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  4. Unveiling the risk: predicting out-of-hospital cardiac arrest in geriatric patients with depression - longitudinal study.
 
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Unveiling the risk: predicting out-of-hospital cardiac arrest in geriatric patients with depression - longitudinal study.

Journal
British Journal of Psychiatry
ISSN
1472-1465
Date Issued
2025-10-23
Author(s)
CHIH-WEI SUNG  
Chen, Cheng-Che
Chih, Yun-Ting
CHENG-YI FAN  
EDWARD PEI-CHUAN HUANG  
DOI
10.1192/bjp.2025.10427
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/736461
Abstract
Background The association between geriatric depression and out-of-hospital cardiac arrest (OHCA) has not been fully clarified. Aims This study aimed to develop and validate a predictive model for OHCA in older patients through a longitudinal, population-based approach. Method This study analysed data from the National Health Insurance Research Database for the period 2011–2020, focusing on older patients both diagnosed with depression and treated with antidepressant medications. A multivariate logistic regression model was used to identify potential predictors of OHCA. Considering the effect of COVID-19, data-sets from 2019 and 2020 were used as external validation. The model’s performance was evaluated using receiver operating characteristic (ROC) curves and confusion matrix metrics. Results Out of 104 022 geriatric patients with depression, 2479 (2.4%) experienced OHCA. Significant predictors of OHCA included age, male gender, previous utilisation of medical resources, renal failure with haemodialysis, existing comorbidities, medication changes and recent psychotherapy. The ROC values for the predictive models ranged from 0.707 to 0.771 in the 2019 and 2020 external validations for 7-, 30- and 90-day OHCA. For 2019, the 7-day model demonstrated sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio of 0.600, 0.718, 2.130, 0.560 and 3.840, respectively. For 2020, these metrics for the 7-day model were 0.775, 0.655, 2.250, 0.340 and 6.550, respectively. Conclusion This study developed and validated a predictive model for OHCA in older patients with depression. The model identified crucial predictors, providing valuable insights for psychiatrists and emergency clinicians to identify high-risk patients and implement early preventive measures.
Subjects
National Health Insurance Research Database
Out-of-hospital cardiac arrest
depression
geriatric
prediction model
Publisher
Cambridge University Press
Type
journal article

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To permanently archive and promote researcher profiles and scholarly works, Library integrates the services of “NTU Repository” with “Academic Hub” to form NTU Scholars.

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