Prognostic Models for 9-Month Mortality in Tuberculous Meningitis

结核性脑膜炎9个月死亡率的预后模型

阅读:1

Abstract

BACKGROUND: Tuberculous meningitis (TBM) is the most severe form of extrapulmonary tuberculosis. We developed and validated prognostic models for 9-month mortality in adults with TBM, with or without human immunodeficiency virus (HIV) infection. METHODS: We included 1699 subjects from 4 randomized clinical trials and 1 prospective observational study conducted at 2 major referral hospitals in Southern Vietnam from 2001-2015. Modeling was based on multivariable Cox proportional hazards regression. The final prognostic models were validated internally and temporally and were displayed using nomograms and a Web-based app (https://thaole.shinyapps.io/tbmapp/). RESULTS: 951 HIV-uninfected and 748 HIV-infected subjects with TBM were included; 219 of 951 (23.0%) and 384 of 748 (51.3%) died during 9-month follow-up. Common predictors for increased mortality in both populations were higher Medical Research Council (MRC) disease severity grade and lower cerebrospinal fluid lymphocyte cell count. In HIV-uninfected subjects, older age, previous tuberculosis, not receiving adjunctive dexamethasone, and focal neurological signs were additional risk factors; in HIV-infected subjects, lower weight, lower peripheral blood CD4 cell count, and abnormal plasma sodium were additional risk factors. The areas under the receiver operating characteristic curves (AUCs) for the final prognostic models were 0.77 (HIV-uninfected population) and 0.78 (HIV-infected population), demonstrating better discrimination than the MRC grade (AUC, 0.66 and 0.70) or Glasgow Coma Scale score (AUC, 0.68 and 0.71) alone. CONCLUSIONS: The developed models showed good performance and could be used in clinical practice to assist physicians in identifying patients with TBM at high risk of death and with increased need of supportive care.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。