系统性红斑狼疮患者类固醇糖尿病发生风险预警模型构建
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2019年度河北省医学科学研究课题计划(20190362)


Establishment of risk warning models for steroid diabetes mellitus in patients with systemic lupus erythematosus
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    摘要:

    目的 探讨系统性红斑狼疮(SLE)患者类固醇糖尿病(SDM)发生危险因素,并构建风险预警模型。方法 回顾性选取2021年2月—2023年10月河北省人民医院风湿免疫科住院SLE患者168例为研究对象,根据SDM发生与否分为SDM组(n=16)与非SDM组(n=152)。对比两组患者基本情况、SLE相关等资料,将上述资料对比中有统计学意义的指标纳入二元Logistic回归分析,筛选出SLE合并SDM的危险因素,依据Logistic回归结果构建SDM发生风险预警模型,并经由受试者工作特征(ROC)曲线分析该模型预测价值。结果 SLE患者中SDM发生率为9.52%。SDM组年龄、BMI、有高血压病史、合并高甘油三酯血症、合并高胆固醇血症、有糖尿病(DM)家族史比例、SLE病程、补体C3及C4水平均明显高于非SDM组(P<0.05),累及血液系统比例、抗dsDNA阳性比例均明显低于非SDM组(P<0.05)。Logistic多因素回归分析显示,年龄45~60岁、有DM家族史是SLE患者SDM发生的独立危险因素(P<0.05)。基于年龄、DM家族史构建SDM风险预防模型预测SDM发生的曲线下面积为0.815,敏感度为87.50%,特异度为67.11%。结论 年龄45~60岁,有DM家族史是SLE患者SDM发生的独立危险因素,据此构建的预测模型区分能力及校准能力均较好,敏感度及准确度较高

    Abstract:

    Objective To explore the risk factors of steroid diabetes mellitus (SDM) in patients with systemic lupus erythematosus (SLE) and establish risk warning models. Methods A total of 168 inpatients with SLE in the rheumatology and immunology department of Hebei People's Hospital from February 2021 to October 2023 were retrospectively collected and separated into SDM group and non-SDM group according to the occurrence of SDM. The basic information and SLE related data of the two groups were compared, and the statistically significant indicators in the above data comparison were incorporated into binary Logistic regression analysis to screen out the risk factors of SLE combined with SDM. The predictive value of SDM risk early warning model was analyzed by receiver operating characteristic (ROC) curve. Results The incidence of SDM in SLE was 9.52%. Age, BMI, proportion of family history of hypertension, hypertriglyceridemia, hypercholesterolemia, proportion of family history of DM, duration of SLE, and complement C3/C4 level in SDM group were significantly higher than those in non-SDM group (P<0.05), while the proportion of blood system involvement and the proportion of anti-dsDNA were significantly lower (P<0.05). Multivariate Logistic regression analysis showed that older age and family history of DM were independent risk factors for SDM in SLE patients (P<0.05). A risk warning model for SDM was established based on age and family history of DM: Logit (P)=-4.026+0.062×age +1.573×family history of DM, which predicted the occurrence of SDM with the AUC of 0.845, the sensitivity of 87.50%, and the specificity of 77.63%. Conclusion Older age and family history of DM are independent risk factors of SDM in SLE patients. The predictive model constructed based on this model has good differentiation ability and high sensitivity, but its calibration ability is poor

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  • 在线发布日期: 2025-11-20
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