Zhao Ting, Xu Xiao-Lei, Nie Jing-Min, Chen Xiao-Hong, Jiang Zhong-Sheng, Liu Shui-Qing, Yang Tong-Tong, Yang Xuan, Sun Feng, Lu Yan-Qiu, Harypursat Vijay, Chen Yao-Kai
Division of Infectious Diseases, Chongqing Public Health Medical Center, 109 Baoyu Road, Shapingba, Chongqing, 400036, China.
Department of Infectious Diseases, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang province, China.
BMC Infect Dis. 2021 Aug 10;21(1):786. doi: 10.1186/s12879-021-06417-9.
Cryptococcal meningitis (CM) remains a leading cause of death in HIV-infected patients, despite advances in CM diagnostic and therapeutic strategies. This study was performed with the aim to develop and validate a novel scoring model to predict mortality risk in HIV-infected patients with CM (HIV/CM).
Data on HIV/CM inpatients were obtained from a Multicenter Cohort study in China. Independent risk factors associated with mortality were identified based on data from 2013 to 2017, and a novel scoring model for mortality risk prediction was established. The bootstrapping statistical method was used for internal validation. External validation was performed using data from 2018 to 2020.
We found that six predictors, including age, stiff neck, impaired consciousness, intracranial pressure, CD4 T-cell count, and urea levels, were associated with poor prognosis in HIV/CM patients. The novel scoring model could effectively identify HIV/CM patients at high risk of death on admission (area under curve 0.876; p<0.001). When the cut-off value of 5.5 points or more was applied, the sensitivity and specificity was 74.1 and 83.8%, respectively. Our scoring model showed a good discriminatory ability, with an area under the curve of 0.879 for internal validation via bootstrapping, and an area under the curve of 0.886 for external validation.
Our developed scoring model of six variables is simple, convenient, and accurate for screening high-risk patients with HIV/CM, which may be a useful tool for physicians to assess prognosis in HIV/CM inpatients.
尽管隐球菌性脑膜炎(CM)的诊断和治疗策略取得了进展,但它仍然是HIV感染患者死亡的主要原因。本研究旨在开发并验证一种新型评分模型,以预测HIV感染的CM患者(HIV/CM)的死亡风险。
HIV/CM住院患者的数据来自中国的一项多中心队列研究。基于2013年至2017年的数据确定与死亡率相关的独立危险因素,并建立一种新型的死亡风险预测评分模型。采用自抽样统计方法进行内部验证。利用2018年至2020年的数据进行外部验证。
我们发现,包括年龄、颈部僵硬、意识障碍、颅内压、CD4 T细胞计数和尿素水平在内的六个预测因素与HIV/CM患者的预后不良相关。该新型评分模型能够有效识别入院时死亡风险高的HIV/CM患者(曲线下面积为0.876;p<0.001)。当应用5.5分及以上的临界值时,敏感性和特异性分别为74.1%和83.8%。我们的评分模型显示出良好的鉴别能力,通过自抽样进行内部验证时曲线下面积为0.879,外部验证时曲线下面积为0.886。
我们开发的包含六个变量的评分模型简单、便捷且准确,可用于筛查HIV/CM高危患者,这可能是医生评估HIV/CM住院患者预后的有用工具。