AIMC Topic: Intensive Care Units

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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...
Aged Male Middle Aged Sepsis Myocardial Infarction Prognosis Critical Illness Humans Intensive Care Units Machine Learning Female Algorithms
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Protocol for the impact of machine learning-based clinician decision support algorithims in perioperative care (IMAGINATIVE) in Singapore general hospital : a large prospective randomised controlled trial.

BMJ open Dec 20, 2024
INTRODUCTION: As surgical accessibility improves, the incidence of postoperative complications is expected to rise. The implementation of a precise and objective risk stratification tool holds the potential to mitigate these complications by early id...
Perioperative Care Male Decision Support Systems, Clinical Female Humans Randomized Controlled Trials as Topic Middle Aged Aged Machine Learning Elective Surgical Procedures Risk Assessment Prospective Studies Aged, 80 and over Singapore Postoperative Complications Intensive Care Units Young Adult Hospitals, General Adult
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Predictive modeling of ICU-AW inflammatory factors based on machine learning.

BMC neurology Dec 19, 2024
BACKGROUND: ICU-acquired weakness (ICU-AW) is a common complication among ICU patients. We used machine learning techniques to construct an ICU-AW inflammatory factor prediction model to predict the risk of disease development and reduce the incidenc...
Humans Machine Learning Intensive Care Units Female Aged Male Middle Aged Inflammation Muscle Weakness
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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...
Triglycerides Hospital Mortality Predictive Value of Tests Cause of Death Stroke Reproducibility of Results Prognosis Risk Factors Risk Assessment Humans Retrospective Studies Aged China Critical Illness Male Machine Learning Length of Stay Intensive Care Units Middle Aged Databases, Factual Blood Glucose Female Biomarkers Time Factors
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Predicting blood transfusion demand in intensive care patients after surgery by comparative analysis of temporally extended data selection.

BMC medical informatics and decision making Dec 18, 2024
BACKGROUND: Blood transfusion (BT) is a critical aspect of medical care for surgical patients in the Intensive Care Unit (ICU). Timely and accurate identification of BT needs can enhance patient outcomes and healthcare resource management.
Female Aged Adult Male Middle Aged Blood Transfusion Critical Care Netherlands Humans Machine Learning Retrospective Studies Intensive Care Units
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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 ...
Critical Illness Intensive Care Units Female Male Infant Machine Learning Retrospective Studies Continuous Renal Replacement Therapy Acute Kidney Injury Adolescent Child, Preschool Child Hospital Mortality ROC Curve Humans
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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...
Acute Disease Aged, 80 and over Retrospective Studies Humans Heart Failure Machine Learning Male Critical Illness Middle Aged Intensive Care Units Databases, Factual Hospital Mortality Female Predictive Value of Tests Aged
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Utility of an Echocardiographic Machine Learning Model to Predict Outcomes in Intensive Cardiac Care Unit Patients.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography Dec 14, 2024
INTRODUCTION: The risk stratification at admission to the intensive cardiac care unit (ICCU) is crucial and remains challenging.
Humans Machine Learning Prospective Studies Prognosis Intensive Care Units Middle Aged Risk Assessment Hospital Mortality Coronary Care Units Female Aged Male Echocardiography
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A Machine Learning Approach for Predicting In-Hospital Cardiac Arrest Using Single-Day Vital Signs, Laboratory Test Results, and International Classification of Disease-10 Block for Diagnosis.

Annals of laboratory medicine Dec 13, 2024
BACKGROUND: Predicting in-hospital cardiac arrest (IHCA) is crucial for potentially reducing mortality and improving patient outcomes. However, most models, which rely solely on vital signs, may not comprehensively capture the patients' risk profiles...
Humans Machine Learning Retrospective Studies Intensive Care Units Female Middle Aged ROC Curve International Classification of Diseases Vital Signs Heart Arrest Hospitalization Aged Aged, 80 and over Adult Male
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Employing artificial intelligence for optimising antibiotic dosages in sepsis on intensive care unit: a study protocol for a prospective observational study (KI.SEP).

BMJ open Dec 12, 2024
INTRODUCTION: In sepsis treatment, achieving and maintaining effective antibiotic therapy is crucial. However, optimal antibiotic dosing faces challenges due to significant variability among patients with sepsis. Therapeutic drug monitoring (TDM), th...
Drug Monitoring Artificial Intelligence Meropenem Machine Learning Humans Germany Research Design Piperacillin, Tazobactam Drug Combination Prospective Studies Anti-Bacterial Agents Intensive Care Units Female Sepsis Observational Studies as Topic
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