Derivation of a Clinical Decision Rule for the Discontinuation of
In-Hospital Cardiac Arrest Resuscitations
Author Information
<http://archinte.ama-assn.org/issues/v159n2/rfull/#aainfo> Carl van
Walraven, MD, FRCPC, MSc; Alan J. Forster, MD, FRCPC; Ian G. Stiell, MD,
MSc, FRCPC
Background Most patients undergoing in-hospital cardiac resuscitation will
not survive to hospital discharge.
Objective To derive a decision rule permitting the discontinuation of
futile resuscitation attempts by identifying patients with no chance of
surviving to hospital discharge.
Patients and Methods Patient, arrest, and outcome data for 1077 adult
patients undergoing in-hospital cardiac resuscitation was retrieved from 2
randomized clinical trials involving 5 teaching hospitals at 2 university
centers. Recursive partitioning was used to identify a decision rule using
variables significantly associated with death in hospital.
Results One hundred three patients (9.6%) survived to hospital discharge.
Death in hospital was significantly more likely if patients were older than
75 years (P<.001), the arrest was unwitnessed (P = .003), the resuscitation
lasted longer than 10 minutes (P<.001), and the initial cardiac rhythm was
not ventricular tachycardia or fibrillation (P<.001). All patients died if
there was no pulse 10 minutes after the start of cardiopulmonary
resuscitation, the initial cardiac rhythm was not ventricular tachycardia or
fibrillation, and the arrest was not witnessed. As a resuscitation rule,
these parameters identified all patients who survived to hospital discharge
(sensitivity, 100%; 95% confidence interval, 97.1%-100%). Resuscitation
could have been discontinued for 119 (12.1%) of 974 patients who did not
survive, thereby avoiding 47 days of postresuscitative care.
Conclusions A practical and highly sensitive decision rule has been derived
that identifies patients with no chance of surviving in-hospital cardiac
arrest. Prospective validation of the rule is necessary before it can be
used clinically.
Arch Intern Med. 1999;159:129-134
IOI80173
CARDIOPULMONARY resuscitation (CPR) and advanced cardiac life support are
used to resuscitate patients suffering cardiac arrest. With the exception of
airway management and cardiac defibrillation, the effectiveness of
interventions provided during resuscitation is uncertain. 1
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r1> Physicians and other
health care personnel often expend prolonged amounts of time and effort in
attempting to resuscitate patients. Resuscitated patients may be subjected
to prolonged, intensive, and invasive therapy. Throughout this time, the
patient's family and members of the health care team often deal with
difficult emotions and decisions.
Several clinical factors have been associated with poor outcome following
in-hospital cardiac arrest. Death has been shown to be independently
associated with several prearrest clinical factors including hypotension, 2
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r2> renal failure, 3-5
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r3> pneumonia, 2
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r2> poor functional
status, 2 <http://archinte.ama-assn.org/issues/v159n2/rfull/#r2> , 6
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r6> and metastatic
cancer. 2 <http://archinte.ama-assn.org/issues/v159n2/rfull/#r2> , 5
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r5> Several factors
identifiable during the arrest independently predict mortality including
prolonged duration of resuscitation 2
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r2> , 6
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r6> , 7
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r7> and initial cardiac
rhythms other than ventricular tachycardia or fibrillation. 6
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r6> , 8
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r8> , 9
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r9> Postarrest factors
such as high Acute Physiology and Chronic Health Evaluation II or low
Glasgow Coma Scale scores are associated with death after initially
successful resuscitation. 10
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r10> However, most of
these studies were conducted within a single center, contained small numbers
of arrests, or used data from unblinded and retrospective medical record
review. Therefore, it is not surprising that some of the studies have
conflicting results.
Several studies 8 <http://archinte.ama-assn.org/issues/v159n2/rfull/#r8> ,
10-12 <http://archinte.ama-assn.org/issues/v159n2/rfull/#r10> have combined
various prearrest, arrest, and postarrest factors into clinical decision
rules for predicting survival following cardiac arrest. However, because the
probability of survival from in-hospital cardiac arrest in most studies is
less than 20%, a decision rule will not change management unless it can
confidently predict the likelihood of survival to be nil. None of the
published rules 8 <http://archinte.ama-assn.org/issues/v159n2/rfull/#r8> ,
10-12 <http://archinte.ama-assn.org/issues/v159n2/rfull/#r10> have this
level of accuracy. The rules can be impractical for common use because they
require large amounts of clinical data, 10
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r10> , 11
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r11> complex
mathematical calculations, 9
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r9> or involve clinical
information not available to the resuscitation team.
