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1.
Resusc Plus ; 18: 100615, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38549697

ABSTRACT

A growing number out-of-hospital cardiac arrest (OHCA) registries have been developed across the globe. A few of these are national, while others cover larger geographical regions. These registries have common objectives; continuous quality improvement, epidemiological research and providing infrastructure for clinical trials. OHCA registries make performance comparison across Emergency Medical Services systems possible for benchmarking, hypothesis generation and further research. Changes in OHCA incidence and outcomes provide insights about the effects of secular trends or health services interventions. These registries, therefore, have become a mainstay of OHCA management and research. However, developing and maintaining these registries is challenging. Coordination of different service providers to support data collection, sustainable resourcing, data quality and data security are the key challenges faced by these registries. Despite all these challenges, noteworthy progress has been made and further standardization and co-ordination across registries can result in great international benefit. In this paper we present a 'why' and 'how to' model for setting up OHCA registries, and suggestions for better international co-ordination through a Global OHCA Registries Collaborative (GOHCAR). We draw together the knowledge of a cohort of international researchers, with experience and expertise in OHCA registry development, management, and data synthesis.

2.
Resuscitation ; 170: 213-221, 2022 01.
Article in English | MEDLINE | ID: mdl-34883217

ABSTRACT

AIM: 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. METHODS: We stratified OHCAs occurring in Singapore (2010-2017) based on time to defibrillation and developed a regression model to predict the Utstein survival rate. We then developed a novel AED placement model, the maximum expected survival rate (MESR) model. We compared the performance of MESR with a maximum coverage model developed for Canada that was shown to be generalizable to other settings (Denmark). The survival gain of MESR was assessed through 10-fold cross-validation for placement of 20 to 1000 new AEDs in Singapore. Statistical analysis was performed using χ2 and McNemar's tests. RESULTS: During the study period, 15,345 OHCAs occurred. The power-law approximation with R2 of 91.33% performed best among investigated models. It predicted a survival of 54.9% with defibrillation within the first two minutes after collapse that was reduced by more than 60% without defibrillation within the first 4 minutes. MESR outperformed the maximum coverage model with P-value < 0.05 (<0.0001 in 22 of 30 experiments). CONCLUSION: We developed a novel AED placement model based on the impact of time to defibrillation on OHCA outcomes. Mathematical optimization can improve OHCA survival.


Subject(s)
Cardiopulmonary Resuscitation , Emergency Medical Services , Out-of-Hospital Cardiac Arrest , Defibrillators , Humans , Out-of-Hospital Cardiac Arrest/therapy , Retrospective Studies , Survival Rate
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