Epidemiology and outcomes of out-of-hospital cardiac arrest in Rochester, New York

Article (PDF Available)inResuscitation 72(3):415-24 · April 2007with76 Reads
DOI: 10.1016/j.resuscitation.2006.06.135 · Source: PubMed
To characterize out-of-hospital cardiac arrest (OHCA) and factors that affect survival in a medium sized city that uses system status management for dispatch. A retrospective cohort study of all adult OHCA patients treated by EMS between 1998 and 2001 was conducted using Utstein definitions. The primary endpoint was 1-year survival. Of the 1177 patients who experienced OHCA during the study period, 539 (46%) met inclusion criteria. Age ranged from 18 to 98 years (median 67). The median call-response interval was 5 min (range 0-21), and 93% were 9 min or less. There was no significant difference in the median call-response intervals between call location zip (Post) codes (p=0.07). Twenty percent of experienced ROSC (95% CI 17-23), 7% survived more than 30 days (95% CI 5-9%), and 5% survived to 1 year (95% CI 3-7%). In bivariate analysis, first rhythm and bystander CPR affected survival to 1 year. There was no significant difference in survival between male (4%) and female (7%), black (4%) and white (6%), or witnessed (7%) and unwitnessed arrest (4%). Logistic regression identified younger age, CPR initiated by bystander (19%) or first responder (41%), and presenting rhythm of VF/VT (32%) as factors associated with survival to 1 year. This study finds a 5% survival to 1 year among OHCA patients in Rochester, NY. A presenting rhythm of VF/VT and bystander CPR were associated with increased survival.


Resuscitation (2007) 72, 415—424
Epidemiology and outcomes of out-of-hospital
cardiac arrest in Rochester, New York
Rollin J. Fairbanks
, Manish N. Shah
, E. Brooke Lerner
Kumar Ilangovan
, Elliot C. Pennington
, Sandra M. Schneider
Department of Emergency Medicine, University of Rochester School of Medicine & Dentistry,
Rochester, NY, United States
Department of Community & Preventive Medicine, University of Rochester School of Medicine &
Dentistry, Rochester, NY, United States
Loyola University Chicago Stritch School of Medicine, Maywood, IL, United States
University of Missouri-Columbia School of Medicine, Columbia, MO, United States
Received 2 January 2006; received in revised form 27 June 2006; accepted 27 June 2006
Advanced life support
Cardiac arrest;
Emergency medical
Heart arrest;
Objective: To characterize out-of-hospital cardiac arrest (OHCA) and factors that
affect survival in a medium sized city that uses system status management for
Methods: A retrospective cohort study of all adult OHCA patients treated by EMS
between 1998 and 2001 was conducted using Utstein definitions. The primary end-
point was 1-year survival.
Results: Of the 1177 patients who experienced OHCA during the study period, 539
(46%) met inclusion criteria. Age ranged from 18 to 98 years (median 67). The median
call-response interval was 5 min (range 0—21), and 93% were 9 min or less. There was
no significant difference in the median call-response intervals between call location
zip (Post) codes (p = 0.07). Twenty percent of experienced ROSC (95% CI 17—23), 7%
survived more than 30 days (95% CI 5—9%), and 5% survived to 1 year (95% CI 3—7%). In
bivariate analysis, first rhythm and bystander CPR affected survival to 1 year. There
was no significant difference in survival between male (4%) and female (7%), black
(4%) and white (6%), or witnessed (7%) and unwitnessed arrest (4%). Logistic regres-
sion identified younger age, CPR initiated by bystander (19%) or first responder (41%),
and presenting rhythm of VF/VT (32%) as factors associated with survival to 1 year.
A Spanish translated version of the summary of this article appears as Appendix in the final online version at
Corresponding author at: Department of Emergency Medicine, University of Rochester School of Medicine & Dentistry, 601
Elmwood Avenue, Box 655, Rochester, NY 14642, United States. Tel.: +1 585 273 3849; fax: +1 585 275 2092.
