ArticleNeuropsychiatric disease and treatment2024
Building and Validation of an Acute Event Prediction Model for Severe Mental Disorders.
Article in Neuropsychiatric disease and treatment, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Predicting the risk of mental disorders using complete blood count indicators: a machine learning approach.Frontiers in medicine · 2026Article
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8 authors.
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Abstract
Background: The global incidence of acute events in psychiatric patients is intensifying, and models to successfully predict acute events have attracted much attention. Objective: To explore the influence factors of acute incident severe mental disorders (SMDs) and the application of Rstudio statistical software, and build and verify a nomogram prediction model. Methods: SMDs were taken as research objects. The questionnaire survey method was adopted to collect data. Patients with acute event independent factors were screened. R software multivariable Logistic regression model was constructed and a nomogram was drawn. Results: A total of 342 patients with SMDs were hospitalized, and the number of patients who encountered acute events was 64, which accounted for 18.70% of all patients. Statistical significances were found in many aspects (all Conclusion: The constructed risk prediction model shows good prediction effectiveness in the acute events of patients with SMDs, which is helpful for the early detection of clinical mental health staff at high risk of acute events.
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