METHODS: A single-centre retrospective study was conducted on 245 patients with PNS admitted to Zibo Central Hospital from August 2020 to August 2022. According to the 36-Item Short-Form Health Survey (SF-36) for QOL evaluation, the patients were divided into the good QOL group (the total score ≥50 points) and poor QOL group (the total score <50 points). Univariate analysis was conducted by collecting clinical data from patients, and multiple logistic regression analysis was carried out on single factors with statistically significant differences to construct a clinical prediction model. The diagnostic efficacy of the prediction model was evaluated using the receiver operating characteristic (ROC) curve.
RESULTS: A total of 245 questionnaires were distributed, and 243 valid questionnaires were recovered, in which 143 cases had good QOL, with an average score of (71.86 ± 10.83) points, and 100 cases had poor QOL, with an average score of (40.03 ± 5.95) points. Statistical differences were observed in age, education level, monthly family average income, payment methods of medical expenses, albumin, 24-hour urinary protein quantification (24 h UPro) and serum uric acid (SUA) in both groups (p < 0.05), whereas no statistical difference was found in gender, body mass index (BMI) and marital status (p > 0.05). The multiple logistic regression analysis showed that age (X1), monthly family average income (X2), payment methods of medical expenses (X3), albumin (X4), 24 h UPro (X5) and SUA (X6) were risk factors for the QOL of patients with PNS, with Y = -12.105 + 0.130X1 + 0.457X2 + 0.448X3 + -0.161X4 + 0.823X5 + 0.025X6 as the regression prediction model. The results of ROC curve showed that the area under the curve (AUC) was 0.987 with standard error of 0.005 (p < 0.001), and 95% CI was 0.976-0.998.
CONCLUSIONS: Age, monthly family average income, payment methods of medical expenses, albumin, 24 h UPro and SUA are risk factors that affect the QOL of patients with PNS, and the construction of prediction model has good evaluation value and can provide a reference for clinical practice.
方法:对2020年8月至2022年8月淄博市中心医院收治的245例PNS患者进行单中心回顾性研究。根据用于QOL评估的36项短期健康调查(SF-36),将患者分为生活质量良好组(总分≥50分)和生活质量较差组(总分<50分)。通过收集患者的临床数据进行单变量分析,对差异有统计学意义的单因素进行多因素logistic回归分析,构建临床预测模型。使用受试者工作特征(ROC)曲线评估预测模型的诊断效能。
结果:共发放了245份问卷,回收有效问卷243份,其中143例QOL良好,平均得分为(71.86±10.83)分,100例生活质量差,平均得分为(40.03±5.95)分。在年龄上观察到统计学差异,教育水平,家庭月平均收入,医疗费用的支付方式,白蛋白,两组24小时尿蛋白定量(24hUPro)和血清尿酸(SUA)(p<0.05),而性别没有统计学差异,体重指数(BMI)和婚姻状况(p>0.05)。多因素Logistic回归分析显示,年龄(X1),家庭月平均收入(X2),医疗费用支付方式(X3),白蛋白(X4),24hUPro(X5)和SUA(X6)是影响PNS患者生活质量的危险因素,以Y=-12.105+0.130X1+0.457X2+0.448X3+-0.161X4+0.823X5+0.025X6为回归预测模型。ROC曲线结果显示曲线下面积(AUC)为0.987,标准误差为0.005(p<0.001),95%CI为0.976-0.998。
结论:年龄,家庭月平均收入,医疗费用的支付方式,白蛋白,24hUPro和SUA是影响PNS患者生活质量的危险因素,预测模型的构建具有较好的评价价值,可为临床实践提供参考。