AIMC Topic: Critical Illness

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An artificial intelligence application to predict prolonged dependence on mechanical ventilation among patients with critical orthopaedic trauma: an establishment and validation study.

BMC musculoskeletal disorders Dec 30, 2024
BACKGROUND: Prolonged dependence on mechanical ventilation is a common occurrence in clinical ICU patients and presents significant challenges for patient care and resource allocation. Predicting prolonged dependence on mechanical ventilation is cruc...
Male Critical Illness Middle Aged Humans Intensive Care Units Risk Assessment Artificial Intelligence Female Respiration, Artificial Support Vector Machine Machine Learning Aged Time Factors Retrospective Studies Adult Predictive Value of Tests
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Allogenic faecal microbiota transplantation for antibiotic-associated diarrhoea in critically ill patients (FEBATRICE)-Study protocol for a multi-centre randomised controlled trial (phase II).

PloS one Dec 27, 2024
BACKGROUND: Exposure of critically ill patients to antibiotics lead to intestinal dysbiosis, which often manifests as antibiotic-associated diarrhoea. Faecal microbiota transplantation restores gut microbiota and may lead to faster resolution of diar...
Female Fecal Microbiota Transplantation Humans Clinical Trials, Phase II as Topic Male Anti-Bacterial Agents Dysbiosis Diarrhea Prospective Studies Multicenter Studies as Topic Feces Critical Illness Randomized Controlled Trials as Topic Gastrointestinal Microbiome
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Comparison of population pharmacokinetic modeling and machine learning approaches for predicting voriconazole trough concentrations in critically ill patients.

International journal of antimicrobial agents Dec 26, 2024
BACKGROUND: Despite the widespread use of voriconazole in antifungal treatment, its high pharmacokinetic and pharmacodynamic variability may lead to suboptimal efficacy, especially in intensive care unit (ICU) patients. Machine learning (ML), an arti...
Male Middle Aged Antifungal Agents Bayes Theorem Intensive Care Units Voriconazole Humans Female Machine Learning Aged Critical Illness Adult
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Machine learning for predicting acute myocardial infarction in patients with sepsis.

Scientific reports Dec 24, 2024
Acute myocardial infarction (AMI) and sepsis are the leading causes of high mortality rates in intensive care units. While sepsis frequently affects the cardiovascular system, distinguishing between sepsis-induced cardiomyopathy and AMI remains chall...
Middle Aged Sepsis Myocardial Infarction Humans Machine Learning Algorithms Prognosis Critical Illness Intensive Care Units Female Aged Male
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Exploring the prognostic impact of triglyceride-glucose index in critically ill patients with first-ever stroke: insights from traditional methods and machine learning-based mortality prediction.

Cardiovascular diabetology Dec 18, 2024
BACKGROUND: The incidence and mortality of first-ever strokes have risen sharply, especially in the intensive care unit (ICU). Emerging surrogate for insulin resistance, triglyceride-glucose index (TyG), has been linked to stroke prognosis. We aims t...
Machine Learning Databases, Factual Biomarkers Prognosis Retrospective Studies Humans Aged Male Middle Aged Risk Assessment China Critical Illness Intensive Care Units Female Reproducibility of Results Risk Factors Predictive Value of Tests Cause of Death Stroke Triglycerides Length of Stay Blood Glucose Time Factors Hospital Mortality
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Machine Learning-Based Prediction Model for ICU Mortality After Continuous Renal Replacement Therapy Initiation in Children.

Critical care explorations Dec 17, 2024
BACKGROUND: Continuous renal replacement therapy (CRRT) is the favored renal replacement therapy in critically ill patients. Predicting clinical outcomes for CRRT patients is difficult due to population heterogeneity, varying clinical practices, and ...
ROC Curve Adolescent Child, Preschool Child Hospital Mortality Machine Learning Retrospective Studies Continuous Renal Replacement Therapy Acute Kidney Injury Critical Illness Intensive Care Units Humans Female Male Infant
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Machine Learning for In-hospital Mortality Prediction in Critically Ill Patients With Acute Heart Failure: A Retrospective Analysis Based on the MIMIC-IV Database.

Journal of cardiothoracic and vascular anesthesia Dec 16, 2024
BACKGROUND: The incidence, mortality, and readmission rates for acute heart failure (AHF) are high, and the in-hospital mortality for AHF patients in the intensive care unit (ICU) is higher. However, there is currently no method to accurately predict...
Female Aged Aged, 80 and over Male Middle Aged Hospital Mortality Predictive Value of Tests Acute Disease Heart Failure Machine Learning Databases, Factual Humans Retrospective Studies Critical Illness Intensive Care Units
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Early prediction of intensive care unit admission in emergency department patients using machine learning.

Australian critical care : official journal of the Confederation of Australian Critical Care Nurses Dec 5, 2024
BACKGROUND: The timely identification and transfer of critically ill patients from the emergency department (ED) to the intensive care unit (ICU) is important for patient care and ED workflow practices.
Humans Machine Learning Retrospective Studies Critical Illness Male Middle Aged Triage Emergency Service, Hospital Patient Admission Intensive Care Units Electronic Health Records Female Aged Adult
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Construction and validation of a machine learning-based prediction model for short-term mortality in critically ill patients with liver cirrhosis.

Clinics and research in hepatology and gastroenterology Nov 30, 2024
OBJECTIVE: Critically ill patients with liver cirrhosis generally have a poor prognosis due to complications such as multiple organ failure. This study aims to develop a machine learning-based prediction model to forecast short-term mortality in crit...
Middle Aged Liver Cirrhosis Intensive Care Units Female Aged Male Humans Machine Learning Prognosis Critical Illness
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Developing a prediction model for cognitive impairment in older adults following critical illness.

BMC geriatrics Nov 29, 2024
BACKGROUND: New or worsening cognitive impairment or dementia is common in older adults following an episode of critical illness, and screening post-discharge is recommended for those at increased risk. There is a need for prediction models of post-I...
Dementia Humans Cohort Studies Machine Learning Aged, 80 and over North Carolina Critical Illness Intensive Care Units Male Electronic Health Records Middle Aged Female Risk Assessment Aged Cognitive Dysfunction
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