AIMC Topic: 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...
Cognitive Dysfunction Dementia Cohort Studies North Carolina Aged, 80 and over Male Middle Aged Risk Assessment Humans Machine Learning Critical Illness Intensive Care Units Electronic Health Records Female Aged
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Prognostic value of glycaemic variability for mortality in critically ill atrial fibrillation patients and mortality prediction model using machine learning.

Cardiovascular diabetology Nov 26, 2024
BACKGROUND: The burden of atrial fibrillation (AF) in the intensive care unit (ICU) remains heavy. Glycaemic control is important in the AF management. Glycaemic variability (GV), an emerging marker of glycaemic control, is associated with unfavourab...
Male Middle Aged Risk Assessment Blood Glucose Time Factors Reproducibility of Results Risk Factors Aged Aged, 80 and over Glycemic Control Hospital Mortality Predictive Value of Tests Cause of Death Atrial Fibrillation Machine Learning Decision Support Techniques Databases, Factual Biomarkers Prognosis Retrospective Studies Critical Illness Intensive Care Units Female Humans
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Factors and machine learning models for predicting successful discontinuation of continuous renal replacement therapy in critically ill patients with acute kidney injury: a retrospective cohort study based on MIMIC-IV database.

BMC nephrology Nov 12, 2024
BACKGROUND: For critically ill patients with acute kidney injury (AKI), there remains controversy regarding the predictive factors affecting the discontinuation of continuous renal replacement therapy (CRRT). This study aims to explore factors associ...
Humans Machine Learning Databases, Factual Retrospective Studies Aged Male Middle Aged Cohort Studies Withholding Treatment Continuous Renal Replacement Therapy Acute Kidney Injury Critical Illness Female
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Impact of nutrition-related laboratory tests on mortality of patients who are critically ill using artificial intelligence: A focus on trace elements, vitamins, and cholesterol.

Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition Oct 25, 2024
BACKGROUND: This study aimed to understand the collective impact of trace elements, vitamins, cholesterol, and prealbumin on patient outcomes in the intensive care unit (ICU) using an advanced artificial intelligence (AI) model for mortality predicti...
Retrospective Studies Critical Illness Intensive Care Units Female Aged Humans Artificial Intelligence ROC Curve Vitamins Cholesterol Nutritional Status Prealbumin Male Middle Aged Trace Elements Hospital Mortality
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Prognosis of major bleeding based on residual variables and machine learning for critical patients with upper gastrointestinal bleeding: A multicenter study.

Journal of critical care Oct 2, 2024
BACKGROUND: Upper gastrointestinal bleeding (UGIB) is a significant cause of morbidity and mortality worldwide. This study investigates the use of residual variables and machine learning (ML) models for predicting major bleeding in patients with seve...
Middle Aged Gastrointestinal Hemorrhage Humans Machine Learning Algorithms Critical Illness Prognosis Intensive Care Units Female Aged Male
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From bytes to bedside: a systematic review on the use and readiness of artificial intelligence in the neonatal and pediatric intensive care unit.

Intensive care medicine Sep 12, 2024
PURPOSE: Despite its promise to enhance patient outcomes and support clinical decision making, clinical use of artificial intelligence (AI) models at the bedside remains limited. Translation of advancements in AI research into tangible clinical benef...
Intensive Care Units, Pediatric Intensive Care Units, Neonatal Humans Artificial Intelligence Critical Illness Infant, Newborn Child
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A machine learning-based prediction of hospital mortality in mechanically ventilated ICU patients.

PloS one Sep 4, 2024
BACKGROUND: Mechanical ventilation (MV) is vital for critically ill ICU patients but carries significant mortality risks. This study aims to develop a predictive model to estimate hospital mortality among MV patients, utilizing comprehensive health d...
Middle Aged Intensive Care Units Respiration, Artificial Humans Female Hospital Mortality Machine Learning Aged Support Vector Machine Databases, Factual Male Critical Illness
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Construction and evaluation of a mortality prediction model for patients with acute kidney injury undergoing continuous renal replacement therapy based on machine learning algorithms.

Annals of medicine Aug 19, 2024
BACKGROUND: To construct and evaluate a predictive model for in-hospital mortality among critically ill patients with acute kidney injury (AKI) undergoing continuous renal replacement therapy (CRRT), based on nine machine learning (ML) algorithm.
Retrospective Studies Risk Assessment Continuous Renal Replacement Therapy Hospital Mortality Acute Kidney Injury ROC Curve Critical Illness Nomograms Intensive Care Units United States Female Humans Aged Machine Learning Male Algorithms Middle Aged
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Unraveling the impact of therapeutic drug monitoring via machine learning for patients with sepsis.

Cell reports. Medicine Aug 9, 2024
Clinical studies investigating the benefits of beta-lactam therapeutic drug monitoring (TDM) among critically ill patients are hindered by small patient groups, variability between studies, patient heterogeneity, and inadequate use of TDM. Accordingl...
Humans Machine Learning Algorithms Anti-Bacterial Agents Critical Illness Female Aged Male Middle Aged Sepsis Drug Monitoring Organ Dysfunction Scores beta-Lactams
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Spectrochemical and explainable artificial intelligence approaches for molecular level identification of the status of critically ill patients with COVID-19.

Talanta Jul 31, 2024
This study explores the molecular alterations and disease progression in COVID-19 patients using ATR-FTIR spectroscopy combined with spectrochemical and explainable artificial intelligence (XAI) approaches. Blood serum samples from intubated patients...
Adult Male Middle Aged Severity of Illness Index Glycosylation Humans Critical Illness Spectroscopy, Fourier Transform Infrared Artificial Intelligence Female COVID-19 SARS-CoV-2 Biomarkers Aged Immunoglobulin G
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