中性粒细胞/淋巴细胞比值(NLR)和预后营养指数(PNI)在帕金森病患者伴发抑郁中的预测价值
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南京医科大学附属淮安第一医院神经内科

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江苏省自然科学基金面上项目(编号:BK20191212);江苏省卫健委面上项目(编号:M2022082)


Predictive value of neutrophil-to-lymphocyte ratio (NLR) and prognostic nutritional index (PNI) in Parkinson"s disease patients with depression
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1.Department of Neurology,The Affiliated Huai’an NO People’s Hospital of Nanjing Medical University,Huai'2.'3.an;4.Department of Neurology,The Affiliated Huai’an NO 1 People’s Hospital of Nanjing Medical University,Huai'5.China

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    摘要:

    目的 探讨中性粒细胞/淋巴细胞比值(NLR)和预后营养指数(PNI)对帕金森病(PD)患者伴抑郁中的预测价值,构建并验证PD患者伴发抑郁风险的列线图预测模型。方法 连续收集就诊于淮安市第一人民医院的182例PD患者为PD组,根据HAMD-24评分将PD患者分为PD不伴抑郁组和PD伴抑郁组,并选取同期175名健康体检人群为健康对照组,进行组间临床资料差异比较,采用多因素logistic回归分析探讨PD患者伴发抑郁的影响因素,并据此构建和验证个体化预测PD患者伴发抑郁风险的列线图模型。结果 1. PD组PNI低于健康对照组,而NLR高于健康对照组(P<0.05)。2. PD伴抑郁组NLR、LED、H-Y分期、病程和UPDRS-III均高于PD不伴抑郁组,而PNI低于PD不伴抑郁组(P<0.05)。3. 多因素logistic回归分析结果显示NLR、LED和UPDRS-III的是PD患者伴发抑郁的独立危险因素,而PNI是PD患者伴发抑郁的独立保护因素。4. 基于多因素logistic回归分析结果构建个体化预测PD患者伴发抑郁风险的列线图模型,该列线图模型的ROC曲线下面积(AUC)为0.835(95%CI:0.776~0.893,P<0.01)。Hosmer-Lemeshow拟合度检验结果为χ2=11.576(P>0.05)。结合校准曲线和决策曲线可见该列线图模型具有较好的临床一致性和临床适用性。结论 基于PNI、NLR、LED和UPDRS-III构建的个体化列线图模型可有效预测PD患者伴发抑郁的风险,具有一定的临床应用价值。

    Abstract:

    Objective To explore the predictive value of neutrophil/lymphocyte ratio (NLR) and prognostic nutritional index (PNI) for Parkinson"s disease (PD) patients with depressive symptoms, and to construct and verify a nomogram prediction model for the risk of PD patients with depression. Methods One hundred and eighty-two patients with PD were recruited, and 175 healthy controls (HCs) matched for age and sex were admitted simultaneously. According to the HAMD-24 score, the patients with PD were divided into two groups: PD without depression group and PD with depression group. The differences in clinical data between the groups were compared, and a multivariate logistic regression analysis was used to explore the influencing factors of PD patients with depression, And based on this, construct and validate a column chart model for personalized prediction of the risk of depression in PD patients. Results (1) Compared with HCs, patients with PD showed lower PNI but higher NLR (P<0.05). (2) Compared with PD patients without depression, PD patients with depression showed higher levels of NLR, LED, H-Y stage, course of disease, and UPDRS-III; but lower level of PNI (P<0.05). (3) The results of multivariate logistic regression analysis showed that NLR, LED and UPDRS-III were independent risk factors for PD patients with depression; while PNI was an independent protective factor for PD patients with depression. (4) Based on the results of multivariate logistic regression analysis, a nomogram model was constructed to predict the risk of depression in PD patients. The area under the ROC curve (AUC) of the nomogram model was 0.835 (95%CI: 0.776-0.893, P<0.01). The Hosmer- Leme show test showed χ2=11.576 (P>0.05). Combining the calibration curve and decision curve, it was found that the nomogram model had good clinical consistency and clinical applicability. Conclusions The individualized nomogram model based on PNI, NLR, LED and UPDRS-III can effectively predict the risk of depression in patients with PD, and has certain clinical application value.

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  • 收稿日期:2023-09-07
  • 最后修改日期:2023-11-21
  • 录用日期:2023-11-27
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