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作 者:李蜜 蒋进[1] LI Mi;JIANG Jin(Department of Dermatology,Liyang People’s Hospital,213300,China)
机构地区:[1]溧阳市人民医院皮肤科,213300
出 处:《传染病信息》2024年第3期208-214,共7页Infectious Disease Information
摘 要:目的建立并验证包含3个临床参数的列线图预测模型,预测人类免疫缺陷病毒阴性早期梅毒患者治疗后出现血清固定的发生概率。方法检索溧阳市人民医院的门诊数据,将2017年9月1日至2019年9月30日诊治的431例早期梅毒患者纳入建模队列建立预测模型,将2019年11月1日至2022年12月30日诊治的172例早期梅毒患者纳入验证队列。采用单因素和多因素Logistic回归分析筛选出现血清固定状态的独立危险因素。根据回归系数绘制相应的列线图预测模型;采用曲线下面积值评价其区分度;通过校准曲线评估校准度;采用决策曲线分析评价净效益。结果多因素Logistic回归分析结果显示,年龄、初始快速血浆反应试验滴度和性生活时间点3个因素是患者出现血清固定状态的独立危险因素。列线图预测模型的曲线下面积在建模和验证队列中分别为0.816和0.726,显示出良好的性能。预测模型校准良好,决策曲线分析显示,当出现血清固定的阈值概率在75%~95%时,使用该模型预测出现血清固定的概率将获得净收益。结论该列线图预测模型可为非HIV感染的早期梅毒患者出现血清固定概率提供个体化预测。Objective A nomogram prediction model incorporating 3 clinical parameters was established and validated to accurately predict the likelihood of serofast state in HIV-negative patients with early syphilis following treatment.Methods A total of 603 patients with early syphilis and 431 patients were enrolled in a training cohort,while 172 patients were included in the validation cohort.The corresponding nomogram prediction model was drawn according to the logistic regression coefficients.Area under the curve(AUC)values were used to evaluate the discrimination.Calibration was evaluated with a calibration curve.The net benefit was performed via decision curve analysis(DCA).Results Multivariate logistic regression analysis showed that the three factors of age,RPR and sexual life time point were independent risk factors of serofast state.The nomogram showed a good performance as the AUCs of the nomogram were 0.816 in training and 0.726 in validation.Furthermore,decision curve analysis reveals a significant net benefit in utilizing this prediction model to estimate the probability of serofast state when the threshold probability ranges from 75%to 95%.Conclusions This nomogram can provide individualized prediction for the serofast state in patients with early syphilis.
分 类 号:R759.3[医药卫生—皮肤病学与性病学]
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