In this study, we used prospectively collected data for patients entered
into 1 of 2 randomized controlled trials to derive a clinical decision rule
for in-hospital cardiac arrest. Specifically, we wanted to determine if
readily available patient and arrest characteristics could be combined
during the resuscitation to identify which patients had no chance of being
discharged from hospital. This rule would therefore allow the treating team
to discontinue futile resuscitation efforts.
PATIENTS AND METHODS
Patients were eligible for this study if they suffered in-hospital cardiac
arrest and were enrolled in 1 of 2 randomized controlled trials. These
negative trials determined that neither high-dose epinephrine 13
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r13> nor active
compression-decompression cardiopulmonary resuscitation (CPR) 14
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r14> increased
resuscitation from cardiac arrest. To be included in these studies, patients
had to undergo CPR in the hospital. Consequently, patients whose
resuscitation required defibrillation only were not included. Patients
resuscitated in the emergency department had a spontaneous pulse when
presenting to the department and subsequently underwent an arrest while in
the department. Patients were excluded if they were younger than 16 years;
had a terminal illness; had been without CPR for more than 15 minutes after
their collapse; had acute trauma or exsanguination; were in the operating,
recovery, or delivery rooms at the time of the arrest; had a recent
sternotomy; or were judged (as determined by a blinded chart review) to have
received inappropriate CPR (eg, a respiratory arrest with detectable pulse).
These studies took place at 5 university-associated, tertiary care teaching
hospitals in Ottawa and London, Ontario, between 1989 and 1995.
During the resuscitations, nurses, respiratory therapists, orderlies, and
physicians administered CPR. These hospital staff members were fully trained
in standard CPR and required regular testing. Advanced cardiac life support
was directed by staff physicians or senior medical residents using standard
protocols published by the American Heart Association. 15
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r15> During the
epinephrine trial, 13
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r13> patients were
randomized to receive either high (7-mg) or standard (1-mg) dosages of
epinephrine. During the active compression-decompression–CPR trial, 14
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r14> patients were
randomized to receive either standard CPR or a device for active chest
compression-decompression. Otherwise, resuscitation efforts were identical
in the 2 studies. Neither study showed a significant difference between
treatment and control groups.
Following each cardiac arrest, the resuscitation team completed data
collection forms. Physicians documented the suspected cause of the arrest as
well as the cardiac rhythm noted at the start of advanced cardiac life
support. Resuscitation nurses recorded all other factors. The arrest was
considered "unwitnessed" if the patient lost spontaneous circulation in the
absence of another person. The duration of the arrest was defined as the
time from the start of CPR to either return of spontaneous circulation or
cessation of resuscitative efforts. A study nurse abstracted current and
past medical conditions of each patient from the medical record. All
resuscitated patients were followed up until death or discharge from
hospital. Prior to discharge, the neurologic status of all patients were
evaluated with the Modified Mini-Mental State Examination 16
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r16> and a 5-point scale
of cerebral performance. 17
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r17>
Data from both studies were combined and all clinical variables were
assessed for association with discharge from hospital using the chi2 test
(for nominal data) or the unpaired separate-variance Student t test (for
continuous data). Age and resuscitation duration was dichotomized at
clinically reasonable cutoff points and analyzed as nominal variables.
Variables that were significantly associated with survival-to-discharge
(P<.05, 2-tailed) were analyzed by a chi2 recursive-partitioning technique
using a P value threshold of .05 for each split. 18
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r18> , 19
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r19> Our goal was to
generate a decision rule that would accurately identify patients with any
chance of being discharged from hospital. For the decision rule, we chose
the statistical model that offered a sensitivity of 1.0 (ie, no patients
discharged from the hospital were predicted by the decision rule to die in
hospital). Since several models meeting this standard were derived, that
with the highest possible specificity was chosen as the final decision rule.
The performance of the derived decision rule for identifying patients with
no chance of discharge from hospital was assessed by calculating
sensitivity, specificity, and negative and positive predictive values with
95% confidence intervals (CIs). 20
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r20> A receiver
operating characteristics curve was not calculated since the prediction rule
is binary. To determine what effect the decision rule could have if used
clinically, the outcome of patients identified by the decision rule as
having no chance of discharge was determined. All analyses were performed
using SPSS for Windows, Version 7.0 (SPSS Inc, Chicago, Ill) and
KnowledgeSEEKER for Windows 3.1 (Angoss Software, Toronto, Ontario).
RESULTS
During the clinical trials, 1472 patients were treated for in-hospital
cardiac arrest. However, 376 of them were excluded from analysis because of
exclusion criteria for the randomized trials. Nineteen (1.3%) were excluded
because of incomplete data.
For derivation of the prediction rule, 1077 patients were eligible ( Table 1
<http://archinte.ama-assn.org/issues/v159n2/fig_tab/ioi80173_t1.html> ).
