Brain Sciences, University of New South Wales, Sydney, Australia.
HIV Med. 2010 Nov;11(10):642-9. doi: 10.1111/j.1468-1293.2010.00834.x.
HIV physicians have limited time for cognitive screening. Here we developed an extra-brief, clinically based tool for predicting HIV-associated neurocognitive impairment (HAND) in order to determine which HIV-positive individuals require a more comprehensive neurological/neuropsychological (NP) assessment.
Ninety-seven HIV-positive individuals with advanced disease recruited in an HIV out-patient clinic received standard NP testing. A screening algorithm was developed using support vector machines, an optimized prediction procedure for classifying individuals into two groups (here NP-impaired and NP-normal) based on a set of predictors.
The final algorithm utilized age, current CD4 cell count, past central nervous system HIV-related diseases and current treatment duration and required approximately 3 min to complete, with a good overall prediction accuracy of 78% (against the gold standard; NP-impairment status derived from standard NP testing) and a good specificity of 70%.
This noncognitive-based algorithm should prove useful to identify HIV-infected patients with advanced disease at high risk of HAND who require more formal assessment. We propose staged guidelines, using the algorithm, for improved HAND therapeutic management. Future larger, international studies are planned to test the predictive effect of nadir CD4 cell count, hepatitis C virus infection, gender, ethnicity and HIV viral clade. We recommend the use of this first version for HIV-infected Caucasian men with advanced disease.
艾滋病毒医生用于认知筛查的时间有限。为此，我们开发了一种额外的简短、基于临床的工具，用于预测与艾滋病毒相关的神经认知障碍 (HAND)，以确定哪些 HIV 阳性个体需要更全面的神经学/神经心理学 (NP) 评估。
在一家艾滋病毒门诊诊所招募了 97 名患有晚期疾病的 HIV 阳性个体，他们接受了标准的 NP 测试。使用支持向量机开发了一种筛选算法，这是一种优化的预测程序，用于根据一组预测因子将个体分为两组（这里是 NP 受损和 NP 正常）。
最终算法利用了年龄、当前 CD4 细胞计数、过去中枢神经系统 HIV 相关疾病以及当前治疗持续时间，完成大约需要 3 分钟，整体预测准确性为 78%（针对金标准；NP 损伤状态源自标准 NP 测试）和良好的特异性为 70%。
这种基于非认知的算法应该有助于识别患有晚期疾病、HAND 风险高的 HIV 感染患者，这些患者需要更正式的评估。我们提出了分阶段的指南，使用该算法来改善 HAND 的治疗管理。未来计划进行更大规模的国际研究，以测试最低 CD4 细胞计数、丙型肝炎病毒感染、性别、种族和 HIV 病毒群的预测效果。我们建议将此第一个版本用于患有晚期疾病的 HIV 感染白种男性。
