clinical outcomes in patients with newly diagnosed Crohn’s disease

Abstract

Abstract We aimed to determine whether Crohn’s disease (CD) activity patterns assessed via a web-based symptom diary can help predict clinical outcomes in patients with newly diagnosed CD. Patients diagnosed with CD within the preceding 3 months were prospectively enrolled at four tertiary centers. All patients recorded their symptoms on a website using a smartphone at least once a week. The index outcomes were disease-related admission and surgery during follow-up. The disease activity from enrollment to outcome or last follow-up was reviewed for pattern analysis. Cox regression analysis was used to identify the predictors of disease outcomes. A total of 102 patients were enrolled. During a median follow-up period of 42 months, 25 (24.5%) and 6 (5.9%) patients required admission and surgery, respectively. Poor activity pattern was an independent predictor of disease-related hospitalization (adjusted hazard ratio [aHR], 3.96; 95% confidence interval [CI] 1.5–10.45; p = 0.005). A poor activity pattern (aHR, 19.48; 95% CI 1.86–203.95; p = 0.013) and female sex (aHR, 11.28; 95% CI 1.49–85.01; p = 0.018) were found to be independent predictors of bowel resection. CD disease activity patterns monitored through the mobile monitoring system may help predict clinical outcomes, such as disease-related hospitalization and surgery, in patients with newly diagnosed CD.