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Comprehensive Geriatric Assessment as a predictor model for post-operative delirium in older adults undergoing major non-cardiac elective surgery

  • 0Division of Geriatrics, Department of Internal Medicine, Cipto Mangunkusumo National General Hospital - Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia.
Frontiers in Medicine +

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August 1, 2025

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August 1, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

Postoperative delirium in older adults undergoing major surgery is predicted by age, cognitive, and nutritional status. A developed model shows good calibration and moderate performance for predicting delirium incidence.

Area Of Science

  • Geriatric Medicine
  • Surgical Complications
  • Epidemiology

Background

  • Surgical needs in older adults are rising, with postoperative delirium being a common complication.
  • Comprehensive Geriatric Assessment (CGA) and risk stratification are crucial for prevention and prognosis.
  • Developing predictive models is essential for managing delirium in this population.

Purpose Of The Study

  • To determine the incidence of postoperative delirium in older adults after major non-cardiac elective surgery.
  • To develop a prediction model for postoperative delirium using identified risk factors.
  • To establish an applicable prognosis predictor for adverse outcomes.

Main Methods

  • Retrospective cohort study utilizing secondary data from medical records.
  • Analysis of 370 older adult inpatients undergoing major elective non-cardiac surgery (January 2020 - March 2023).
  • Statistical analysis using SPSS 20.0 and STATA 10, with Hosmer-Lemeshow test and AUC ROC for model development.

Main Results

  • The incidence of postoperative delirium was 6.8%.
  • Key predictors identified include age (HR=3.43), cognitive status (HR=2.74), and nutritional status (HR=3.35).
  • The prediction model demonstrated good calibration (p > 0.05) and moderate performance (AUC=0.750).

Conclusions

  • Age, cognitive status, and nutritional status are significant predictors of postoperative delirium.
  • The developed prediction model offers good calibration and moderate performance for identifying at-risk older adults.
  • These findings support the use of predictive models for managing surgical complications in the elderly.

Keywords:

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