Resuscitation
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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.
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Accurate prediction of complications often informs shared decision-making. Derived over 10 years ago to enhance prediction of intra/post-operative myocardial infarction and cardiac arrest (MI/CA), the Gupta score has been criticized for unreliable calibration and inclusion of a wide spectrum of unrelated operations. In the present study, we developed a novel machine learning (ML) model to estimate perioperative risk of MI/CA and compared it to the Gupta score. ⋯ The present ML model outperformed the Gupta score in the prognostication of MI/CA across a heterogenous range of operations. Given the growing integration of ML into healthcare, such models may be readily incorporated into clinical practice and guide benchmarking efforts.
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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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Frailty is associated with increased 30-day mortality and non-home discharge following perioperative cardiac arrest. We estimated the predictive accuracy of frailty when added to baseline risk prediction models. ⋯ Incorporating frailty did not significantly improve predictive accuracy of models for 30-day mortality and non-home discharge following perioperative resuscitation. Thus, demonstrated associations between frailty and outcomes of perioperative resuscitation may not translate into improved predictive accuracy. When engaging patients in shared decision-making regarding do-not-resuscitate orders perioperatively, providers should acknowledge uncertainty in anticipating resuscitation outcomes.