E-mail address: Terry.Fairbanks@Rochester.edu (R.J. Fairbanks).
Present address: The Medical College of Wisconsin, Milwaukee, WI, United States.
0300-9572/$ see front matter © 2006 Elsevier Ireland Ltd. All rights reserved.
416 R.J. Fairbanks et al.
Conclusions: This study finds a 5% survival to 1 year among OHCA patients in Rochester,
NY. A presenting rhythm of VF/VT and bystander CPR were associated with increased
© 2006 Elsevier Ireland Ltd. All rights reserved.
Heart disease is the leading cause of mortality
in the United States,
and death from heart dis-
ease most frequently presents as sudden death
outside of the hospital, or out-of-hospital cardiac
arrest (OHCA).
Many factors have been shown to
influence OHCA survival, including demographic,
clinical, and treatment factors, and attempts
have been made to modify those factors that
are modifiable. One factor shown to influence
survival in multiple studies has been the call-
response interval for emergency medical services
System status management (SSM) is a dynamic
dispatch system commonly used in EMS.
SSM uses
historical data to predict future requests for EMS
responses. EMS dispatchers use this information to
locate ambulances strategically throughout a ser-
vice area. Theoretically, use of this system will
result in approximately equal and more rapid call-
response intervals throughout a service area.
our knowledge, no study has described the epidemi-
ology of OHCA in an EMS system that uses system
status management exclusively.
This study describes the epidemiology and out-
come of patients suffering from OHCA in Rochester,
New York, a medium sized city with an EMS sys-
tem that utilizes SSM. It also evaluates predictors
of OHCA resuscitation and survival.
Materials and methods
Research design
A retrospective cohort study of all adult patients
(18 and older) experiencing OHCA between 1 Jan-
uary 1998 and 31 December 2001 was conducted in
Rochester, New York. The University of Rochester
Research Subjects Review Board approved this
study, and consent was waived. The Utstein recom-
mendations and definitions were followed for data
collection, analysis and reporting to allow compar-
ison of our findings with other systems.
The city of Rochester has a population of 220,000
and spans 36 square miles. The 2000 census
described the city’s residents as 52% female, 48%
white, 38% black, and with a median age of 31.
Twenty-seven percent have not completed high
school, 45% have only a high school degree, and
28% have a college degree. Twenty-three per-
cent of the population lives below the poverty
The City of Rochester is served by a sin-
gle, government-operated, public safety answering
point. The City is also served by a single EMS agency
that staffs each ambulance with two New York
State certified emergency medical technicians, at
least one of which is certified at the advanced EMT
level (paramedic or critical care technician). EMS
responds to approximately 50,000 calls per year in
Residents of Rochester, NY access the public
safety answering point by dialing 911. As soon as
the call-taker identifies that the patient is request-
ing medical assistance, the call-taker uses the
Medical Priority Dispatch System (Priority Dispatch
Salt Lake City, UT) to categorize
the request for assistance and determine which
resources to send to the patient.
City Fire Depart-
ment units are sent to assist on all calls coded as
potentially life-threatening by the dispatch system.
Fire department units are located in traditional
geographically fixed stations throughout the city
and are staffed by personnel who are capable
of performing cardiopulmonary resuscitation (CPR)
and are equipped with automatic external defibril-
Patient information is transmitted electroni-
cally from the 911 center to the EMS agency
dispatchers who initiate a response. The closest
available crew is selected to respond from the
ambulances which are staged dynamically depend-
ing on how many crews are available at the time
the call is received. Time of call, defined as
the time the call-taker receives the initial 911
call, is recorded electronically by the 911 center.
The arrival time, defined as the time the crew
reports to the dispatcher via radio that their vehi-
cle has arrived at the call location, is recorded by
the agency. 911 center and agency dispatch cen-
ter times are synchronized for consistency. These
times are applied consistently and recorded on the
patient care report. The call-response interval was
defined as the interval from time of call to arrival
Epidemiology and outcomes of out-of-hospital cardiac arrest 417
Research methods
Cases were identified using a state-mandated, EMS
agency-maintained list of all OHCA cases. The list
includes the agency run number, patient name, age,
gender, incident date, and incident location.
