Resuscitation
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Cardiac arrest (CA) is the third leading cause of death, with persistently low survival rates despite medical advancements. This article evaluates the potential of emerging technologies to enhance CA management over the next decade, using predictions from the AI tools ChatGPT-4 and Gemini Advanced. ⋯ Integrating advanced monitoring technologies and AI-driven tools offers hope in improving CA management. A balanced approach involving rigorous scientific validation and ethical oversight is necessary. Collaboration among technologists, medical professionals, ethicists, and policymakers is crucial to use these innovations ethically to reduce CA incidence and enhance outcomes. Further research is needed to enhance the reliability of AI predictive capabilities.
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Multicenter Study Observational Study
Regional Brain Net Water Uptake in Computed Tomography after Cardiac Arrest - A Novel Biomarker for Neuroprognostication.
Selective water uptake by neurons and glial cells and subsequent brain tissue oedema are key pathophysiological processes of hypoxic-ischemic encephalopathy (HIE) after cardiac arrest (CA). Although brain computed tomography (CT) is widely used to assess the severity of HIE, changes of brain radiodensity over time have not been investigated. These could be used to quantify regional brain net water uptake (NWU), a potential prognostic biomarker. ⋯ This pilot study indicates that NWU derived from serial head CTs is a promising novel biomarker for outcome prediction after CA. NWU >8% in basal ganglia grey matter regions predicted poor outcome while absence of NWU indicated good outcome. NWU and follow-up CTs should be investigated in larger, prospective trials with standardized CT acquisition protocols.
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CT perfusion is a valuable tool for evaluating cerebrovascular diseases, but its role in patients with hypoxic ischaemic encephalopathy is unclear. This study aimed to investigate 1) the patterns of cerebral perfusion changes that may occur early on after successful resuscitation, and 2) their correlation with clinical outcome to explore their value for predicting outcome. ⋯ This pilot study identified various perfusion patterns in patients after resuscitation, indicative of circulatory changes associated with post-cardiac-arrest brain injury. After validation, certain patterns could potentially be used in conjunction with other prognostic markers for stratifying patients and adjusting personalized treatment following cardiopulmonary resuscitation. Normal brain perfusion within 12 h after resuscitation is predictive of favourable outcome with high specificity.
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Extracorporeal cardiopulmonary resuscitation (ECPR) can improve survival for refractory out-of-hospital cardiac arrest (OHCA). We sought to assess the feasibility of a proposed ECPR programme in Scotland, considering both in-hospital and pre-hospital implementation scenarios. ⋯ An ECPR programme for OHCA in Scotland could provide access to ECPR to a modest number of eligible OHCA patients, with pre-hospital ECPR implementation scenarios yielding higher access to ECPR and higher numbers of additional survivors.
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In patients undergoing cardiopulmonary resuscitation (CPR) after an Out-of-Hospital Cardiac Arrest (OHCA), intrathoracic airway closure can impede ventilation, adversely affecting patient outcomes. This explorative study investigates the evolution of intrathoracic airway closure by analyzing the lower inflection point (LIP) during the inspiration phase of CPR, aiming to identify the potential thresholds for alveolar recruitment. ⋯ These explorative data demonstrate a predominantly negative trajectory in LIP evolution during CPR, suggesting potential challenges in maintaining airway patency. Limitations include a small sample size and sensor recording issues. Further research is warranted to explore the evolution of LIP and its implications for personalized ventilation strategies in CPR.