Artificial Intelligence-Based Models for Prediction of Mortality in ICU Patients: A Scoping Review.

BACKGROUND AND OBJECTIVE: Healthcare professionals may be able to anticipate more accurately a patient's timing of death and assess their possibility of recovery by implementing a real-time clinical decision support system. Using such a tool, the healthcare system can better understand a patient's condition and make more informed judgements about distributing limited resources. This scoping review aimed to analyze various death prediction AI (Artificial Intelligence) algorithms that have been used in ICU (Intensive Care Unit) patient populations. METHODS: The search strategy of this study involved keyword combinations of outcome and patient setting such as mortality, survival, ICU, terminal care. These terms were used to perform database searches in MEDLINE, Embase, and PubMed up to July 2022. The variables, characteristics, and performance of the identified predictive models were summarized. The accuracy of the models was compared using their Area Under the Curve (AUC) values. RESULTS: Databases search yielded an initial pool of 8271 articles. A two-step screening process was then applied: first, titles and abstracts were reviewed for relevance, reducing the pool to 429 articles. Next, a full-text review was conducted, further narrowing down the selection to 400 key studies. Out of 400 studies on different tools or models for prediction of mortality in ICUs, 16 papers focused on AI-based models which were ultimately included in this study that have deployed different AI-based and machine learning models to make a prediction about negative patient outcome. The accuracy and performance of the different models varied depending on the patient populations and medical conditions. It was found that AI models compared with traditional tools like SAP3 or APACHE IV score were more accurate in death prediction, with some models achieving an AUC of up to 92.9%. The overall mortality rate ranged from 5% to more than 60% in different studies. CONCLUSION: We found that AI-based models exhibit varying performance across different patient populations. To enhance the accuracy of mortality prediction, we recommend customizing models for specific patient groups and medical contexts. By doing so, healthcare professionals may more effectively assess mortality risk and tailor treatments accordingly. Additionally, incorporating additional variables-such as genetic information-into new models can further improve their accuracy.

Conceptual Approach to Body Fluids and Edema, Education Determines Clinical Outcomes in Heart Failure.

In this brief communication, we reemphasize the importance of critical thinking in clinical practice using the example of edema. The common practice of thinking and inquiry by practicing clinicians has beneficial implications for healthcare by improving outcomes and patient care while alleviating the burden of misconceptions in practice. We provide an in-depth and interactive investigation of physiological concepts as a foundation for understanding body fluid dynamics. Finally, we offer a new classification of symptoms of heart failure. DOI: 10.52547/ijkd.8171.

Conceptual Approach to Body Fluids and Edema, Education Determines Clinical Outcomes in Nephrotic Syndrome Management.

The objective of our paper is to reemphasize the importance of critical thinking in clinical practice and education in the field of internal medicine using the example of edema. We provide an in-depth and interactive investigation of physiological concepts as a foundation for the understanding of body fluid dynamics. Four fundamental concepts described are the hydrostatic and oncotic pressure gradients, capillary permeability, and lymphatic drainage. Furthermore, we visit the causes of edema in nephrotic syndrome. Traditional teaching considers hypoalbuminemia as a primary cause of edema formation in nephrotic syndrome. It has been proven that other etiologies causing edema include salt and water retention by the kidneys and a possible increase in capillary permeability are more important causes in the development of edema in nephrotic syndrome.