EMS medical records were obtained and data
were abstracted by a research assistant (KI) using
standardized abstraction forms. Standard chart
review methods were followed to improve accu-
racy and reduce inconsistencies in abstraction.
The first 6 months of cases were also abstracted
independently by a physician investigator (RJF),
and inconsistencies were identified and discussed to
resolution. From this, a codebook and abstraction
rules were created to ensure consistency. During
abstraction of the remaining cases, any ambiguous
records were brought to biweekly research team
meetings and coding rules and definitions were
reviewed. Cases that were unclear were resolved
by group consensus (RJF, MNS, KI).
Patients with no resuscitation attempt (either
dead on arrival or do not attempt resuscitation),
less than 18 years old, arrest witnessed by EMS,
and arrest from non-cardiac etiology were excluded
from the analysis. Non-cardiac etiology cases were
defined as those which, in the reviewer’s judgment,
had a clearly documented traumatic, toxicologi-
cal, or respiratory cause (except CHF). Ambiguous
causes were assumed to be cardiac.
Survival data were obtained using the county
medical examiner records and the Social Security
Death Index database (SSDI).
Medical examiner
and SSDI records were searched at least 1 year after
enrollment of the last patient, and the SSDI was
searched for a second time in 2004, 3—7 years after
the OHCA event date. In addition, hospital medi-
cal records were accessed if missing demographic
data prevented identification of the subject using
the SSDI. Survival was assumed if a patient with
complete identifying data, including name, date of
birth, and social security number, was absent from
the medical examiner database and the SSDI. The
SSDI was searched manually and independently for
all of these cases by four of the investigators (RJF,
MNS, KI, ECP) using different permutations and the
soundex function in order to reduce the chance that
a patient was missed due to errors in the spelling
of names, social security number, or date of birth.
Additional demographic data were obtained
from the 2000 Census by using the patient’s home
address to determine their census block group. The
information obtained for the patients block group
included: (1) median household income, (2) edu-
cational attainment for individuals 25 years of age
and older and (3) percent unemployment within the
civilian workforce. Abstraction, census, and out-
come data were entered into a Microsoft Access
database (Redmond, WA).
Three outcome measures were used: (1) return
of spontaneous circulation (ROSC), defined as tran-
sient or sustained return of pulses and organized
rhythm before reaching the emergency depart-
ment, (2) 30-day survival, and (3) 1 year survival.
Survival to 1 year was the primary end point.
Data analysis
The population of patients experiencing OHCA was
characterized using standard descriptive statistics.
Call-response intervals were analyzed and char-
acterized by median, range, and percent over
preestablished thresholds. This analyses were per-
formed using Microsoft Excel (Redmond, WA) and
Stata 7.0 (College Station, TX).
Survival rate at 1 year was compared by pre-
senting rhythm, call-response interval, and patient
demographics (race, age, and gender). Bivari-
ate analysis was conducted to investigate which
variables were independent predictors of OHCA sur-
vival. During each individual analysis, cases were
excluded if the variable was unknown.
Multivariate analysis was conducted using logis-
tic regression to identify predictors associated with
survival to 1 year. Variables were entered into
the regression model if they demonstrated moder-
ately significant bivariate associations (defined as
p < 0.20) or there was previous literature or clinical
relevance to support its inclusion. Variables identi-
fied a priori for entrance into the regression model
included age, sex, race, witnessed arrest, presence
of bystander CPR, initial rhythm, and call-response
interval of 9 min or less. Cases were excluded from
the regression analysis if any of these variables was
A total of 1177 patients experienced OHCA during
the study period. Five hundred and thirty-nine (46%)
patients met inclusion criteria. Patient age ranged
from 18 to 98 years (median 67). Figure 1 shows
the distribution of OHCA inclusions and exclusions
according to the Utstein template. The demo-
graphic characteristics are reported in Table 1.
