Resuscitation
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Observational Study
Association between haemodynamics during cardiopulmonary resuscitation and patient outcomes.
There is no defined target for blood flow during chest compressions (CC). We previously reported various haemodynamic patterns in which dominant arterial and venous pressures were observed during CC. This study aimed to evaluate arterial and venous perfusion pressures during CC and determine their association with patient outcomes. ⋯ ROSC did not occur in patients with negative average ΔMean A-V values. ROSC may be achieved through individualised resuscitation that places a greater emphasis on differences between mean arterial and venous pressure, rather than through uniform resuscitation.
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To examine the associations between ETCO2, ROSC, and chest compression quality markers in paediatric patients during active resuscitation. ⋯ This represents the largest collection of ETCO2 and chest compression data in paediatric patients to date and unadjusted analyses suggests an association between ETCO2 and ROSC in some paediatric patients.
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Accurate and timely prognostication of patients with out-of-hospital cardiac arrest (OHCA) who achieved the return of spontaneous circulation (ROSC) is crucial in clinical decision-making, resource allocation, and communications with next-of-kins. We aimed to develop the Survival After ROSC in Cardiac Arrest (SARICA), a practical clinical decision tool to predict survival in OHCA patients who attained ROSC. ⋯ We developed and internally validated the SARICA score to accurately predict survival of OHCA patients with ROSC at the time of admission. SARICA is clinically practical and developed using an interpretable machine-learning framework. SARICA has unknown generalizability pending external validation studies.
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Outcomes of cardiac arrest (CA) remain dismal despite therapeutic advances. Literature is limited regarding outcomes of CA in emergency departments (ED). ⋯ Survival remains dismal among CA patients especially those occurring in the ED. Given that there are considerable variations in the etiology between the two studied cohorts, more research is required to improve the understanding of these factors, which may improve survival outcomes.
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Mathematical optimization of automated external defibrillator (AED) placement has demonstrated potential to improve survival of out-of-hospital cardiac arrest (OHCA). Existing models mostly aim to improve accessibility based on coverage radius and do not account for detailed impact of delayed defibrillation on survival. We aimed to predict OHCA survival based on time to defibrillation and developed an AED placement model to directly maximize the expected survival rate. ⋯ We developed a novel AED placement model based on the impact of time to defibrillation on OHCA outcomes. Mathematical optimization can improve OHCA survival.