Critical care medicine
-
Critical care medicine · Feb 2024
Does Reinforcement Learning Improve Outcomes for Critically Ill Patients? A Systematic Review and Level-of-Readiness Assessment.
Reinforcement learning (RL) is a machine learning technique uniquely effective at sequential decision-making, which makes it potentially relevant to ICU treatment challenges. We set out to systematically review, assess level-of-readiness and meta-analyze the effect of RL on outcomes for critically ill patients. ⋯ In this first systematic review on the application of RL in intensive care medicine we found no studies that demonstrated improved patient outcomes from RL-based technologies. All studies reported that RL-agent policies outperformed clinician policies, but such assessments were all based on retrospective off-policy evaluation.
-
Critical care medicine · Feb 2024
Defining Intensivists: A Retrospective Analysis of the Published Studies in the United States, 2010-2020.
The Society of Critical Care Medicine last published an intensivist definition in 1992. Subsequently, there have been many publications relating to intensivists. Our purpose is to assess how contemporary studies define intensivist physicians. ⋯ There was no consistency of intensivist nomenclature or definitions in contemporary adult intensivist studies in the United States.
-
Critical care medicine · Feb 2024
ReviewThe Roles of Venopulmonary Arterial Extracorporeal Membrane Oxygenation.
Concise definitive review of the use of venopulmonary arterial extracorporeal membrane oxygenation (V-PA ECMO) support in patients with cardiopulmonary failure. ⋯ V-PA ECMO is a promising form of extracorporeal support for patients with right ventricular dysfunction. Future work should focus on identifying the optimal timing and populations for the use of V-PA ECMO.
-
Critical care medicine · Feb 2024
Severe Acute Respiratory Syndrome Coronavirus 2 Pneumonia in Critically Ill Patients: A Cluster Analysis According to Baseline Characteristics, Biological Features, and Chest CT Scan on Admission.
Inconsistent results from COVID-19 studies raise the issue of patient heterogeneity. ⋯ Three clusters with distinct characteristics and outcomes were identified. Such clusters could facilitate the identification of targeted populations for the next trials.
-
Critical care medicine · Feb 2024
Use of Lung Ultrasound in the New Definitions of Acute Respiratory Distress Syndrome Increases the Occurrence Rate of Acute Respiratory Distress Syndrome.
To assess the effect of incorporating bilateral abnormalities as detected by lung ultrasound (LUS) in the Kigali modification and the New Global definition of acute respiratory distress syndrome (ARDS) on the occurrence rate of ARDS. ⋯ The addition of bilateral abnormalities as detected by LUS to the Kigali modification and the New Global definition increases the occurrence rate of the ARDS. The nomenclature for LUS needs to be better defined as LUS patterns differ between patients with and without ARDS. Incorporating well-defined LUS criteria can increase specificity and sensitivity of new ARDS definitions.