Social security number was not available for seven
patients (1%) and there was no known date of death
from other sources (medical examiner or hospital
medical record data) so these seven patients were
excluded prior to all analyses involving outcomes
since there was insufficient information to assume
418 R.J. Fairbanks et al.
Figure 1 Distribution of OHCA types.
survival. However, a sensitivity analysis was per-
formed and showed that there would be no effect
on the results if all these individuals were assumed
to have survived.
Definitive death data were available from the
medical record, medical examiner, or SSDI in all
but 10 patients (2%), and since complete identifi-
cation data were available for these 10 patients,
their absence from these databases was considered
sufficient evidence to assume survival. Overall sur-
vival data are shown in Table 2, and survival by
characteristic for this group is reported in Table 3.
For each of these individual analyses, the small
amount of cases in which the characteristics were
Epidemiology and outcomes of out-of-hospital cardiac arrest 419
Table 1 Demographic characteristics of included cases
95% confidence interval
Age (median, range) 67 (18—98)
Gender (female) 219 (41%) 36—45%
White 274 (51%) 47—55%
Black 190 (35%) 31—39%
Other 28 (5%) 3—7%
Unknown race 47 (9%) 6—11%
Witnessed arrest
Not witnessed 286 (53%) 49—57%
Fire 9 (2%) 1—3%
Bystander 236 (44%) 40—48%
Unknown 8 (1%) 1—3%
CPR started by
EMS 212 (39%) 25—44%
Fire/police 219 (41%) 36—45%
Bystander 105 (19%) 16—23%
Unknown 3 (1%) 0—2%
First defibrillation performed by
EMS 202 (37%) 33—42%
Fire 43 (8%) 6—11%
Bystander 1 (0%) 0—1%
Unknown 3 (1%) 0—2%
Not defibrillated 290 (54%) 49—58%
First rhythm
Asystole 251 (47%) 42—51%
VF/VT 175 (32%) 29—37%
Other 109 (20%) 17—34%
Unknown 4 (1%) 0—2%
Call-response interval
7 min or less 451 (84%) 80—87%
8 min or less 478 (89%) 86—91%
9 min or less 501 (93%) 90—95%
unavailable in the chart were excluded. Whites had
a higher ROSC rate than blacks (23% versus 15%,
p = 0.028), but a lower rate of VF/VT as presenting
rhythm (29% versus 35%, p = 0.038). However, there
was no difference in survival to 1 year between
whites and blacks (6% versus 4%, p = 0.67).
The median call-response interval was 5 min
(range 0—21), and 93% of calls had a call-response
interval of 9 min or less. There was no significant
difference in the median call-response intervals
between call location zip codes (p = 0.07). There
was no difference in median response times
between blacks and whites (both 5 min).
The 2000 census describes the city’s residents
as 52% female, but only 41% of OHCA cases were
female. Thirty-eight of city residents are black, and
35% of OHCA cases were black, and 48% of residents
are white, while 51% of cases were white.