Patients were more commonly men and had a mean age of 68 years, with 35%
being older than 75 years. Cardiovascular disease was more common than
respiratory disease as a current diagnosis, a pattern also seen for chronic
diagnoses. Most arrests were witnessed and occurred on the hospital ward.
For witnessed cases in which the time of collapse could be determined, delay
to CPR and advanced cardiac life support was short. In 31.4% of arrests, the
initial cardiac rhythm was either ventricular tachycardia or fibrillation,
with the remainder of the patients having asystole or pulseless electrical
activity. Most arrests had a cardiac cause; 9.6% of the patients survived to
discharge. Survivors had good cognitive function with a median Modified
Mini-Mental State Examination score only slightly lower than normal.
Patients from the 2 trials were similar for most characteristics.
The association of patient and resuscitation variables with
survival-to-discharge is shown in Table 2
<http://archinte.ama-assn.org/issues/v159n2/fig_tab/ioi80173_t2.html> .
Although mean age was not associated with survival, patients older than 75
years were significantly less likely to survive. Neither sex nor any of the
current or past diagnoses were associated with survival. Cardiac arrests of
survivors were more likely to be witnessed, to have either ventricular
tachycardia or fibrillation as the initially recorded rhythm, and were
shorter in duration. Groups did not differ with respect to treatment delays,
or location and cause of arrest.
Using the variables significantly associated with survival-to-discharge,
recursive partitioning identified 3 resuscitation factors that predicted no
chance of survival ( Figure 1
<http://archinte.ama-assn.org/issues/v159n2/fig_tab/ioi80173_f1.html> ). All
patients died if there was no pulse 10 minutes after the start of CPR, the
initial cardiac rhythm was not ventricular tachycardia or fibrillation, and
the arrest was not witnessed. These factors were combined into the
resuscitation rule, whereby continued resuscitation is unnecessary if all
the following are true: (1) no pulse 10 minutes after the start of CPR; (2)
initial cardiac rhythm is not ventricular tachycardia or fibrillation; and
(3) the arrest was not witnessed. In our study population, this decision
rule predicted 119 patients (11.0%) to die in hospital and correctly
identified all patients who were discharged from hospital (sensitivity,
100%; 95% CI, 97.1%-100%) ( Table 3
<http://archinte.ama-assn.org/issues/v159n2/fig_tab/ioi80173_t3.html> ). The
low specificity (12.2%; 95% CI, 10.3%-14.4%) and positive predictive value
(10.8%; 95% CI, 8.9%-12.8%) are the trade-offs for the high sensitivity.
Of the 119 patients identified by the decision rule to die in hospital, 99
(83.1%) could not be resuscitated with resuscitations lasting a mean of 25.6
minutes (range, 10-60 minutes). The remaining 20 patients survived a total
of 1147 hours (mean, 57.4 hours; range, 1-240 hours), or 47.9 days in the
intensive care unit. Details of the 7 patients identified by the rule to not
survive who lived longer than 24 hours following the arrest are summarized
in Table 4
<http://archinte.ama-assn.org/issues/v159n2/fig_tab/ioi80173_t4.html> . All
but 2 patients had multisystem disease prior to the arrest. Three of the
patients (patients 3, 4, and 6) experienced new problems in hospital prior
to the arrest and all except patient 4 experienced an arrest within the
first week of hospitalization. Following the arrest, patients 1 through 4
had anoxic encephalopathy severe enough to preclude meaningful interaction
with their environment; discussion with families resulted in life support
being withdrawn. The remaining patients were able to participate in
decisions regarding their treatment and all decided to not undergo further
resuscitation in the event of cardiac arrest. Each patient died within 24
hours of extubation and only 1 (patient 6) was transferred out of the
intensive care unit prior to death.
COMMENT
To our knowledge, this study represents the largest collection of
prospectively gathered data for in-hospital cardiac arrests. With commonly
available factors, our resuscitation rule identified all patients having any
chance of being discharged from hospital following resuscitation. For
patients identified by the rule as having no chance of survival,
resuscitative efforts were often prolonged. At least 16.8% of patients
predicted by the rule to die were treated in hospital for often extensive
amounts of time following the arrest. If this decision rule is validated
with prospectively collected data, it should be easy to use and avoid futile
resuscitative efforts.
