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Development of a multidimensional 1-year mortality prediction model for patients discharged from the geriatric

Jiaojiao Li1, Lin Kang2, Xiaohong Liu3

  • 1Department of Geriatrics, Peking Union Medical College, Chinese Academy of Medical Sciences, Peking Union Medical College Hospital, No.1 Shuaifuyuan, Wangfujing, Dongcheng District, Beijing, 100730, China.

BMC Geriatrics
|April 8, 2025
PubMed

Insights

This study developed a new risk model for predicting 1-year mortality in geriatric patients after hospital discharge. The model accurately identifies high-risk individuals, aiding in better palliative care decisions.

Area of Science:

  • Geriatric Medicine
  • Clinical Epidemiology
  • Biostatistics

Background:

  • Post-discharge mortality in geriatric inpatients poses a significant challenge.
  • Comprehensive Geriatric Assessment (CGA) aids interventions but current prognostic models lack accuracy.
  • There is a need for improved prediction of 1-year mortality in this population.

Purpose of the Study:

  • To develop and validate an accurate model for predicting 1-year mortality in geriatric patients post-discharge.
  • To utilize Comprehensive Geriatric Assessment (CGA) and clinical data for enhanced prognostic performance.
  • To provide a tool for objective risk stratification and improved palliative care decisions.

Main Methods:

  • A longitudinal cohort study of 816 geriatric patients was conducted.
  • Cox proportional hazards regression was used to construct the prediction model.
  • Model validity was assessed using discrimination, calibration, C-statistics, Brier scores, and calibration curves, with sensitivity analysis for robustness.

Main Results:

  • The final model included activities of daily living, serum albumin, Charlson Comorbidity Index, FRAIL scale, and Mini-Nutrition Assessment-Short Form scores.
  • The model demonstrated high predictive accuracy with a C-statistic of 0.911 and a Brier score of 0.058.
  • A nomogram was developed for practical prediction of 1-year mortality probability.

Conclusions:

  • The developed risk stratification model accurately predicts prospective mortality risk in geriatric patients post-discharge.
  • This validated tool supports objective decision-making for palliative care.
  • The model enhances the utility of Comprehensive Geriatric Assessment (CGA) in clinical practice.
Abstract

Keywords:
Comprehensive geriatric assessmentOlder adultsPalliative carePrediction model

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