Table 2 Survival data
Survival N Percent CI
ROSC 107 20 95% CI 17—23%
Died within 30 days 495 92 95% CI 89—94%
Alive at 30 days 37 7 95% CI 5—9%
Alive at 1 year 27 5 95% CI 3—7%
Incomplete survival data 7 1 95% CI 1—3%
420 R.J. Fairbanks et al.
Table 3 One-year survival by characteristic
<1-year survival 1-year survival p (
Gender (n = 539)
Male 307 13 (4%)
Female 205 14 (7%)
Race (n = 492)
White 258 16 (6%)
Black 182 8 (4%)
Other 26 2 (8%)
Witnessed arrest (n = 531)
Not witnessed 275 11 (4%)
Fire/police 9 0 (0%)
Bystander 221 15 (7%)
CPR started by (n = 536)
EMS 207 5 (2%)
Fire/police 207 12 (6%)
Bystander 96 9 (9%)
First defibrillation by (n = 536)
EMS 187 15 (8%)
Fire 39 4 (10%)
Bystander 1 0 (0%)
Not defibrillated 282 8 (3%)
First rhythm (n = 535)
Asystole 246 5 (2%)
VF/VT 160 15 (9%)
Other 103 6 (6%)
Age (n = 539)
Age (median) 67 64 Rank sum
p = 0.053 (median
p = 0.447)
Call-response interval (n = 539)
9 min or less 501 25 (5%)
Greater than 9 min 38 2 (5%)
Demographics (n = 539)
Median income 25726 26155 0.68 (rank sum)
% finished HS 29% (mean) 31% (mean) 0.557 (t-test)
% unemployed 5% (mean) 4% (mean) 0.393 (t-test)
Note: Cases were excluded within each analysis if the information for that category could not be obtained.
Statistical significance (p < 0.05).
Logistic regression results are reported in
Table 4. The following variables were significantly
associated with survival to 1 year: younger age, CPR
started prior to EMS arrival, and VF/VT as present-
ing rhythm. The provider of initial defibrillation was
excluded because it correlated strongly with the
patient’s initial cardiac rhythm.
We found an overall 5% survival at 1 year for OHCA
patients in the medium-sized city of Rochester,
NY, with a 9% survival among patients present-
ing with ventricular fibrillation, and a 9% survival
among patients who received bystander CPR. With
the notable exception of data from King County,
Washington, this rate is comparable to or higher
than most American cities with published data (see
Table 5). Assuming that survival to 1 year is com-
parable to survival to discharge, two locations in
the US that have reported a higher survival rate are
Portland, OR (6—10% survival to discharge, mean
call-response interval 3—4 min),
and Tucson, AZ
(8.4% survival to discharge, 93% call-response inter-
val less than 9 min).
Although we were not able
Epidemiology and outcomes of out-of-hospital cardiac arrest 421
Table 4 Logistic regression model of survival to 1 year ( n = 466
Characteristic Odds ratio 95% confidence interval p-Value
Age (by year) 0.96 0.93—0.98 0.001
Gender: female 1.76 0.69—4.49 0.234
White Reference
Black 0.48 0.171—1.34 0.159
Other 1.15 0.22—6.03 0.868
Witnessed arrest
Not witnessed Reference
Bystander 1.22 0.463—3.20 0.691
CPR started by
EMS Reference
Fire/police 3.65 1.10—12.1 0.035
Bystander 4.99 1.49—16.7 0.009
First rhythm
Asystole Reference
VF/VT 6.85 1.91—24.5 0.003
Other 2.9 0.71—11.9 0.14
Call- response interval (CRI)
CRI 9 min or less 1.01 0.19—5.29 0.992
Note: All cases with unknown findings for any variable included in the regression were excluded from the analysis.
Witnessed by fire/police predicted failure/death perfectly therefore was dropped from model.
Statistical significance (p < 0.05).
Table 5 Call-response interval and survival in selected large OHCA studies (n > 300)
Study N Call-response
Survival Outcome
1046 Mean: 9 min 9% Survival to discharge
Chicago, IL
3221 Mean: 5 min (±2) 2% Survival to discharge
Chicago, IL
6451 Mean: 6 min Black:
white: 2.6%
Survival to discharge
703 Median ALS: 6 min n/a Overall survival rate
not reported
Houston, TX
300 Mean: 4.5 min BLS,
9.4 min ALS
2.0% Survival to discharge
388 Mean: 6.3 min 5.4% Survival to discharge
King County, WA
487 (186 ALS) Mean: 8 min (ALS
20.4% Survival to discharge
King County, WA
1029 Mean: 9 min 16% Survival to discharge
King County, WA
Mean: 4.0 min BLS,
10.0 min ALS
16% Survival to discharge
Memphis, TN
1068 Mean: 3.5 min ALS,
5.8 min BLS
6—9% Survival to discharge
1317 81.7%, <9 min 4.9% Survival to discharge
New York
2329 Median: 9.9 min 1.4% Survival to discharge
Toronto (OPALS I)
4690 76.8%, 8 min 3.9% Survival to discharge
Toronto (OPALS II)
