ArticleFrontiers in neurology2026
A nomogram for predicting viral encephalitis based on cerebrospinal fluid biomarkers.
Article in Frontiers in neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: VE is a central nervous system infection of viral origin, and remains an important disease burden in recent years. Early identification of VE patients and timely interventions are crucial for optimizing clinical outcomes. Objective: This study aims to construct a predictive model for early detection of VE patients. Methods: The study retrospectively analyzed clinical data of 160 VE and 131 non-VE patients from China between January 2022 and March 2025. Data were split into training (70%, 203 cases) and validation (30%, 88 cases) cohorts. Predictor variables were identified via logistic regression analyses, and predictive models were established and validated. Model discrimination was assessed using ROC curves, calibration via H-L test and calibration curves, and clinical applicability via DCA. A nomogram was developed for result visualization. Results: Six covariates (ALB, Conclusion: This study's predictive model reliably identifies VE patients, offering a scientific basis for clinical decision-making and improving patient outcomes.
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