Basic Life Support Termination of Resuscitation in the Prehospital Environment for Primary Care Paramedics-A Prospective Observational Study of the Implementation of a Clinical Prediction Rule (TORIT)

1. What is this study?

This is a multi-centre prospective implementation study involving several regional emergency medical services across Ontario

2. What is this study trying to accomplish?

This study aims to document the usefulness of the termination of resuscitation guideline in decreasing the rate of transport of out-of –hospital cardiac arrest patients to the ED.

Secondary aim of this implementation study will be to describe the rates of erroneous application of the guideline.  The comfort of use of the rule among paramedics and base hospital emergency physicians will be described.

3. Who is eligible for this study?

To be included in the study, the following criteria must be met.
Inclusion Criteria:

•    Subjects 18 years and above, both male and female
•    No advanced cardiac life support procedures (ACLS) were available during the call
•    The cardiac arrest is of presumed cardiac cause only

Exclusion Criteria:
•    Age < 18
•    The patient possesses a documented do-not-resuscitate(DNR) order
•    The cardiac arrest is due to non cardiac causes such as trauma, drowning or drug overdose
•    Patient receives any Prehospital ACLS care.

4. Why bother doing this study?

•    In Ontario, fewer than 5% of patients survive Prehospital cardiac arrest.
•    Emergency ambulance transport can be hazardous to motorists, pedestrians and paramedic.
•    A TOR guideline has been dev eloped that is by itself 99.5% accurate in identifying patients who will not survive cardiac arrest.
•    Families are comfortable with TOR in the home and support given by the paramedics.
•    CPR guidelines support the concept of TOR by PCPs.

5. Who is involved?

This study is a collaborative involving at least 8 different EMS systems and base hospital medical directors from all across Ontario.

Grey Bruce Huron
Sault Ste Marie

6.  How will we measure the difference?

Primary outcome
The primary outcome measure, transport rate, will be analyzed by means of two sided, one sample test proportions comparing the transport rate in the implementation cohort to current standard practice (i.e. according to current practice, 100% are transported to the Emergency Department)

Secondary outcomes
Guideline compliance and patient outcomes: Descriptive statistics (frequencies and percentages) will be used to measure the physician application of the rule and track the number of false positive and false negatives. Incorrect application of the Guideline (false positive and false negative) will be tabulated to obtain rates of erroneous application.  Patient outcomes and Cerebral performance Category scores will be tabulated and documented. Any unexpected outcomes will be documented.

Self-reported comfort with application of the Guideline
A two sided one sample test will be used to compare the mean comfort score value to the hypothesized null value of a comfort score of 3(neutral). The sample size required to analyze the primary hypothesis will provide sufficient power for analysis of this secondary hypothesis as a two –sided one-sample t-test would require 12 subjects to provide 80% power to detect a mean comfort score of 2 compared to the null value of 3 and assuming a standard deviation of 1.2 with alpha set at 0.05.

Psychological comfort with the pronouncement of death
The analysis of psychological comfort will be based on the total comfort score computed from the sum of 22 questions on the survey. With each question being scored on a 1 to 5 scale, the total score can therefore range from 22 to 110. the null hypothesis will be that a neutral response(a value of 3 ) is chosen for all questions resulting in a total score of 66, where as the alternate hypothesis will be that there is an overall 1 point per question shift toward greater comfort, thereby resulting in a total comfort score of 88(higher scores representing greater comfort). The total comfort score will be measured for each respondent at two time points; T1 after accrual of 50 patients in each site, and time interval 2, T2, which is two times T1 in each site. A regression model will look at the relationship of the covariates of interest, adjustment to personal loss, gender, age, experience, and number of cardiac arrests personally attended per year, to the dependent measure of individual total comfort score across the 2 time points.

7.  What are the timelines?

The study was started in January 2006. Expected completion – January 2009 or continue to accrue cases until the very last site has obtained 50 patients.