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Abstract：
Diabetes mellitus (DM) is a prevalent disorder that affects the endocrine and metabolic systems. Among the various complications associated with DM, diabetic bladder dysfunction (DBD) is the most frequently occurring genitourinary complication. The presence of DBD can lead to complications that affect the upper urinary tract, significantly impacting the quality of life for individuals with DM. Therefore, it is crucial to identify early risk factors for DBD and predict its onset. Given the absence of studies involving bladder dysfunction in patients with type 2 diabetes mellitus (T2DM) in Syria, this study aims to examine the risk factors associated with bladder dysfunction in T2DM patients and develop a predictive model to identify DBD early. Patients diagnosed with T2DM were enrolled in six endocrinology centers spread across four Syrian provinces between January 2018 and December 2023. Factors that showed an association with DBD in the bivariate analysis, with a significance level of p < 0.05, were included in a multiple logistic regression analysis. The logistic regression analysis was used to identify independent risk factors and develop a prediction model. The receiver operating characteristic (ROC) curve was used to assess the predictive performance of the identified risk factors and the prediction model for DBD. One hundred and eighty-four patients were included in this study, and they were divided into the DBD group (n = 88) and the non-DBD group (n = 96). Seven variables showed significance in the bivariate analysis. Furthermore, the multiple logistic regression analysis revealed that age (OR [95% CI]: 0.981 [0.614 - 1.337]), p < 0.007; diabetic peripheral neuropathy (DPN) (OR [95% CI]: 1.421 [1.027 - 3.308]), p = 0.03; glycated hemoglobin (HbA1c) (OR [95% CI]: 0.942 [0.821 - 1.141]), p = 0.042; and percentage of monocyte (Mono%) (OR [95% CI]: 1.109 [0.812 - 1.258]), p = 0.031 were independent risk factors for DBD. Analysis of the ROC curve revealed that the area under the curve (AUC) for age, DPN, HbA1c, and Mono were 0.703, 0.541, 0.613, and 0.836, respectively. Age, DPN, HbA1c, and Mono% were risk factors for DBD. The prediction model constructed based on the four risk factors had a good predictive value for predicting the occurrence of DBD.
摘要：
糖尿病（DM）是一种影响内分泌和代谢系统的常见疾病。在与DM相关的各种并发症中，糖尿病性膀胱功能障碍（DBD）是最常见的泌尿生殖系统并发症。DBD的存在会导致影响上尿路的并发症，显着影响DM患者的生活质量。因此,识别DBD的早期危险因素并预测其发病至关重要。鉴于叙利亚缺乏涉及2型糖尿病（T2DM）患者膀胱功能障碍的研究，本研究旨在探讨T2DM患者膀胱功能障碍的相关危险因素,并建立早期识别DBD的预测模型.2018年1月至2023年12月，被诊断为T2DM的患者在分布在四个叙利亚省份的六个内分泌中心招募。在双变量分析中显示与DBD相关的因素，P<0.05的显著性水平纳入多元logistic回归分析.Logistic回归分析用于识别独立危险因素并建立预测模型。使用受试者工作特征（ROC）曲线评估已识别的风险因素的预测性能和DBD的预测模型。本研究纳入了一百八十四名患者，分为DBD组(n=88)和非DBD组(n=96)。七个变量在双变量分析中显示出显著性。此外，多元逻辑回归分析显示，年龄(OR[95%CI]：0.981[0.614-1.337])，p<0.007；糖尿病周围神经病变（DPN）（OR[95%CI]：1.421[1.027–3.308]），p=0.03；糖化血红蛋白（HbA1c）（OR[95%CI]：0.942[0.821–1.141]），p=0.042；单核细胞百分比（Mono%）（OR[95%CI]：1.109[0.812-1.258]），p=0.031是DBD的独立危险因素。ROC曲线分析显示曲线下面积(AUC)随年龄变化,DPN,HbA1c,和单声道分别为0.703、0.541、0.613和0.836。年龄,DPN,HbA1c,和Mono%是DBD的危险因素。基于4个危险因素构建的预测模型对DBD的发生具有较好的预测价值。
