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Data_Sheet_1_Developing a rapid predictive model for falls in older hospitalized patients.docx

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Data_Sheet_1_Developing_a_rapid_predictive_model_for_falls_in_older_hospitalized_patients_docx/27148299
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BackgroundThis study was aimed to identify the independent risk factors for falls n hospitalized older patients and develop a corresponding predictive model. MethodsA retrospective observational study design was adopted, comprising 440 older patients with falls history and 510 older patients without falls history during hospitalization. Data collected included demographic information, vital signs, comorbidities, psychiatric disorder, function absent, current medication, other clinical indicators. ResultsMobility disability, high-risk medications use, frequency of hospitalizations, psychiatric disorder, visual impairment are independent risk factors for falls in older patients. The A-M2-HPV scoring system was developed. The AUC value of the nomogram was 0.884, indicating the model has excellent discriminative ability. The AUC value of the A-M2-HPV score was 0.788, demonstrating better discrimination and stratification capabilities. ConclusionThe A-M2-HPV scoring system provides a valuable tool to assess the risk of falls in hospitalized older patients and to aid in the implementation of preventive measures.
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2024-10-02
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