Selected article for: "curve area and cut off"

Author: 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
Title: Establishment of a novel scoring model for mortality risk prediction in HIV-infected patients with cryptococcal meningitis
  • Cord-id: 091hyvve
  • Document date: 2021_8_10
  • ID: 091hyvve
    Snippet: BACKGROUND: 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). METHODS: 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
    Document: BACKGROUND: 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). METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

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