Resuscitation
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Observational Study
Neurologic outcome in comatose patients resuscitated from out-of-hospital cardiac arrest with prolonged downtime and treated with therapeutic hypothermia.
Previous reports have shown that prolonged duration of resuscitation efforts in out-of-hospital cardiac arrest (OHCA) is associated with poor neurologic outcome. This concept has recently been questioned with advancements in post-cardiac arrest care including the use of therapeutic hypothermia (TH). The aim of this study was to determine the rate of good neurologic outcome based on the duration of resuscitation efforts in OHCA patients treated with TH. ⋯ Although longer downtime is associated with worse outcome in OHCA patients, we found that comatose patients who have been successfully resuscitated and treated with TH have neurologically intact survival rates of 23% even with downtime >20min.
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Multicenter Study
Development and validation of risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team.
The National Cardiac Arrest Audit (NCAA) is the UK national clinical audit for in-hospital cardiac arrest. To make fair comparisons among health care providers, clinical indicators require case mix adjustment using a validated risk model. The aim of this study was to develop and validate risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team in UK hospitals. ⋯ Validated risk models for ROSC>20min and hospital survival following in-hospital cardiac arrest have been developed. These models will strengthen comparative reporting in NCAA and support local quality improvement.
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Current focus on immediate survival from out-of-hospital cardiac arrest (OHCA) has diverted attention away from the variables potentially affecting long-term survival. ⋯ One-third of the patients discharged from hospital after OHCA died within 30 months of the event. Long-term survival was associated both with better neurological and functional level at hospital discharge and a smaller decrease in functional limitation from before to after the arrest, yet some patients with a poor neurological outcome survived prolonged periods after hospital discharge.
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Early warning scores (EWS) are designed to identify early clinical deterioration by combining physiologic and/or laboratory measures to generate a quantified score. Current EWS leverage only a small fraction of Electronic Health Record (EHR) content. The planned widespread implementation of EHRs brings the promise of abundant data resources for prediction purposes. The three specific aims of our research are: (1) to develop an EHR-based automated algorithm to predict the need for Pediatric Intensive Care Unit (PICU) transfer in the first 24h of admission; (2) to evaluate the performance of the new algorithm on a held-out test data set; and (3) to compare the effectiveness of the new algorithm's with those of two published Pediatric Early Warning Scores (PEWS). ⋯ The novel algorithm achieved higher sensitivity, specificity, and AUC than the two PEWS reported in the literature.
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To develop and implement a first responder training programme, assess the feasibility of training lay persons with low literacy in rural Bangladesh and determine the acceptability of the programme in the community. ⋯ Developing a first responder training programme that includes CPR in a rural Bangladesh community is feasible if participants have secondary school attainment. Adolescents and young adults are suitable candidates. Evaluation is ongoing to see whether the programme graduates were able to reduce morbidity and mortality through effective first response efforts.