1641 92.5%, 8 min 5.2% Survival to discharge
Osaka, Japan
982 Median: 5 min 3.2% 1-Year survival
Portland, OR
322 Mean: 4.6—3.5 min 6—10% Survival to discharge
13822 91%, <15 min 5% Survival to discharge
Seattle, WA
1224 Mean: 3.4 min BLS,
4.6 min ALS
10.2—16.7% Survival to discharge
Tucson, AZ
298 93%, <9 min 8.4% Survival to discharge
422 R.J. Fairbanks et al.
to capture survival to discharge data in our study,
it has been suggested that survival to 1 year under-
represents survival to discharge by 1—2%.
in our system may therefore also be comparable to
these two systems. The identified survival rate is
also comparable to a previously reported 6% OHCA
survival rate in the greater Rochester metropoli-
tan prior to the introduction of SSM. Unfortunately,
a direct comparison of this study with ours is not
possible since the first study used different method-
ology (pre-Utstein) and encompassed a much larger
geographic region.
We are not aware of any other study to date that
reported the epidemiology and outcomes of OHCA
in a system exclusively utilizing the system status
management (SSM) dispatch model. SSM is thought
to create similarities in response times among all
demographic groups since ambulances are redis-
tributed depending on how many are available,
although this principle is theoretical and has not
been definitively shown in the literature.
found a call-response interval of 9 min or less 93%
of the time, and with the exception of two out-
liers (17 and 21 min), the call-response intervals
ranged from 0 to 15 min. Although this appears gen-
erally shorter and more uniform than most other
systems reported in the literature (see Table 5), the
research design did not allow a direct comparison.
Previous studies have shown that shorter ambu-
lance call-response intervals are independently
associated with OHCA survival.
Many authors
report only the mean call-response interval, a
statistic that may be misleading if there is signif-
icant skewing of the data.
More recently, some
authors have reported call-response intervals in
terms of percentage over a threshold. For exam-
ple, one study reported that ALS arrived in less than
9 min 81% of the time.
The superiority of the per-
centile method over the mean is best illustrated
by comparing the OPALS phase I and phase II data.
In this Canadian series, the largest OHCA study
to date, the mean call-response interval improved
only slightly between phase I and phase II, from
6.7 to 6.5 min. However, when the proportion of
cases with a call-response interval of 8 min or less
was considered, they found a dramatic improve-
ment. During phase 1 the call-response interval was
8 min or less 76.7% of the time, but jumped to
92.5% during phase 2.
Of note, this improvement
in response time corresponded with a statistically
significant increase in OHCA survival, from 3.9%
to 5.2%. Our SSM-based system demonstrates rel-
atively short call-response intervals using either
measure: the mean and median of 5 min and 93rd
percentile of 9 min or less are both shorter than
most reported in the literature (see Table 5). Our
study revealed no significant difference in survival
rates in the group with slower response intervals
(5% survival) compared to that with faster response
intervals (5%). Although this is inconsistent with
some previous studies, it may be because we had
relatively low numbers in the long call-response
interval (>9 min), with only 38 cases, two of which
Disparity among income-levels in cardiovascular
disease has been shown to be a great burden in the
US, particularly for non-Hispanic blacks.
demographics of cardiac arrest victims in this study
were not different from city demographics, except
for females who had a lower incidence of OHCA
but statistically similar survival rate compared to
males. Blacks and whites had proportionally simi-
lar incidence and no difference in survival rates.
In this study race is not a significant predictor of
survival. The impact that race and socioeconomic
factors have on OHCA survival has been controver-
sial in the literature. Becker et al. demonstrated a
strong association between survival and race even
though the mean call-response intervals between
blacks and whites were the same (6 min), though a
secondary analysis showed a significantly different
distribution (shorter for whites), which suggested
that response time may have affected survival.
One possible explanation that has been offered for
differences in survival between races is a disparity
in response times. In this study the call-response
intervals between blacks and whites, and between
zip codes were not found to be different and there
was no difference in survival by race.
