Establishment of a novel scoring model for mortality risk prediction in HIV-infected patients with cryptococcal meningitis

• Published in: BMC infectious diseases Vol. 21; no. 1; pp. 1 - 10
• Main Authors: 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
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 10.08.2021; BioMed Central; BMC
• Subjects: Age; Body temperature; CD4 antigen; Comorbidity; Consciousness; Creatinine; Cryptococcal meningitis; Glucose; Health risks; HIV; HIV infection; Hospitals; Human immunodeficiency virus; Infections; Infectious diseases; Intracranial pressure; Laboratories; Lymphocytes T; Medical prognosis; Medical statistics; Meningitis; Methods; Mortality; Neutrophils; Patients; Physicians; Pneumonia; Prognosis; Public health; Regression analysis; Risk analysis; Risk factors; Risk groups; RNA polymerase; Scoring model; Scoring models; Software; Statistical analysis; Urea; China
• ISSN: 1471-2334; 1471-2334
• 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.sup.+ 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.