Decision rules can improve clinical decision making, 21
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r21> decrease
unnecessary investigations, 22
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r22> and decrease the
cost of health care delivery. 23
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r23> This study meets
most methodological standards for the development of clinical decision
rules. 24 <http://archinte.ama-assn.org/issues/v159n2/rfull/#r24> , 25
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r25> The outcome
predicted by the rule was clearly defined and clearly important. Since many
characteristics of both the patients and study sites were described, the
generalizability of the rule can be determined. The mathematical techniques
used for the derivation of the rule were delineated and valid. Estimates for
ramifications of the rule's application were given. The rule is clinically
sensible since other studies have associated death after resuscitation with
each variable in the rule including prolonged resuscitative efforts, 2
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r2> , 6
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r6> , 7
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r7> , 26
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r26> initial rhythms
other than ventricular tachycardia or fibrillation, 6-9
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r6> , 27
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r27> , 28
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r28> and unwitnessed
arrest. 7 <http://archinte.ama-assn.org/issues/v159n2/rfull/#r7> Finally,
the rule is easy to use, and suggests a course of action.
This study has several limitations. First, the rule has not been
prospectively validated. The performance characteristics of the rule could
change when applied to a different group of patients. Second, we did not
determine the reliability of the variables included in the rule. Most
likely, interobserver agreement for whether the arrest was witnessed is
high. However, agreement may be lower for classification of the initial
cardiac rhythm. Unreliable variables will decrease a rule's reproducibility.
Prior to prospective validation, definitions for these and other parameters
need to be developed and their interobserver agreement needs to be
determined. Third, current and past diagnoses were grouped into relatively
large categories (eg, respiratory disease), therefore making it impossible
to determine the effect that particular diagnoses (eg, pneumonia) had on
resuscitation outcome.
Fourth, the rule included factors concerning patient status at the start of
the arrest and used them to predict prognosis 10 minutes later if
resuscitation was unsuccessful. Therefore, the rule does not consider any
factors arising within the first 10 minutes of the arrest. During this time,
prognostically important cardiac rhythms and responses to therapy could
occur. Also, the rule does not include recently described prognostic factors
such as end-tidal carbon dioxide levels. Several studies 29
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r29> , 30
<http://archinte.ama-assn.org/issues/v159n2/rfull/#r30> have suggested this
to be a powerful predictor of survival from cardiac arrest. Future studies
need to determine if these and other data can be added to the present
prediction rule to improve its performance.
Finally, it is uncertain how effective this rule could be, even if
validated. Situations could arise where a physician decides that the rule
should not apply to a particular patient because of what are considered to
be special, individual circumstances. This is valid since clinical judgment
must always be used when applying any clinical decision rule. Further
research is needed to determine how frequently this would occur with a
particular rule. Also, the rule identified only 12% of all people dying
after in-hospital cardiac arrest. Most of these patients were not
successfully resuscitated. Using the decision rule to predict patient death
minutes prior to it actually happening is not terribly useful. However, we
believe the rule would help physicians with limited experience in cardiac
resuscitation decide when continued resuscitation is futile.
Despite these uncertainties, we believe that this decision rule, if
validated, has the potential to be helpful. It will decrease the amount of
time and effort that staff expend on futile cardiac resuscitations. While
the rule will not protect families from difficult emotions associated with a
loved one's sudden death, stressful days of watching and waiting could be
avoided. Finally, the costs saved by using the rule to avoid prolonged stays
in the intensive care unit could be used to improve other areas of the
health care system. However, these potential benefits can only be realized
if the rule is validated in a prospective, multicenter study.
In summary, we have derived a simple and accurate decision rule that
identifies all patients with a chance of surviving in-hospital cardiac
arrest. The rule is explicit, easy to apply, uses objective data that are
readily available at all cardiac arrests, and could significantly decrease
the amount of futile postresuscitation care. If validated, the rule could be
combined with astute clinical judgment to more effectively use cardiac
resuscitation.
Author/Article Information
From the Department of Medicine (Drs van Walraven and Forster) and the
Division of Emergency Medicine (Dr Stiell), University of Ottawa, Ottawa,
Ontario.
Corresponding author: Carl van Walraven, MD, FRCPC, MSc, F-6, Ottawa Civic
Hospital, 1053 Carling Ave, Ottawa, Ontario, Canada K1Y 4E9.
Accepted for publication May 28, 1998.
Dr van Walraven was an R. Samuel McLaughlin Foundation research fellow at
the Institute for Clinical Evaluative Sciences, Toronto, Ontario, when this
study was completed. Dr Stiell is a scientist of the Medical Research
Council of Canada.
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Validation of a Clinical Decision Aid to Discontinue In-Hospital Cardiac
Arrest Resuscitations
Author Information <http://jama.ama-assn.org/issues/v285n12/rfull/#aainfo>
Carl van Walraven, MD, FRCPC, MSc; Alan J. Forster, MD, FRCPC, MSc; David C.
Parish, MD, MPH; Francis C. Dane, PhD; K. M. Dinesh Chandra, MD; Marcus D.
