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

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.

The Exploring the Relationship between Financial Performance Indicators, ESG, and Stock Price Returns: A Rough Set-based Bipolar Approach

“…DEMATEL enables the identification of causal relationships and interdependencies within a system, helping decision-makers evaluate key elements. By visualizing the cause-and-effect relationships, DEMATEL analysis provides valuable insights into the structure of a problem or decision space, which has gained widespread applications in various fields, including healthcare [23], engineering [24], finance [25][26], and more. This approach is particularly useful in business, management, and policy domains where intricate relationships among variables need to be unraveled for informed decision-making.…”

Big Data, Decision Models, and Public Health

“…Unlike traditional statistics, the multiple criteria decision-making (MCDM) approach can support decision-makers in making rational judgments by considering multiple factors simultaneously, without presumed probabilistic distributions. The fifth paper, “ Clinical Knowledge Supported Acute Kidney Injury (AKI) Risk Assessment Model for Elderly Patients ”, by Shen et al [ 31 ], uses acute kidney injury (AKI) as an empirical case, based on the clinical experience of doctors, and develops a flexible knowledge-based system to support clinical prognoses. Statistics are still the cornerstone of understanding many illnesses in clinical research.…”