Resuscitation
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Brief abstract: In a multicentre network of 28 ICUs in France and Belgium, all comatose patients who fulfilled the 2021 ERC-ESICM criteria for poor outcome after cardiac arrest died or survived with severe neurological disability, even after excluding patients with active WLST to limit self-fulfilling prophecy bias. However, in almost half of the patients, these criteria were not fulfilled, resulting in an indeterminate outcome; in these patients, normal NSE levels and benign EEG predicted neurological recovery, helping reduce prognostic uncertainty. ⋯ Among 337 included patients, the ERC-ESICM algorithm predicted poor neurological outcome in 175 patients, of whom 106 (60%) had withdrawal of life-sustaining treatment (WLST). Among the 69 patients without active WLST, the positive predictive value for an unfavourable outcome was 100% [95-100]%. The specificity of individual predictors ranged from 90% for EEG to 100% for clinical examination and SSEP. Among the remaining 162 patients with indeterminate outcome, a combination of 2 favourable signs predicted good outcome with 99[96-100]% specificity and 23[11-38%]% sensitivity. Conclusion All comatose resuscitated patients not undergoing WLST who fulfilled the ERC-ESICM criteria for poor outcome after CA had poor outcome at three months, even if a self-fulfilling prophecy cannot be completely excluded. In patients with indeterminate outcome (half of the population), favourable signs predicted neurological recovery, reducing prognostic uncertainty.
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To assess the merit of clinical assessment tools in a neurocognitive screening following out-of-hospital cardiac arrest (OHCA). ⋯ gov Identifier: NCT03543371.
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Poor neurological outcome is common following a cardiac arrest. The use of volatile anesthetic agents has been proposed during post-resuscitation to improve outcome. ⋯ In this propensity-matched control study, isoflurane sedation during the post-resuscitation care of ICU patients was associated with a lower incidence of delirium, a shorter duration of mechanical ventilation and a reduced ICU length of stay. Prospective data are needed before its widespread use.
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Out-of-hospital cardiac arrest (OHCA) is a critical condition with low survival rates. In patients with a return of spontaneous circulation, brain injury is a leading cause of death. In this study, we propose an interpretable machine learning approach for predicting neurologic outcome after OHCA, using information available at the time of hospital admission. ⋯ The XGBoost machine learning model with 10 features available at the time of hospital admission showed good performance for predicting neurologic outcome after OHCA, with no apparent signs of overfitting.
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We aimed to estimate the effect of extracorporeal cardiopulmonary resuscitation (ECPR) on neurological outcome and mortality, when compared to conventional cardiopulmonary resuscitation (CCPR), using an individual patient data meta-analysis (IPDMA). ⋯ This IPDMA showed that ECPR was associated with significantly lower rates of unfavorable neurological outcome and mortality in refractory CA. The overall effect could be influenced by CA characteristics and the severity of the initial injury.