patients for whom the CDR recommended
TOR, five (0.2%) survived to hospital discharge. This compared favorably with both
pre-existing guidelines. Although both of these
pre-existing guidelines resulted in fewer unexpected survivors, this was at the cost of greater
numbers of futile attempts being transported.
This study established clinical variables of
a TOR clinical prediction rule for OHCA
managed by our EMS system, to be used in
conjunction with the existing rule that allows
for termination following asystole after 20
minutes of ALS.
We determined, with a high rate of predictability, that adult patients suffering OHCA of
presumed cardiac origin may be considered for
prehospital TOR when the initial presenting
rhythm was not shockable and where there is
no ROSC before transport. Prospective validation of this rule would be required before
its implementation. JEMS
Matthew House, DHC, MSc, LL.B (hons), is a consultant
paramedic working for North West Ambulance Service NHS
Trust in the United Kingdom. He has 18 years’ experience in
the ambulance service and has previously worked as a tutor
and an emergency care practitioner. He can be reached at
Michael Jackson, MBA, MSc, DipIMC(Ed), FCPara, is the
chief consultant paramedic for North West Ambulance Service
NHS Trust, with responsibility for the clinical leadership and
supervision of over 3,000 EMTs and paramedics. He has over
30 years of experience in EMS and is currently engaged in an
advanced critical care program at Warwick Medical School.
Joanne Dinning, MSc, is a senior lecturer of health
economics at Northumbria University. She’s an experienced
health economist with special interests in economic evaluation of health and social care interventions and priority
setting methods to help underpin commissioning processes.
Peter McMeekin, PhD, is a senior research associate. His
research interests include the economic evaluation of health
care technologies, in particular the use of models based on
routine data to inform decision-making.
1. National service framework for coronary heart Disease: Chapter 8:
Arrhythmias and sudden cardiac death. (March 2005.) UK National
Archives. Retrieved May 24, 2017, from http://webarchive.
2. Cummins R, Ornato J, Thies W, et al. Improving survival from sudden cardiac arrest: the “chain of survival” concept. A statement
for health professionals from the Advanced Cardiac Life Support
Subcommittee and the Emergency Cardiac Care Committee,
American Heart Association. Circulation. 1991;83( 5):1832–1847.
3. Ambulance Service Association. (2006.) National cardiac arrest
4. Kay I. (2015.) Ambulance quality indicators: Clinical outcomes survival to discharge following a cardiac arrest for
ambulance services in England. Retrieved June 21, 2017,
5. Bonnin MJ, Pepe PE, Kimball KT, et al. Distinct criteria for termination of resuscitation in the out-of-hospital setting. JAMA.
6. Cheung M, Morrison L, Verbeek PR. Prehospital vs. emergency
department pronouncement of death: A cost analysis. CJEM.
2001; 3( 1): 19–25.
7. Chan KM, Lui CT, Tsui KL, et al. Comparison of clinical prediction
Figure 3: Application of termination of resuscitation guideline
Specificity 99.00% (95% CI: 97.6% to 99.6%) 99.40% (95% CI: 98.1% to 99.8%) 99.60% (95% CI: 98.4% to 99.9%)
Sensitivity 53.10% (95% CI: 51.6% to 54.6%) 41.20% (95% CI: 39.8% to 42.7%) 11.00% (95% CI: 10.0% to 11.9%)
Positive predictive value 99.80% (95% CI: 99.5% to 99.9%) 99.80% (95% CI: 99.5% to 100%) 99.60% (95% CI: 98.3 to 99.9%)
Negative predictive value 20.30% (95% CI: 18.8% to 22.0%) 16.70% (95% CI: 15.4% to 18.1%) 11.70% (95% CI: 10.8% to 12.7%)
Transport rate 52.40% 63.10% 90.20%
Statistical analysis was performed using
IBM SPSS Statistics 22. Variables included:
presence of witnesses to the arrest (bystander
or ambulance clinician); presenting cardiac rhythm; presence of bystander CPR;
defibrillation at any point; and presence of
any ROSC. Logistic regression was performed using all dependent variables.
The database was examined through a secondary analysis of the TOR CDR, so there
are potential limitations with data integrity
and validity. Several of the receiving hospitals didn’t share data on survival, and a further 104 ( 2.15%) cases didn’t record either
initial cardiac rhythm or ROSC, so were
excluded from the study.
The study also failed to determine
whether paramedics in the field would be
able to apply the rule correctly. The CDR
conforms only to level 4 of the hierarchy of
evidence for decision rules. 29 Therefore, it
would need further evaluation before they
are applied clinically. However, as paramed-
ics within the Trust have been successfully
applying a different TOR decision rule for
over 10 years, and follow CDRs relating
to other conditions, this isn’t considered to
Also, the study was limited to a single
ambulance Trust. Although, as a large trust,
covering both densely urban and sparsely
rural areas, the population isn’t heterogeneous, any results may not be transferable
to other localities and emergency systems.
There’s also the possibility that attitudes
and human factors may have influenced outcomes. If an ambulance clinician believes
that an attempt is futile, they may not perform the resuscitation as aggressively as
they would if they expect a positive outcome. As there was no system in place in
the Trust that could record factors such as
effectiveness of compressions, this couldn’t