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Purpose: To develop an algorithm for the diagnosis of Behçet's disease (BD) uveitis based on ocular findings. Methods: Following an initial survey among uveitis experts, we collected multi-center retrospective data on 211 patients with BD uveitis and 207 patients with other uveitides, and identified ocular findings with a high diagnostic odds ratio (DOR). Subsequently, we collected multi-center prospective data on 127 patients with BD uveitis and 322 controls and developed a diagnostic algorithm using Classification and Regression Tree (CART) analysis and expert opinion. Results: We identified 10 items with DOR >5. The items that provided the highest accuracy in CART analysis included superficial retinal infiltrate, signs of occlusive retinal vasculitis, and diffuse retinal capillary leakage as well as the absence of granulomatous anterior uveitis or choroiditis in patients with vitritis. Conclusion: This study provides a diagnostic tree for BD uveitis that needs to be validated in future studies. [ABSTRACT FROM AUTHOR]

Background: Dehydration due to insufficient fluid intake (IFI) is detrimental to health. This cross-sectional study aimed to assess the fluid intake of urban adults in Wuxi, China, and to identify potential risk factors contributing to IFI.Methods: Adults were selected from the urban area of Wuxi, China, using a multiple-stage random sampling method. The fluid intake information was obtained with a 24-h self-reported diary over seven consecutive days in both summer and winter of 2015. A classification and regression tree (CART) analysis was conducted to detect the potential risk factors associated with IFI. CART is a machine-learning algorithm that portions the data into subsets by threshold.Results: A total of 584 adults aged 18-87 years were included. The results showed that the median (P25-P75) values of daily fluid intake of the participants were 1100 (800-1550) mL in summer and 1000 (750-1300) mL in winter. Women had a higher prevalence of IFI than men in both summer (odds ratio (OR) = 2.683, 95% confidence interval (CI): 1.830-3.934) and winter (OR = 2.636, 95% CI: 1.677-4.142). The results of CART analysis showed that, in summer, BMI < 25 kg/m2 (probability: 64.2%) and age < 64 years (probability: 67.4%) were main risk factors of IFI for men, and BMI < 29 kg/m2 (probability: 81.6%) and living in C Community (probability: 86.7%) were main risk factors for women. In winter, age < 40 years (probability: 81.8%) and BMI < 20 kg/m2 (probability: 94.5%) were identified as main risk factors of IFI for men and women, respectively.Conclusions: Most of the participants living in the study site had IFI. The fluid consumption varied by gender, age, location, and BMI. The findings could be useful for the implementation and optimization of intervention programs by identifying the individuals who may at greater risk of dehydration. [ABSTRACT FROM AUTHOR]