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A/Prof Marcus Ong Eng Hock
Consultant, Director of Research and Senior Medical Scientist
Dept of Emergency Medicine, Singapore General Hospital
Adjunct Assoc Professor, Office of Research
Duke-NUS Graduate Medical School, Singapore
Prehospital Emergency Care is still developing and much
needed in Asia
Chain of survival concept provides a framework for
describing PEC systems in Asia
Using Utstein methodology, allows for a descriptive
comparison of PEC systems and performance in different
Out of Hospital Cardiac Arrest
(OHCA) is a global health concern.
Eg, 16, 000 deaths occur in Singapore
◦ 23% from a cardiac cause,
◦ 30-40% will occur suddenly, outside
of a hospital.
Mechanism of death is usually a fatal
arrhythmia, most often ventricular
tachycardia or fibrillation.
Early initiation of treatment has an
important effect on outcomes and
The Cardiac Arrest and Resuscitation Epidemiology (CARE)
study, is a multi-agency, national wide collaboration to study
OHCA in Singapore.
Serve as a model for a Pan-Asian Resuscitation Outcomes
Give valuable information regarding OHCA in Asian
countries, and also help an understanding of the variations
and different Emergency Medical Systems (EMS) in Asia.
Establishment of a Pan-Asian Resuscitation Outcomes
Study will be important to track trends and the
effectiveness of subsequent interventions related to our
Opportunity to conduct
interventional trials across
Can be extended to look at
major trauma, myocardial
infarction, stroke, respiratory
To establish a Pan-Asian
Resuscitation Outcomes Study
that will track out-of-hospital
1. Describing regional variations in the incidence and outcomes of OHCA
across Asia and beyond
2. Describing the true population based incidence of OHCA across different
countries, using standardized common denominators as agreed across the
3. Comparing Emergency Medical Services (EMS) outcomes (including
response times and treatment outcomes) for OHCA across regions,
allowing for international benchmarking and study of best practices
4. Understanding the etiology and preventable risk factors for OHCA and
predictors of survival. The large sample size and international nature of the
study will allow analysis of the influence of racial, population age structure,
chronic disease burden, socio-economic factors, EMS characteristics,
bystander cardio-pulmonary resuscitation (CPR), EMS response times,
prehospital defibrillation and treatment, seasonal, geographic and climatic
factors on OHCA incidence and outcomes.
5. Understanding geospatial and temporal occurrence of OHCA across
regions that will facilitate systems level strategies for Public Access
Defibrillation, community education and CPR training.
6. Study differences in the occurrence of OHCA between North American and
Asia-Pacific populations, specifically with regards to the role of primary
ventricular arrhythmias in sudden cardiac arrest.
Establish a Pan Asian network of EMS
physicians that will collect and link data
and outcomes from OHCA in their
respective cities and countries.
Include EMS data from dispatch services,
ambulance records and service
Data regarding cardiac arrest outcomes
will be collected from all major hospitals.
Data will be collected from:
◦ ‘995’ dispatch records
◦ Ambulance patient case notes
◦ Emergency Department (ED)
◦ In-hospital records
Completed data will collected and sent to the
Pan-Asian Resuscitation Outcomes Study Co-
ordination Center for data management using
Electronic Data Capture (EDC).
Web based data collection software that enables
researchers for single sites or multi-site clinical
trials to "create" a study online.
Customizing CRFs for the study, enrolling patients
and collecting data, and extracting data.
Give access to team members all over the world for
data collection (Ethics approval must be attained for
your study before data collection can begin).
In collaboration with CDC Atlanta/Emory USA
A Pan-Asian Resuscitation Outcomes Study
will be an important foundation to implement
and track planned improvements to EMS in
It will aid in planning for deployment of
resources, interventions and ongoing efforts
to improve Asian EMS.
PAROS: List of Participating Countries
Principal Investigator Country Sites Population base
Sang Do Shin Korea 6 20 million
Marcus Ong Singapore 6 4 million
Matthew Huei-Ming Ma Taiwan 2 10 million
William, Wing-Keung Woo Hong 5 10 million
Hideharu Tanaka Japan 2 20 million
Pairoj Khruekarnchana Thailand 2 10 million
Nik H Rahman Malaysia 2 5 million
Paul Middleton Australia 3 10 million
Ridvan Atilla Turkey 3 8 million
Ang Swee Hui Brunei 1 400,000
To compute the sample size, we looked at each potential risk factor and
identified the one which would require the largest sample size to assess.
OPALS study from Canada reported the probability of exposure (community size
<30,000) among controls (non-survivors) was 0.0536.
To detect an odds ratio for disease in exposed subjects relative to unexposed
subjects of 1.4, we will need to study 13,447 OHCA patients to be able to reject
the null hypothesis (using an uncorrected chi-squared statistic) that the odds
ratio equals to 1, with type I error of 0.05 and power of 90%.
Singapore 1,000 cases. Other PAROS sites: Korea 4,000, Taiwan 1,500, Hong Kong
1,500, Japan 3,000, Thailand 1,000, Turkey 1,600, Brunei 400.
no. is 13,447
Descriptive statistics (frequencies, means and standard deviation,
medians, and quartiles) will be obtained for the socio-demographic and
other independent variables as appropriate.
For independent variables with >2 categories, dummy variables will be
created. The categories of variables having sparse data will be grouped
together in biologically meaningful ways.
The category with minimum level of potential risk (hazard) of survival
will be taken as the reference group for each risk (prognostic) factor.
Univariate analysis will be carried out and relative risk (RR) and
corresponding 95% CI will be computed to estimate the association
between the dependent variable (survival status) and each factor.
Independent variables associated with survival status at 0.25 significance
level in the univariate analysis or those with biological importance will be
further analyzed through multivariate logistic regression
The overall significance of the independent variables in the model will be
assessed by the Likelihood ratio test.
Confounding variables will be assessed by ≥10% change in the estimated
coefficient for the particular variable.
After developing the main effect model, to uncover any multicollinearity,
the association among independent variables will be assessed by using the
appropriate test, and plausible interactions between the independent
variables will also be assessed.
The Pearson’s Chi-square test will be applied to check for the goodness-of-
fit of the final model.
Appendix 1: Timeline for establishing proposed OHCA EDC
Task Milestone Due Date
1 Create taxonomy and data dictionary End Sep 2009
2 Design CRF End Nov 2009
3 Set up operation committee and publication committee End Jan 2010
4 Set up EDC and co-ordination meeting for members Mid Mar 2010
5 Mid Mar 2010
-Survey of members
6 EDC training for member countries Mid Jun 10
7 Launch EDC for OHCA study
Manuscript completed for PAROS survey and submitted for
8 End 2010
Data collection completed for PAROS OHCA study and
9 June 2011
preparation for publication