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Machine Learning Models for the Early Real-Time Prediction of Deterioration in Intensive Care Units-A Novel Approach to the Early Identification of High-Risk Patients.
J Clin Med
January 2025
Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, 22083 Berlin, Germany.
Predictive machine learning models have made use of a variety of scoring systems to identify clinical deterioration in ICU patients. However, most of these scores include variables that are dependent on medical staff examining the patient. We present the development of a real-time prediction model using clinical variables that are digital and automatically generated for the early detection of patients at risk of deterioration.
View Article and Find Full Text PDFThe Need for Standardized Guidelines for the Use of Monocyte Distribution Width (MDW) in the Early Diagnosis of Sepsis.
J Pers Med
December 2024
Department of Emergency Medicine, Fondazione Policlinico Universitario A. Gemelli-IRCCS, 00168 Rome, Italy.
Sepsis is a complex and potentially life-threatening syndrome characterized by an abnormal immune response to an infection, which can lead to organ dysfunction, septic shock, and death. Early diagnosis is crucial to improving prognosis and reducing hospital management costs. This narrative review aims to summarize and evaluate the current literature on the role of monocyte distribution width (MDW) as a diagnostic biomarker for sepsis, highlighting its advantages, limitations, and potential clinical applications.
View Article and Find Full Text PDFReal-time estimated Sequential Organ Failure Assessment (SOFA) score with intervals: improved risk monitoring with estimated uncertainty in health condition for patients in intensive care units.
Health Inf Sci Syst
December 2025
Department of Cardiac, Thoracic and Vascular Surgery, National University Hospital, Singapore, Singapore.
Article Synopsis
- Real-time risk monitoring is essential in ICUs but often struggles with a lack of updates for clinical variables, prompting the development of a new framework that incorporates uncertainties into existing risk assessment systems like the SOFA score.
- The study analyzed data from 5,351 patients in a Cardiothoracic ICU, utilizing machine learning models to enhance real-time SOFA scores and account for uncertainties, with validation showing improved predictive capabilities for mortality and readmission.
- Results demonstrated that the new model outperformed traditional SOFA scores and quick SOFA in predicting outcomes, suggesting it could lead to more efficient testing and better patient care in clinical settings.
Comparative Analysis of qSOFA, PRIEST, PAINT, and ISARIC4C Scores in Predicting Severe COVID-19 Outcomes Among Patients Aged over 75 Years.
Diseases
November 2024
Discipline of Parasitology, Department of Infectious Diseases, "Victor Babes" University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square 2, 300041 Timisoara, Romania.
Background: Elderly patients, particularly those over 75 years old, have been disproportionately affected by COVID-19, exhibiting higher rates of severe outcomes, such as ICU admissions and mortality. This study aimed to evaluate and compare the effectiveness of various clinical scoring systems-qSOFA, PRIEST, PAINT, and ISARIC4C-in predicting ICU admission, the need for mechanical ventilation, and mortality among elderly COVID-19 patients.
Methods: In this retrospective cohort study conducted at two tertiary care hospitals, 131 elderly patients (aged ≥ 75) and 226 younger controls (aged < 65) with confirmed COVID-19 were included.
PRISMA-7 is a predictor of intensive care unit admission and mortality in older patients in an emergency department.
Geriatr Gerontol Int
January 2025
Department of Health Programs, Vocational School of Health Services, Sivas Cumhuriyet University, Sivas, Turkey.
Article Synopsis
- The study aimed to compare the effectiveness of the PRISMA-7 tool for assessing frailty in elderly patients against qSOFA and ESI in predicting 28-day mortality and ICU admissions.
- Patients aged over 65 admitted to a hospital in Turkey were studied, evaluating their mortality and ICU admission rates over 28 days.
- Results indicated that PRISMA-7 was more effective than qSOFA and similarly effective as ESI for predicting mortality and hospitalization, establishing its reliability in emergency settings.
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