Durham, MA; Candace Whaley, BBA; Ian Stiell, MD, FRCPC, MSc
Context Most patients undergoing in-hospital cardiac resuscitation do not
survive to hospital discharge. In a previous study, we developed a clinical
decision aid for identifying all patients undergoing resuscitation who
survived to hospital discharge.
Objective To validate our previously derived clinical decision aid.
Design, Setting, and Participants Data from a large registry of in-hospital
resuscitations at a community teaching hospital in Georgia were analyzed to
determine whether patients would be predicted to survive to hospital
discharge (ie, whether their arrest was witnessed or their initial cardiac
rhythm was either ventricular tachycardia or ventricular fibrillation or
they regained a pulse during the first 10 minutes of chest compressions).
Data from 2181 in-hospital cardiac resuscitation attempts in 1987-1996
involving 1884 pulseless patients were analyzed.
Main Outcome Measure Comparison of predictions based on the decision aid
with whether patients were actually discharged alive from the hospital.
Results For 327 resuscitations (15.0%), the patient survived to hospital
discharge. For 324 of these resuscitations, the patients were predicted to
survive to hospital discharge (sensitivity = 99.1%, 95% confidence interval,
97.1%-99.8%). In 269 resuscitations, patients did not satisfy the decision
aid and were predicted to have no chance of being discharged from the
hospital. Only 3 of these patients (1.1%) were discharged from the hospital
(negative predictive value = 98.9%), none of whom were able to live
independently following discharge from the hospital.
Conclusion This decision aid can be used to help physicians identify
patients who are extremely unlikely to benefit from continued resuscitative
efforts.
JAMA. 2001;285:1602-1606
JOC02206
Cardiopulmonary resuscitation and advanced cardiac life support
interventions are used to resuscitate patients having cardiac or respiratory
arrest. Physicians and other health care workers follow algorithmic advanced
cardiac life support guidelines from the American Heart Association 1
<http://jama.ama-assn.org/issues/v285n12/rfull/#r1> in an attempt to
restore a spontaneous circulation in these patients. Despite these
guidelines, decision making during resuscitation is difficult because
cardiac arrest is a complex common pathway of a diverse collection of
diseases. 2 <http://jama.ama-assn.org/issues/v285n12/rfull/#r2>
The decision to stop resuscitative efforts can be particularly difficult for
physicians. In these situations, decision making must balance a "respect for
human dignity" and clinical judgment. 3
<http://jama.ama-assn.org/issues/v285n12/rfull/#r3> Prognostic factors that
portend a poor outcome following arrest may help the latter. Death following
resuscitation has been associated with both prearrest factors (including
hypotension, 4 <http://jama.ama-assn.org/issues/v285n12/rfull/#r4> renal
failure, 5 <http://jama.ama-assn.org/issues/v285n12/rfull/#r5> , 6
<http://jama.ama-assn.org/issues/v285n12/rfull/#r6> pneumonia, 4
<http://jama.ama-assn.org/issues/v285n12/rfull/#r4> low functional status,
4 <http://jama.ama-assn.org/issues/v285n12/rfull/#r4> , 7
<http://jama.ama-assn.org/issues/v285n12/rfull/#r7> and metastatic cancer 4
<http://jama.ama-assn.org/issues/v285n12/rfull/#r4> , 6
<http://jama.ama-assn.org/issues/v285n12/rfull/#r6> ) and intra-arrest
factors (including prolonged duration of resuscitation 4
<http://jama.ama-assn.org/issues/v285n12/rfull/#r4> , 7
<http://jama.ama-assn.org/issues/v285n12/rfull/#r7> , 8
<http://jama.ama-assn.org/issues/v285n12/rfull/#r8> and initial cardiac
rhythms other than pulseless ventricular tachycardia or ventricular
fibrillation 7 <http://jama.ama-assn.org/issues/v285n12/rfull/#r7> , 9-11
<http://jama.ama-assn.org/issues/v285n12/rfull/#r9> ). However, decision
aids that use these and other factors to determine a patient's prognosis
following resuscitation are complicated and difficult to use at the bedside.
