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

移动监测系统可检测疾病活动模式,并显示其与新诊断克罗恩病患者的临床结局之间的关联。

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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.

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