AIMC Topic: Critical Illness

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Methodological Review of Classification Trees for Risk Stratification: An Application Example in the Obesity Paradox.

Nutrients May 31, 2025
BACKGROUND: Classification trees (CTs) are widely used machine learning algorithms with growing applications in clinical research, especially for risk stratification. Their ability to generate interpretable decision rules makes them attractive to hea...
Algorithms Critical Illness Intensive Care Units Risk Assessment Humans Machine Learning Obesity Decision Trees Critical Care Obesity Paradox
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The extent of Skeletal muscle wasting in prolonged critical illness and its association with survival: insights from a retrospective single-center study.

BMC anesthesiology May 26, 2025
OBJECTIVE: Muscle wasting in critically ill patients, particularly those with prolonged hospitalization, poses a significant challenge to recovery and long-term outcomes. The aim of this study was to characterize long-term muscle wasting trajectories...
Psoas Muscles Muscular Atrophy Female Aged Adult Male Middle Aged Length of Stay Respiratory Distress Syndrome Muscle, Skeletal Retrospective Studies Tomography, X-Ray Computed Critical Illness Intensive Care Units Humans COVID-19
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Association between fibrinogen levels and prognosis in critically bleeding patients: exploration of the optimal therapeutic threshold.

European journal of trauma and emergency surgery : official publication of the European Trauma Society May 23, 2025
BACKGROUND: Severe bleeding is a leading cause of ICU admission and mortality. Fibrinogen plays a crucial role in prognosis, yet optimal thresholds and supplementation targets remain unclear.
Propensity Score Intensive Care Units Female Aged Male Middle Aged Hospital Mortality Fibrinogen Hemorrhage Humans Prognosis Critical Illness
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Development of a risk prediction model for secondary infection in severe/critical COVID-19 patients.

BMC infectious diseases May 21, 2025
OBJECTIVE: This study aimed to develop a predictive model for secondary infections in patients with severe or critical COVID-19 by analyzing clinical characteristics and laboratory indicators.
Female SARS-CoV-2 Risk Factors Aged Adult Male Middle Aged Risk Assessment Machine Learning COVID-19 Retrospective Studies Critical Illness Humans Coinfection Respiration, Artificial Severity of Illness Index Procalcitonin Interleukin-8
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Construction and validation of a pain facial expressions dataset for critically ill children.

Scientific reports May 17, 2025
Automatic pain assessment for non-communicative children is in high demand. However, the availability of related training datasets remains limited. This study focuses on creating a large-scale dataset of pain facial expressions specifically for Chine...
Pain Humans Critical Illness Facial Expression Female Child, Preschool Child Intensive Care Units, Pediatric Pain Measurement Male Infant Deep Learning Adolescent
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Enriching patient populations in ICU trials: reducing heterogeneity through machine learning.

Current opinion in critical care May 2, 2025
PURPOSE OF REVIEW: Despite the pivotal role of randomized controlled trials (RCTs) in critical care research, many have failed to demonstrate significant benefits, particularly in nutrition interventions. This review highlights how patient heterogene...
Research Design Humans Precision Medicine Artificial Intelligence Critical Illness Randomized Controlled Trials as Topic Machine Learning Intensive Care Units Patient Selection Critical Care
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Timing of kidney replacement therapy in critically ill patients: A call to shift the paradigm in the era of artificial intelligence.

Science progress Apr 24, 2025
Acute kidney injury (AKI) is a common condition in intensive care units (ICUs) and is associated with high mortality rates, particularly when kidney replacement therapy (KRT) becomes necessary. The optimal timing for initiating KRT remains a subject ...
Acute Kidney Injury Humans Critical Illness Artificial Intelligence Intensive Care Units Renal Replacement Therapy Time Factors
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A machine learning model to predict intradialytic hypotension in pediatric continuous kidney replacement therapy.

Pediatric nephrology (Berlin, Germany) Apr 3, 2025
BACKGROUND: Intradialytic hypotension (IDH) is associated with mortality in adults undergoing intermittent hemodialysis, but this relationship is unclear in critically ill children receiving continuous kidney replacement therapy (CKRT). We aim to eva...
Female Male Infant Renal Dialysis Machine Learning Retrospective Studies Continuous Renal Replacement Therapy Critical Illness Intensive Care Units, Pediatric ROC Curve Predictive Value of Tests Hypotension Adolescent Child, Preschool Child Hospital Mortality Humans
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Interpretable machine learning model for early prediction of disseminated intravascular coagulation in critically ill children.

Scientific reports Apr 2, 2025
Disseminated intravascular coagulation (DIC) is a thrombo-hemorrhagic disorder that can be life-threatening in critically ill children, and the quest for an accurate and efficient method for early DIC prediction is of paramount importance. Candidate ...
Disseminated Intravascular Coagulation Humans Machine Learning Child, Preschool Child Logistic Models Support Vector Machine Critical Illness Female Infant, Newborn Male Infant Adolescent
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The future of artificial intelligence in cardiovascular monitoring.

Current opinion in critical care Mar 24, 2025
PURPOSE OF REVIEW: Cardiovascular monitoring is essential for managing hemodynamic instability and preventing complications in critically ill patients. Conventional monitoring approaches are limited by predefined thresholds, dependence on clinician e...
Humans Artificial Intelligence Critical Illness Intensive Care Units Hemodynamic Monitoring Hemodynamics Wearable Electronic Devices Monitoring, Physiologic Critical Care
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