They have operated poorly when validated in distinct populations 12
<http://jama.ama-assn.org/issues/v285n12/rfull/#r12> and have been unable
to definitively identify patients with no hope of survival. 13
<http://jama.ama-assn.org/issues/v285n12/rfull/#r13> A simple decision aid
that reliably identifies patients whoregardless of the cause of their
arresthave a poor outcome would be helpful. This could help avoid the
"tendency to try prolonged, excessive resuscitative efforts." 3
<http://jama.ama-assn.org/issues/v285n12/rfull/#r3>
For this reason, we previously derived a simple clinical decision aid to
identify all patients who were eventually discharged from hospital after
their arrest. 14 <http://jama.ama-assn.org/issues/v285n12/rfull/#r14> Our
goal, when deriving this decision aid, was to maximize sensitivity for
identifying these patients. We studied 1077 adults undergoing in-hospital
resuscitation who participated in 2 randomized clinical trials 15
<http://jama.ama-assn.org/issues/v285n12/rfull/#r15> , 16
<http://jama.ama-assn.org/issues/v285n12/rfull/#r16> involving 5 teaching
hospitals. Using recursive partitioning, we found that all resuscitated
patients who were eventually discharged from the hospital had a witnessed
arrest, an initial cardiac rhythm of either ventricular tachycardia or
ventricular fibrillation, or a pulse within the first 10 minutes of chest
compressions. We proposed that physicians might safely withdraw
resuscitative efforts on patients who did not satisfy the decision aid since
none of these patients were discharged from the hospital.
In that report we stressed 2 issues. First, we emphasized that while 100% of
the patients not satisfying the decision aid eventually died in hospital,
the 95% confidence interval (CI) of this point estimate extended down to
97.1%. Second, we cautioned that validation of the decision aid in a
separate patient population was required before the decision aid should be
used clinically. 14 <http://jama.ama-assn.org/issues/v285n12/rfull/#r14>
This was the objective of our current study.
METHODS
This validation study was a secondary analysis of a resuscitation registry
at the Medical Center of Central Georgia (MCCG) in Macon. The MCCG is a
550-bed community teaching hospital affiliated with the Mercer University
School of Medicine. It is the major hospital for the metropolitan area as
well as the tertiary center for the surrounding rural areas and has
approximately 25 000 admissions per year.
Multidisciplinary teams consisting of nurses, residents, staff physicians,
respiratory therapists, and pharmacists conducted the resuscitations. Staff
physicians or senior medical residents directed the resuscitations using
standard protocols published by the American Heart Association. 3
<http://jama.ama-assn.org/issues/v285n12/rfull/#r3> Team members were all
trained in basic life support and most were trained in advanced cardiac life
support. All members underwent regular updates. During the study period,
resuscitation was attempted for approximately 1.5% of admissions.
With the exception of arrests occurring in the neonatal intensive care unit
or operating room, all in-hospital arrests occurring between 1987 and 1996
were entered into the registry. The resuscitation registry was reviewed and
approved by the Institutional Review Board of Mercer University School of
Medicine and MCCG. Resuscitation was defined, as has been suggested by the
Utstein Conference, 17 <http://jama.ama-assn.org/issues/v285n12/rfull/#r17>
as "any effort to reverse a clinical death in progress." Code sheets were
completed after each resuscitation attempt and were used to identify events.
To ensure complete capture of resuscitations, the records of patients
without a code sheet but whose hospital charges included cardioversion,
defibrillation, or the administration of epinephrine were also reviewed to
determine if a resuscitation attempt occurred. Data were entered into the
registry by MCCG project staff and were checked prior to analysis. All data
were cross-checked for accuracy through an extensive review of hospital
records and death logs. Clinical categories, such as whether or not the
arrest was witnessed and initial cardiac rhythm, used standardized
definitions that had interrater kappavalues exceeding 0.9 before final
classification of the data set was complete. Questionable cases were
reviewed by 2 researchers (D.C.P., K.M.D.C.) for consensus definition in the
final review. This was done before this study was conceived. A detailed desc
ription of the registry was previously published. 11
<http://jama.ama-assn.org/issues/v285n12/rfull/#r11>
All resuscitations in the registry were eligible for this study.
Resuscitations were excluded if they were performed on patients younger than
16 years old or were performed on patients in the operating room at the time
of the arrest. Our decision aid applies to patients who were pulseless at
the start of the resuscitation. Therefore, resuscitations were excluded if
the initial rhythm was any other than pulseless ventricular tachycardia,
ventricular fibrillation, pulseless electrical activity, or asystole.
Resuscitations were also excluded if patients received no chest
compressions, if information required by the decision aid was missing, or if
time to initial chest compressions exceeded 15 minutes. Each of these
exclusion criteria was used for patient selection in the decision aid
derivation. 14 <http://jama.ama-assn.org/issues/v285n12/rfull/#r14>
To apply the decision aid, we determined the time from the start of chest
compressions to the end of the resuscitation. This was the return of any
spontaneous circulation lasting 2 or more minutes or the end of
resuscitative efforts. The former criterion addressed a concern of our
decision aid, 2 <http://jama.ama-assn.org/issues/v285n12/rfull/#r2> namely,
that patients who regained a pulse for most of the resuscitation only to
lose it before the 10-minute mark might have resuscitation stopped if the
aid was applied. Patients who were directly seen to lose spontaneous
circulation were classified as "witnessed." Also, all patients who had an
arrest while on a cardiac monitor, in the intensive or coronary care unit or
in the cardiac catheterization laboratory, were classified as "witnessed
arrests." This was regardless of whether or not the patient was directly
visualized to lose spontaneous circulation. Patients in the emergency
department were included in the study only if they actually had an arrest
after they arrived in the department. Finally, we applied the decision aid
in this study in a more clinically intuitive order than that presented in
the derivation study. This altered order does not affect the model's
statistical significance or operating characteristics.
