Critical care medicine
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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.
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Critical care medicine · Jan 2024
Multicenter StudyThe Predictive Validity of the Berlin Definition of Acute Respiratory Distress Syndrome for Patients With COVID-19-Related Respiratory Failure Treated With High-Flow Nasal Oxygen: A Multicenter, Prospective Cohort Study.
The Berlin definition of acute respiratory distress syndrome (ARDS) was constructed for patients receiving invasive mechanical ventilation (IMV) with consideration given to issues related to reliability, feasibility, and validity. Notwithstanding, patients with acute respiratory failure (ARF) may be treated with high-flow nasal oxygen (HFNO) and may not fall within the scope of the original definition. We aimed to evaluate the predictive validity of the Berlin definition in HFNO-treated patients with COVID-19-related respiratory failure who otherwise met ARDS criteria. ⋯ The predictive validity of the Berlin ARDS definition was similar for HFNO-treated patients as compared with the original population of invasively ventilated patients. Our findings support the extension of the Berlin definition to HFNO-treated patients with ARDS.
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Critical care medicine · May 2024
Observational StudySodium and Its Impact on Outcome After Aneurysmal Subarachnoid Hemorrhage in Patients With and Without Delayed Cerebral Ischemia.
To perform a detailed examination of sodium levels, hyponatremia and sodium fluctuations, and their association with delayed cerebral ischemia (DCI) and poor outcome after aneurysmal subarachnoid hemorrhage (aSAH). ⋯ Sodium levels, hyponatremia, and sodium fluctuations were not associated with the occurrence of DCI. However, higher sodium levels, hypernatremia, and greater sodium fluctuations were associated with poor outcome after aSAH irrespective of the presence of DCI. Therefore, sodium levels, even with mild changes in levels, warrant close attention.
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Critical care medicine · Apr 2024
Observational StudyModification in ICU Design May Affect Delirium and Circadian Melatonin: A Proof of Concept Pilot Study.
Nonpharmacologic delirium management is recommended by current guidelines, but studies on the impact of ICU design are still limited. The study's primary purpose was to determine if a multicomponent change in room design prevents ICU delirium. Second, the influence of lighting conditions on serum melatonin was assessed. ⋯ Modifications in ICU room design may influence the incidence and severity of delirium. Dedicated light therapy could potentially influence delirium outcomes by modulating circadian melatonin levels.
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Critical care medicine · May 2024
Development and External Validation of Models to Predict Persistent Hypoxemic Respiratory Failure for Clinical Trial Enrichment.
Improving the efficiency of clinical trials in acute hypoxemic respiratory failure (HRF) depends on enrichment strategies that minimize enrollment of patients who quickly resolve with existing care and focus on patients at high risk for persistent HRF. We aimed to develop parsimonious models predicting risk of persistent HRF using routine data from ICU admission and select research immune biomarkers. ⋯ Parsimonious, interpretable models that predict persistent HRF may improve enrichment of trials testing HRF-targeted therapies and warrant future validation.