There are limitations to our study that are impor-
tant to discuss. First, this was a retrospective
chart review. Despite the use of well-established
standards for chart review, we were dependent
upon the accurate and complete documentation
of patient care. Because of the study design, we
used EMS provider interpretations for most clinical
data, such as rhythm strips and presenting rhythm
information. Additionally, information was some-
times omitted from the patient care report and
not all demographic information was reported by
subject or their proxy. In some cases it may have
been estimated by the provider. For instance, race
information was unavailable in 47 cases, and, when
available, was determined by the EMS providers or
emergency department registration clerks, not by
the patients themselves.
Second, we were unable to compare our findings
to a non-SSM control group. Thus, we are not able
to draw definitive conclusions regarding the affect
Epidemiology and outcomes of out-of-hospital cardiac arrest 423
of SSM on OHCA survival; we are able to report the
epidemiology and survival in a system that utilizes
SSM and contrast it to non-SSM systems reported in
the literature.
Third, although there is strong precedent in the
medical literature, the use of the SSDI for out-
comes data is not perfect. However, we believe
that we greatly increased our accuracy by using
medical examiner and hospital medical record data
when patient demographic data were missing and
when the patients were not found within the SSDI
This study reveals a 5% overall survival to 1 year
among OHCA patients in Rochester, NY, with a 9%
survival among patients with a presenting rhythm
of VF/VT or who received bystander CPR. In this
system which utilized system status management
there was no difference in survival based on race,
gender, or socioeconomic status of patients, or in
patients defibrillated by fire department person-
nel, witnessed collapse, or call-response intervals
greater than 9 min.
Conflict of interest
The authors report no real or perceived conflicts of
The authors wish to recognize the following indi-
viduals and organizations for their contribution
to this project: Jennifer Williams, James Wood,
Marlene Terrana, Mike Kuder, Robert Zerby, Robin
Dick, Rural/Metro Medical Services-Rochester, the
Monroe County Medical Examiners Office, Highland
Hospital, and Rochester General Hospital.
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    • "The MPbased approach achieved a coverage of 77.6% for incidents where response was given below the 9-minutes threshold. This is less than the 93% coverage reported in an earlier study [36] that had a system operating under the SSM strategy. The coverage proportion at 8 minutes threshold is also less than in other studies considering static deployments [37]. "
    [Show abstract] [Hide abstract] ABSTRACT: Dynamically reassigning ambulance deployment locations throughout a day in order to balance ambulance availability and demands can be effective in reducing response times. The objectives of this study were to model dynamic ambulance allocation plans in Singapore based on the System Status Management (SSM) strategy and to evaluate the dynamic deployment plans using a Discrete Event Simulation (DES) model.Methods The Geographical Information System (GIS)-based analysis and Mathematical Programming (MP) were used to develop the dynamic ambulance deployment plans for SSM based on ambulance calls data from 1st January 2011 to 30th June 2011. A DES model that incorporated these plans was used to compare the performance of the dynamic SSM strategy against static reallocation policies under various demands and travel time uncertainties.ResultsWhen the deployment plans based on the SSM strategy were followed strictly, the DES model showed that the GIS-based plans resulted in approximately 13 seconds reduction in the median response times compared to the static reallocation policy, whereas the MP-based plans resulted in approximately a 44 seconds reduction. The response times and coverage performances were still better than the static policy when reallocations happened for only 60% of all the recommended moves.Conclusions Dynamically reassigning ambulance deployment locations based on the SSM strategy can result in superior response times and coverage performance compared to static reallocation policies even when the dynamic plans were not followed strictly.
