AIMC Topic: Shock, Cardiogenic
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Renal Dysfunction Across the Spectrum of Cardiogenic Shock: Mechanisms, Clinical Implications, and Therapeutic Strategies.
Current heart failure reports
Jun 25, 2025
PURPOSE OF REVIEW: This review aims to elucidate the complex interplay between cardiogenic shock (CS) and renal function, detailing the mechanisms of kidney injury, identifying risk factors, and providing a framework for the diagnosis and management ...
Comparison of machine learning and nomogram to predict 30-day in-hospital mortality in patients with acute myocardial infarction combined with cardiogenic shock: a retrospective study based on the eICU-CRD and MIMIC-IV databases.
BMC cardiovascular disorders
Mar 19, 2025
BACKGROUND: To evaluate the predictive utility of machine learning and nomogram in predicting in-hospital mortality in patients with acute myocardial infarction complicated by cardiogenic shock (AMI-CS), and to visualize the model results in order to...
Machine learning prediction of in-hospital mortality and external validation in patients with cardiogenic shock: the RESCUE score.
Revista espanola de cardiologia (English ed.)
Jan 22, 2025
INTRODUCTION AND OBJECTIVES: Despite advances in mechanical circulatory support, mortality rates in cardiogenic shock (CS) remain high. A reliable risk stratification system could serve as a valuable guide in the clinical management of patients with ...
Cardiogenic Shock Update: New Trials, Evolving Management Paradigms, and Artificial Intelligence.
Journal of cardiothoracic and vascular anesthesia
Jun 12, 2024
Identification of distinct clinical phenotypes of cardiogenic shock using machine learning consensus clustering approach.
BMC cardiovascular disorders
Aug 29, 2023
BACKGROUND: Cardiogenic shock (CS) is a complex state with many underlying causes and associated outcomes. It is still difficult to differentiate between various CS phenotypes. We investigated if the CS phenotypes with distinctive clinical profiles a...
Lactate levels as a prognostic predict in cardiogenic shock under venoarterial extracorporeal membrane oxygenation support.
Revista espanola de cardiologia (English ed.)
Nov 19, 2021
INTRODUCTION AND OBJECTIVES: Lactate and its evolution are associated with the prognosis of patients in shock, although there is little evidence in those assisted with an extracorporeal venoarterial oxygenation membrane (VA-ECMO). Our objective was t...
Predicting Survival After Extracorporeal Membrane Oxygenation by Using Machine Learning.
The Annals of thoracic surgery
May 23, 2020
BACKGROUND: Venoarterial (VA) extracorporeal membrane oxygenation (ECMO) undoubtedly saves many lives, but it is associated with a high degree of patient morbidity, mortality, and resource use. This study aimed to develop a machine learning algorithm...
Predicting Hemodynamic Shock from Thermal Images using Machine Learning.
Scientific reports
Jan 14, 2019
Proactive detection of hemodynamic shock can prevent organ failure and save lives. Thermal imaging is a non-invasive, non-contact modality to capture body surface temperature with the potential to reveal underlying perfusion disturbance in shock. In ...
Temporary circulatory support for cardiogenic shock.
Current opinion in critical care
Aug 1, 2025
PURPOSE OF REVIEW: Temporary circulatory support (TCS) devices play a crucial role in stabilizing patients with refractory cardiogenic shock. They provide essential hemodynamic support and serve as a bridge to recovery, decision-making, heart transpl...
Comparison of different AI systems for diagnosing sepsis, septic shock, and cardiogenic shock: a retrospective study.
Scientific reports
May 6, 2025
Sepsis, septic shock, and cardiogenic shock are life-threatening conditions associated with high mortality rates, but differentiating them is complex because they share certain symptoms. Using the Medical Information Mart for Intensive Care (MIMIC)-I...
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