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Development of a multidimensional 1-year mortality prediction model for patients discharged from the geriatric department: a longitudinal cohort study based on comprehensive geriatric assessment and clinical data

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Title: Development of a multidimensional 1-year mortality prediction model for patients discharged from the geriatric department: a longitudinal cohort study based on comprehensive geriatric assessment and clinical data
Authors: Jiaojiao Li, Lin Kang, Xiaohong Liu, Xiaohong Sun, Minglei Zhu, Qiumei Wang, Xuan Qu, Ning zhang, Eryu Xia, Fei Lu, Shuo Liu, Shuang Jin, Xueping Wang, Guojun Yao
Source: BMC Geriatrics, Vol 25, Iss 1, Pp 1-11 (2025)
Publisher Information: BMC, 2025.
Publication Year: 2025
Collection: LCC:Geriatrics
Subject Terms: Comprehensive geriatric assessment, Older adults, Prediction model, Palliative care, Geriatrics, RC952-954.6
More Details: Abstract Background A poor prognosis within 1 year of discharge is important when making decisions affecting postoperative geriatric inpatients. Comprehensive geriatric assessment (CGA) plays an important role in guiding holistic assessment-based interventions. However, current prognostic models derived from CGA and clinical data are limited and have unsatisfactory performance. We aimed to develop an accurate 1-year mortality prediction model for patients discharged from the geriatric ward using CGA and clinical data. Methods This longitudinal cohort study analysed data from 816 consecutively assessed geriatric patients between January 1, 2018 and December 31, 2019. Models were constructed using Cox proportional hazards regression and their validity was assessed by analysing discrimination, calibration, and decision curves. The robustness of the model was determined using sensitivity analysis. A nomogram was developed to predict the 1-year probability of mortality, and the model was validated using C-statistics, Brier scores, and calibration curves. Results During 644 patient-years of follow-up, 57 (11·7%) patients died. Clinical variables included in the final prediction model were activities of daily living, serum albumin level, Charlson Comorbidity Index, FRAIL scale, and Mini-Nutrition Assessment-Short Form scores. A C-statistic value of 0·911, a Brier score of 0·058, and a calibration curve validated the model. Conclusion Our risk stratification model can accurately predict prospective mortality risk among patients discharged from the geriatric ward. The functionality of this tool facilitates objective palliative care.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1471-2318
24639923
Relation: https://doaj.org/toc/1471-2318
DOI: 10.1186/s12877-025-05734-x
Access URL: https://doaj.org/article/22fa24639923448b90e70e14a849598e
Accession Number: edsdoj.22fa24639923448b90e70e14a849598e
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  Data: Development of a multidimensional 1-year mortality prediction model for patients discharged from the geriatric department: a longitudinal cohort study based on comprehensive geriatric assessment and clinical data
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  Data: <searchLink fieldCode="AR" term="%22Jiaojiao+Li%22">Jiaojiao Li</searchLink><br /><searchLink fieldCode="AR" term="%22Lin+Kang%22">Lin Kang</searchLink><br /><searchLink fieldCode="AR" term="%22Xiaohong+Liu%22">Xiaohong Liu</searchLink><br /><searchLink fieldCode="AR" term="%22Xiaohong+Sun%22">Xiaohong Sun</searchLink><br /><searchLink fieldCode="AR" term="%22Minglei+Zhu%22">Minglei Zhu</searchLink><br /><searchLink fieldCode="AR" term="%22Qiumei+Wang%22">Qiumei Wang</searchLink><br /><searchLink fieldCode="AR" term="%22Xuan+Qu%22">Xuan Qu</searchLink><br /><searchLink fieldCode="AR" term="%22Ning+zhang%22">Ning zhang</searchLink><br /><searchLink fieldCode="AR" term="%22Eryu+Xia%22">Eryu Xia</searchLink><br /><searchLink fieldCode="AR" term="%22Fei+Lu%22">Fei Lu</searchLink><br /><searchLink fieldCode="AR" term="%22Shuo+Liu%22">Shuo Liu</searchLink><br /><searchLink fieldCode="AR" term="%22Shuang+Jin%22">Shuang Jin</searchLink><br /><searchLink fieldCode="AR" term="%22Xueping+Wang%22">Xueping Wang</searchLink><br /><searchLink fieldCode="AR" term="%22Guojun+Yao%22">Guojun Yao</searchLink>
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  Data: BMC Geriatrics, Vol 25, Iss 1, Pp 1-11 (2025)
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  Data: Abstract Background A poor prognosis within 1 year of discharge is important when making decisions affecting postoperative geriatric inpatients. Comprehensive geriatric assessment (CGA) plays an important role in guiding holistic assessment-based interventions. However, current prognostic models derived from CGA and clinical data are limited and have unsatisfactory performance. We aimed to develop an accurate 1-year mortality prediction model for patients discharged from the geriatric ward using CGA and clinical data. Methods This longitudinal cohort study analysed data from 816 consecutively assessed geriatric patients between January 1, 2018 and December 31, 2019. Models were constructed using Cox proportional hazards regression and their validity was assessed by analysing discrimination, calibration, and decision curves. The robustness of the model was determined using sensitivity analysis. A nomogram was developed to predict the 1-year probability of mortality, and the model was validated using C-statistics, Brier scores, and calibration curves. Results During 644 patient-years of follow-up, 57 (11·7%) patients died. Clinical variables included in the final prediction model were activities of daily living, serum albumin level, Charlson Comorbidity Index, FRAIL scale, and Mini-Nutrition Assessment-Short Form scores. A C-statistic value of 0·911, a Brier score of 0·058, and a calibration curve validated the model. Conclusion Our risk stratification model can accurately predict prospective mortality risk among patients discharged from the geriatric ward. The functionality of this tool facilitates objective palliative care.
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