    Full-text · Article · Nov 2014
    • "Despite decades of efforts to promote cardiopulmonary resuscitation (CPR) education and the introduction of automated external defibrillators , less than 50% of cardiac arrest (CA) victims achieve a return of spontaneous circulation (ROSC) and this percentage drops to 20% or less for those patients that live in rural areas or do not have an initial rhythm that can be defibrillated (e.g., pulseless electrical activity, PEA, and asystole)234. Even fewer of these patients are alive on hospital admission and most of them will eventually die because of extended post-anoxic brain injury5678. In 2002, two randomized clinical trials demonstrated the benefit of therapeutic hypothermia (TH) on neurologically intact survival in patients who were cooled inhospital for 12 to 24 hours to 32-34°C within few hours from ROSC following an out-of-hospital cardiac arrest (OHCA) with ventricular fibrillation (VF) or ventricular tachycardia (VT) as first rhythm [9,10]. "
    [Show abstract] [Hide abstract] ABSTRACT: Therapeutic hypothermia (TH, 32-34[degree sign]C) has been shown to improve neurological outcome in comatose survivors of out-of-hospital cardiac arrest (OHCA) with ventricular tachycardia or fibrillation. Earlier initiation of TH may increase the beneficial effects. Experimental studies have suggested that starting TH during cardiopulmonary resuscitation (CPR) may further enhance its neuroprotective effects. The aim of this study was to evaluate whether intra-arrest TH (IATH), initiated in the field with trans nasal evaporative cooling (TNEC), would provide outcome benefits when compared to standard of care in patients being resuscitated from OHCA.Methods/design: We describe the methodology of a multi-centre, randomized, controlled trial comparing IATH delivered through TNEC device (Rhinochill, Benechill Inc., San Diego, CA, USA) during CPR to standard treatment, including TH initiated after hospital admission. The primary outcome is neurological intact survival defined as cerebral performance category 1--2 at 90 days among those patients who are admitted to the hospital. Secondary outcomes include survival at 90 days, proportion of patients achieving a return to spontaneous circulation (ROSC), the proportion of patients admitted alive to the hospital and the proportion of patients achieving target temperature (<34[degree sign]C) within the first 4 hours since CA. This ongoing trial will assess the impact of IATH with TNEC, which may be able to rapidly induce brain cooling and have fewer side effects than other methods, such as cold fluid infusion. If this intervention is found to improve neurological outcome, its early use in the pre-hospital setting will be considered as an early neuro-protective strategy in OHCA.Trial registration: NCT01400373.
    Full-text · Article · Nov 2013
    • "Male patients were less likely to survive then females in both univariate and multivariate analysis. This is in contrast to previous studies which did not show difference in outcome with respect to gender.[13,15161718 ICU patients have a poor outcome compared to non ICU patient. "
    [Show abstract] [Hide abstract] ABSTRACT: The aim of this study was to demonstrate that APACHE II scores can be used as a predictor of the cardio-pulmonary resuscitation (CPR) outcome in hospitalized patients. A retrospective chart review of patients admitted, from 2002 to 2007, at the Aga Khan University Hospital, Karachi, was done for this study. Information was collected on 738 patients, constituting all adults admitted in general ward, ICU, CICU and SCU during this time, and who had under-went cardiac arrest and received cardiopulmonary resuscitation during their stay at the hospital. Patient characteristics, intra-arrest variables such as event-witnessed, initial cardiac rhythm, pre arrest need for intubation and vasoactive drugs, duration of CPR and survival details were extracted from patient records. The APACHE II score was calculated for each patient and a descriptive analysis was done for demographic and clinical features. The primary outcome of successful CPR was categorized as survival >24 h after CPR versus survival <24 h after CPR. Multivariable logistic regression was used to assess the association between the explanatory variables and successful CPR. Patients with APACHE II scores less than 20 had 4.6 times higher odds of survival compared to patients with a score of >35 (AOR: 4.6, 95% CI: 2.4-9.0). Also, shorter duration of CPR (AOR: 2.9, 95% CI: 1.9-4.4), evening shift (AOR: 2.1, 95% CI: 1.3-3.5) and Male patients (AOR: 0.6, 95% CI: (0.4-0.9) compared to females were other significant predictors of CPR outcome. APACHE II score, along with other patient characteristics, should be considered in clinical decisions related to CPR administration.
    Full-text · Article · Mar 2012
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