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Risk Prediction Models for Invasive Mechanical Ventilation in Patients with Autoimmune Encephalitis: A Retrospective Cohort Study

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收录情况： ◇ SCIE

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机构： [1]Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China. [2]Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China. [3]Department of Neurology, Key Laboratory for Neurological Big Data of Liaoning Province, The First Affiliated Hospital of China Medical University, Shenyang, China. [4]Department of Neurosurgery, The First Hospital of China Medical University, Shenyang, China.

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A multivariate predictive nomogram model was developed using the risk factors identified by LASSO regression and assessed by receiver operator characteristics (ROC) curve, calibration curve, and decision curve analysis.The risk factors predictive of severe respiratory failure were male gender, impaired hepatic function, elevated intracranial pressure, and higher neuron-specific enolase. The final nomogram achieved an AUC of 0.770. After validation by bootstrapping, a concordance index of 0.748 was achieved.Our nomogram accurately predicted the risk of developing respiratory failure needing IMV in AE patients and provide clinicians with a simple and effective tool to guide treatment interventions in the AE patients.Copyright © 2023 Shiyang Xie et al.

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出版当年[2022]版：

大类 | 3 区医学

小类 | 4 区免疫学

最新[2023]版：

大类 | 3 区医学

小类 | 4 区免疫学

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出版当年[2021]版：

Q3 IMMUNOLOGY

最新[2023]版：

Q2 IMMUNOLOGY

影响因子： 3.5 最新[2023版] 4.2 最新五年平均 4.493 出版当年[2021版] 5.601 出版当年五年平均 4.818 出版前一年[2020版] 4.1 出版后一年[2022版]

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第一作者机构： [1]Department of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China.

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