基于全身免疫炎症指数的预测帕金森病患者伴发抑郁的列线图模型构建

目的 探讨全身免疫炎症指数(SII)与帕金森病(PD)患者发生抑郁的关系及其预测价值。方法 选取2017年1月至2022年12月徐州医科大学附属淮安临床学院收治的PD患者146例为PD组，同期于该院体检的健康者160例为对照组。根据汉密尔顿抑郁量表24项(HAMD-24)评分将PD组患者分为PD不伴抑郁组(n=77)、PD轻度抑郁组(n=51)、PD中重度抑郁组(n=18)。收集各组一般资料及实验室资料，采用多因素Logistic回归分析筛选PD患者发生抑郁的影响因素，并据此构建列线图预测模型。结果 PD组淋巴细胞计数和血小板计数均低于对照组，SII高于对照组(P<0.05)。PD不伴抑郁组、PD轻度抑郁组、PD中重度抑郁组3组间的左旋多巴等效剂量(LED)、病程、SII、H-Y分期、统一帕金森病评定量表第三部分(UPDRSⅢ)评分比较，差异有统计学意义(P<0.05)。多因素Logistic回归分析结果显示，较高的SII和UPDRSⅢ评分是PD患者发生抑郁的独立危险因素。基于SII及UPDRSⅢ评分构建的列线图模型的ROC曲线显示，SII诊断PD患者发生抑郁的AUC为0....

Construction of a column chart model for predicting depression in Parkinson''s disease patients based on the systemic immune inflammation index

Objective To explore the relationship between systemic immune-inflammation index(SII)and theoccurrence of depression in patients with Parkinson''s disease(PD)and its predictive value.Methods A total of 146 PDpatients admitted to Huaian First Peoples Hospital fromJanuary2017 to December 2022 were selected as the PDgroup,and160 healthy individuals undergoing physical examination during the same period in thesame hospital were selected as thecontrol group.And the PDpatients were divided into PD withoutdepression group(n=77),mild depression group(n=51),and moderate to severe depression group(n=18)based on their Hamilton Depression Rating Scale-24(HAMD-24)scoreMultivariate Logistic regression analysis was conducted on the general data and laboratory data collected to screen theinfluencing factors ofdepression in PD patients,and a nomogram prediction model was constructedaccordingly.Results Thelymphocyte count and platelet count in the PD group were significantly lower than those in the control group,while the SIIwas significantly higher than that in thecontrol group(P<0.05).Therewere statistically significant differences inlevodopaequivalent dose(LED),disease duration,SII,Hoehn-Yahr (H-Y)staging,and Unified Parkinson''s Disease Rating Scale Ⅲ(UPDRSⅢ)scores among the PD without depression group,mild depression group,and moderate to severe depressiongroup(P<0.05).The results of the multivariate Logistic regression analysis showed that higher SII and UPDRS I scoreswere independent risk factors for depression in PD patients.The ROC curve ofthe nomogram model constructed based on SII and UPDRS I scores showed that the AUC of depression in PDpatients diagnosed bySII was 0.894(95%CI0.845-0.943,P<0.05),indicating good discriminative ability of the model.Additionally,the decision curve and calibration curve analysissuggested good clinical consistency andapplicability of themodel.Conclusion The nomogram model constructed based on SIand UPDRS III scores has good predictive valuefor depression in PD patients。