A 2 2 contingency table comparing actual discharge status to that predicted
by the decision aid was used to calculate the classification performance of
the clinical decision aid with 95% CIs. We reviewed the medical record of
all patients who did not satisfy the decision aid but survived more than 24
hours to determine their course in hospital. Analyses are by resuscitation.
RESULTS
When this study was conducted, the registry recorded 3960 resuscitations. We
excluded 1779 events for the following reasons: no chest compressions were
given during the resuscitation (n = 1147), the patient was not pulseless at
the start of the resuscitation (n = 254), the patient was younger than 16
years (n = 85), the patient was in the operating room when the arrest was
called (n = 1), the time from arrest being called to the first chest
compression exceeded 15 minutes (n = 9), or information required to apply
the decision aid was missing (n = 283).
This left 2181 attempted resuscitations comprising 1884 patients. These
patients had a mean age of 65 years (95% CI, 64.3-65.7) and 47.3% were
female. Most arrests occurred off ward, had a cardiorespiratory cause, and
were witnessed ( Table 1
<http://jama.ama-assn.org/issues/v285n12/fig_tab/joc02206_t1.html> ). The
predominant initial rhythms were asystole and pulseless electrical activity,
and for 2094 (96.0%) resuscitations, chest compressions were delivered
within 5 minutes of arrest. A spontaneous circulation was attained in almost
half of resuscitations, and for 15.0% of resuscitations, patients survived
to discharge from hospital.
Figure 1 <http://jama.ama-assn.org/issues/v285n12/fig_tab/joc02206_f1.html>
illustrates how the decision aid identified patients who would be discharged
from the hospital. Of the 327 resuscitations for which patients were
discharged from hospital, 287 satisfied the first component of the decision
aid ("arrest was witnessed"). Of the remaining 40 resuscitations, 10
satisfied the second component of the aid ("initial rhythm was ventricular
tachycardia or ventricular fibrillation"). Twenty-seven of the remaining 30
resuscitations satisfied the final component of the decision aid ("pulse
regained during the first 10 minutes of chest compressions").
Table 2 <http://jama.ama-assn.org/issues/v285n12/fig_tab/joc02206_t2.html>
presents the classification performance of the decision aid. Of the 327
resuscitations for which patients were discharged from hospital, all but 3
satisfied the decision aid, resulting in a sensitivity of 99.1% (95% CI,
97.1%-99.8%). That is, the decision aid correctly identified all but 0.9% of
those who were discharged from the hospital. The decision aid had a negative
predictive value of 98.9% (95% CI, 96.5%-99.7%). That is, 1.1% of arrests
that the decision aid predicted had no chance of survival were actually
discharged from the hospital.
Likelihood ratios allow clinicians to measure the quantitative importance of
test results. 18 <http://jama.ama-assn.org/issues/v285n12/rfull/#r18> The
negative likelihood ratio of the decision aid was 0.064. To put this into
perspective, assume that we could accurately determine the probability that
hospitalized patients will survive to discharge if they required
resuscitation. Also, assume that we have 3 patients whose probability of
surviving to hospital discharge, in the event of an arrest, is 30%, 15%, and
5%. If these patients did not satisfy the decision aid during their
resuscitations, their probabilities of surviving to discharge would decrease
to 2.7%, 1.1%, and 0.3%, respectively.
We determined the outcome of the 3 people whom the aid predicted had no
chance of being discharged from the hospital. The first patient was a
76-year-old man with dementia, hypertension, and chronic obstructive
pulmonary disease who was transferred to another hospital following
resuscitation to continue inpatient medical therapy. When he was discharged
he was in a very poor condition and required tracheostomy, gastrostomy,
foley catheter, and rectal tube. These, however, were at least partially
required for an obstructive oropharyngeal carcinoma as opposed to ischemic
cerebral damage. He died 2 months following discharge from the hospital. The
second patient was a 43-year-old man with chronic obstructive pulmonary
disease and alcoholic cardiomyopathy. Although he had minimal ischemic
damage from the arrest, he was discharged to a nursing home residence
because of problems caring for himself. The final patient was a 65-year-old
previously well woman who had an arrest following back surgery. She had no
ischemic injury but required nursing home placement because of complications
of her back surgery.
