Nugent James, Edmonds Andrew, Lusiama Jean, Thompson Deidre, Behets Frieda
From *Department of Pediatrics, Walter Reed National Military Medical Center, Bethesda, MD; †Department of Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC; ‡The University of Kinshasa, School of Public Health, Kinshasa, Democratic Republic of Congo; §Department of Epidemiology and School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC.
Pediatr Infect Dis J. 2014 Nov;33(11):1148-55. doi: 10.1097/INF.0000000000000454.
While highly active antiretroviral therapy (HAART) programs have been scaled up across sub-Saharan Africa, no prognostic models for the prediction of mortality risk for children initiating HAART are widely available. Current clinical prediction tools for human immunodeficiency virus (HIV)-infected children are derived from pre-HAART data and therefore cannot predict mortality for children initiating HAART. The purpose of this study was to develop a mortality risk scoring system for HIV-infected children beginning HAART in a resource-deprived setting.
Observational data from HIV-infected children initiating HAART from December 2004 through March 2012 in Kinshasa, Democratic Republic of Congo, were analyzed. Cox proportional hazards models were constructed to assess associations between demographic and clinical characteristics at the time of HAART initiation and mortality. Each child received a model-based risk score predicting mortality after HAART initiation.
By 31 March 2012, 1010 children had started HAART. One hundred three children (10.2%) died at a median of 5.3 months post-HAART initiation, yielding a mortality rate of 3.4 deaths per 100 child-years. The final mortality prediction model included undernutrition, low CD4 count, HIV symptoms, and low total lymphocyte count. These factors were highly predictive of mortality in the study population (C statistic = 0.79) and performed well when applied to the validation population (C statistic = 0.77).
Mortality among children starting HAART in resource-deprived settings can be predicted using a simple scoring system incorporating several readily available factors. Identifying predictors of mortality will help clinicians target modifiable risk factors, such as undernutrition, which are not directly addressed by HAART.
虽然高效抗逆转录病毒治疗（HAART）项目已在撒哈拉以南非洲地区扩大规模，但目前尚无广泛可用的预测开始接受HAART治疗的儿童死亡风险的预后模型。目前用于人类免疫缺陷病毒（HIV）感染儿童的临床预测工具源自HAART治疗前的数据，因此无法预测开始接受HAART治疗的儿童的死亡率。本研究的目的是为在资源匮乏地区开始接受HAART治疗的HIV感染儿童开发一种死亡风险评分系统。
分析了2004年12月至2012年3月在刚果民主共和国金沙萨开始接受HAART治疗的HIV感染儿童的观察数据。构建Cox比例风险模型，以评估开始接受HAART治疗时的人口统计学和临床特征与死亡率之间的关联。每个儿童都获得了一个基于模型的风险评分，用于预测开始接受HAART治疗后的死亡率。
截至2012年3月31日，1010名儿童开始接受HAART治疗。103名儿童（10.2%）在开始接受HAART治疗后的中位时间5.3个月时死亡，死亡率为每100儿童年3.4例死亡。最终的死亡预测模型包括营养不良、低CD4细胞计数、HIV症状和低总淋巴细胞计数。这些因素在研究人群中对死亡率具有高度预测性（C统计量=0.79），应用于验证人群时表现良好（C统计量=0.77）。
在资源匮乏地区，开始接受HAART治疗的儿童的死亡率可以使用一个简单的评分系统来预测，该系统纳入了几个容易获得的因素。识别死亡预测因素将有助于临床医生针对可改变的风险因素，如营养不良，而HAART治疗并未直接解决这些因素。
