Articles: intensive-care-units.
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Journal of anesthesia · Apr 2024
ReviewMachine learning in the prediction and detection of new-onset atrial fibrillation in ICU: a systematic review.
Atrial fibrillation (AF) stands as the predominant arrhythmia observed in ICU patients. Nevertheless, the absence of a swift and precise method for prediction and detection poses a challenge. This study aims to provide a comprehensive literature review on the application of machine learning (ML) algorithms for predicting and detecting new-onset atrial fibrillation (NOAF) in ICU-treated patients. ⋯ Notably, CatBoost exhibited superior performance in NOAF prediction, while the support vector machine excelled in NOAF detection. Machine learning algorithms emerge as promising tools for predicting and detecting NOAF in ICU patients. The incorporation of these algorithms in clinical practice has the potential to enhance decision-making and the overall management of NOAF in ICU settings.
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Critical care clinics · Oct 2023
ReviewImplementing Artificial Intelligence: Assessing the Cost and Benefits of Algorithmic Decision-Making in Critical Care.
This article provides an overview of the most useful artificial intelligence algorithms developed in critical care, followed by a comprehensive outline of the benefits and limitations. We begin by describing how nurses and physicians might be aided by these new technologies. We then move to the possible changes in clinical guidelines with personalized medicine that will allow tailored therapies and probably will increase the quality of the care provided to patients. Finally, we describe how artificial intelligence models can unleash researchers' minds by proposing new strategies, by increasing the quality of clinical practice, and by questioning current knowledge and understanding.
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Mayo Clinic proceedings · May 2024
Shock Severity Classification and Mortality in Adults With Cardiac, Medical, Surgical, and Neurological Critical Illness.
To evaluate whether the Society for Cardiovascular Angiography and Interventions (SCAI) Shock Classification could perform risk stratification in a mixed cohort of intensive care unit (ICU) patients, similar to its validation in patients with acute cardiac disease. ⋯ The SCAI Shock Classification provided incremental mortality risk stratification beyond established prognostic markers across the spectrum of medical and surgical critical illness, proving utility outside its original intent.
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Acta Anaesthesiol Scand · Mar 2024
Multicenter Study Observational StudyValidation of PRE-DELIRIC and E-PRE-DELIRIC in a Danish population of intensive care unit patients-A prospective observational multicenter study.
Delirium is a clinical condition characterized by an acute change in brain function and is frequently observed in critically ill patients. The condition has been associated with negative outcomes, making it crucial to identify patients who are at risk. Two recent prediction models have been developed to estimate the risk of delirium in intensive care unit (ICU) patients; the prediction model for delirium (PRE-DELIRIC) and the early prediction model for delirium (E-PRE-DELIRIC). We aimed to perform an external validation of these models in a Danish cohort of critically ill patients. ⋯ In a Danish cohort, we found that the PRE-DELIRIC model demonstrated acceptable performance and E-PRE-DELIRIC demonstrated poor performance. In critically ill adult patients PRE-DELIRIC may be useful in identifying patients at high risk of delirium.
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Over the past decade, significant advancements in pharmacological, endoscopic, and radiographic treatments have emerged in the management of patients with cirrhosis and esophagogastric varices or variceal hemorrhage. These advances have been in several areas, including the role of screening and primary prophylaxis (preventing an initial variceal bleed), evaluation and management of acute esophagogastric variceal hemorrhage, and in preventing variceal rebleeding. Therefore, we believe there is a need for an updated, evidence-based "narrative review" on this important clinical topic that will be relevant for internists, hospitalists, intensive care unit physicians, and those in training. We believe the guidance presented in this narrative review will enhance daily medical practice of health care professionals and has the potential to improve quality of care for these complex patients.