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Clinical Knowledge Supported Acute Kidney Injury (AKI) Risk Assessment Model for Elderly Patients

Author

Listed:
  • Kao-Yi Shen

    (Department of Banking & Finance, Chinese Culture University, Taipei 11114, Taiwan)

  • Yen-Ching Chuang

    (Taiwan Association of Health Industry Management and Development, Taipei 10351, Taiwan)

  • Tao-Hsin Tung

    (Evidence-Based Medicine Center, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai 317000, China)

Abstract

From the clinical viewpoint, the statistical approach is still the cornerstone for exploring many diseases. This study was conducted to explore the risk factors related to acute kidney injury (AKI) for elderly patients using the multiple criteria decision-making (MCDM) approach. Ten nephrologists from a teaching hospital in Taipei took part in forming the AKI risk assessment model. The key findings are: (1) Comorbidity and Laboratory Values would influence Comprehensive Geriatric Assessment; (2) Frailty is the highest influential AKI risk factor for elderly patients; and (3) Elderly patients could enhance their daily activities and nutrition to improve frailty and lower AKI risk. Furthermore, we illustrate how to apply MCDM methods to retrieve clinical experience from seasoned doctors, which may serve as a knowledge-based system to support clinical prognoses. In conclusion, this study has shed light on integrating multiple research approaches to assist medical decision-making in clinical practice.

Suggested Citation

  • Kao-Yi Shen & Yen-Ching Chuang & Tao-Hsin Tung, 2021. "Clinical Knowledge Supported Acute Kidney Injury (AKI) Risk Assessment Model for Elderly Patients," IJERPH, MDPI, vol. 18(4), pages 1-13, February.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:4:p:1607-:d:495736
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    Cited by:

    1. Chien-Lung Chan & Chi-Chang Chang, 2022. "Big Data, Decision Models, and Public Health," IJERPH, MDPI, vol. 19(14), pages 1-9, July.

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