个体化症状网络连通性对HIV感染者健康预后的预测作用

Predictive effect of individualized symptom network connectivity on health outcomes in HIV-infected patients

目的 探索人类免疫缺陷病毒(HIV)感染者个体化症状网络连通性与CD4+T细胞计数、躯体健康和生活质量水平状况之间的纵向关系;以及个体化症状网络连通性在预测HIV感染者治疗预后的应用价值。方法 本研究为2021年6-12月在上海开展的一项前瞻性队列研究,使用经验取样法收集3个周期,共12个阶段27种症状的自我报告数据:第1个月(1~4周)、第4个月(5~8周)和第7个月(9~12周)。在第1个月、第4个月和第7个月进行网络分析,生成个体症状网络。为了评估症状网络连通性,本研究计算了单个网络分析中节点强度的总和。采用随机效应回归模型分析网络连通性与CD4+T细胞、生活质量和躯体健康水平状况之间的纵向关系。结果 共有144例HIV感染者参与研究,137例完成了基线和随访时的所有问卷调查。结果显示,症状网络的连通性越高,感染者躯体健康水平越差(β=0.003,P=0.036);而症状越严重,则感染者生活质量(β=-0.017,P<0.001)和躯体健康水平越低(β=-0.016,P<0.001)。结论 症状网络连通性是HIV感染者躯体健康水平的特异性预测指标,而症状严重程度与多个健康综合指标相关。医护人员可以考虑将网络指标:网络连通性纳入其症状评估指标,以提高预测感染者躯体健康水平预后的准确性。

Objective To explore the longitudinal relationship between individualized symptom network connectivity and CD4+T cell count,physical health status,quality of life in HIV-positive patients,and its application value of sindividualized symptom network connectivity in predicting the prognosis of HIV-positive patients after treatment.Methods A prospective cohort study was conducted in Shanghai from June to December 2021.Experience sampling methods were used to collect self-reported data on 27 symptoms across 12 phases:at the first month(Week 1~4),the fourth month(Week 5~8),and the seventh month(Week 9~12).Network analysis was conducted to generate individual symptom networks at the first month,the fourth month,and the seventh month.The sum of node strengths in the individual network analysis was calculated for assessment of symptom network connectivity.A random-effects regression model was used to analyze the longitudinal relationship between network connectivity and CD4+T count,quality of life,and overall physical health status.Results A total of 144 HIV-positive patients participated in the study,and 137 completed all questionnaires at baseline and follow-up.The results showed that the higher the connectivity of the symptom network,the worse the physical condition was(β=0.003,P=0.036);The more severe the symptoms,the worse the quality of life(β=-0.017,P<0.0001)and the lower the level of physical health(β=-0.016,P<0.001).Conclusion Symptom network connectivity is a specific predictor of physical health status in HIV-positive patients,while symptom severity is associated with multiple general indicators.Health care providers may consider including network indicators:network connectivity in their symptom assessment indicators to improve the accuracy of predicting the prognosis of physical health status of HIV-positive patients.