Of the 269 resuscitations in which patients were predicted to have no chance
of surviving to hospital discharge, the mean resuscitation duration was 22.6
minutes (SD, 11.1 minutes; range, 10-72 minutes). In 53 of these
resuscitations (19.7%), patients achieved a spontaneous circulation and were
transferred to the intensive care unit. Twenty-six of these patients
remained alive for at least 24 hours but died later during the
hospitalization. These 26 patients survived a mean of 8.5 days following the
resuscitation (range, 1-29 days; total, 213 days). Of the 20 patients whose
chart was available, 15 (75%) never regained consciousness. For 9 (45%) of
these 20 patients, a decision was made to withdraw active care.
COMMENT
Using one of the world's largest continuous registries of hospital
resuscitations, we found that a simple clinical decision aid performed well
to identify patients with any chance of discharge from hospital following
resuscitation. All but 3 patients (1.1%) who did not meet criteria for the
decision aid died following their arrest. We believe that this decision aid
can be used with other clinical factors to help physicians identify patients
who are extremely unlikely to benefit from ongoing resuscitation efforts.
Our aid meets the most important methodological standards for decision aids.
19-21 <http://jama.ama-assn.org/issues/v285n12/rfull/#r19> The outcome
predicted by the aid is important and objective. The aid is clinically
sensible since each component (ie, witnessed arrest, 8
<http://jama.ama-assn.org/issues/v285n12/rfull/#r8> initial ventricular
tachycardia or ventricular fibrillation, 7
<http://jama.ama-assn.org/issues/v285n12/rfull/#r7> and duration of
resuscitative efforts 4 <http://jama.ama-assn.org/issues/v285n12/rfull/#r4>
, 7 <http://jama.ama-assn.org/issues/v285n12/rfull/#r7> , 8
<http://jama.ama-assn.org/issues/v285n12/rfull/#r8> , 22
<http://jama.ama-assn.org/issues/v285n12/rfull/#r22> ) has been associated
with survival in other studies. The potential effects of using the decision
aidin terms of avoided intensive care unit dayshave been estimated in both
the derivation 14 <http://jama.ama-assn.org/issues/v285n12/rfull/#r14> as
well as this study. Most important, the aid has been validated on a distinct
population, a standard met by fewer than half of all decision aids published
between 1991 and 1994 in 4 major medical journals. 19
<http://jama.ama-assn.org/issues/v285n12/rfull/#r19> We hope that this aid
will be tested further in other patient populations, preferably in a
prospective fashion, to further ensure its validity.
Two factors regarding the decision aid require more detailed discussion.
First, this study showed that the decision aid is very robust since it was
valid in a separate patient group despite large differences between the
derivation and validation populations. Compared with the derivation group,
14 <http://jama.ama-assn.org/issues/v285n12/rfull/#r14> patients in this
study were significantly younger (mean age, 65 vs 68 years, P<.001), and
were less likely to have have had an arrest on the ward (43.9% vs 55.2%).
Outcomes for the validation group were much better with a significantly
greater number of patients surviving to 1 hour (48.8% vs 33%, P = .0001) and
discharge (15.0% vs 9.6%, P<.001). Most important, the patients used for the
derivation and validation studies were from very different health care
systems. The observation that our decision aid performed so well in such a
different patient population should give physicians confidence to apply it
to their own patients.
Second, although each component of the aid is very objective, it must be
used with care since difficulties in measuring time, classifying cardiac
rhythms, and determining the presence of a pulse during the resuscitation
have been well documented in the medical literature. All patients who had an
arrest in the intensive care unit or while on a monitor are considered
witnessed arrests when applying this aid, even if they are not actually
visualized to become unstable. Similarly, physicians must be confident about
the classification of the initial rhythm, and special care must be exercised
to ensure that perfusing rhythms with hypotension are not classified as
pulseless electrical activity. Also, physicians must ensure that
resuscitative efforts have truly proceeded for a complete 10 minutes,
without the return of a pulse that persisted for 2 or more minutes, before
the last component of the aid is determined. Finally, this decision aid
cannot be applied to out-of-hospital resuscitations without further
research.
Although the resuscitations in this study spanned over 9 years, we do not
believe that changes in resuscitation significantly affected our results.
Between 1987 and 1996, the time period of the study, no pharmacological or
mechanical intervention was introduced that reliably improved the patient
outcomes following resuscitation. Although monitoring technology, such as
telemetry, might have become more prevalent during the study, the decision
aid would account for this since all such patients would be classified as
having a witnessed arrest.
This study addresses several criticisms of our decision aid. 2
<http://jama.ama-assn.org/issues/v285n12/rfull/#r2> There was concern that
patients who regained a pulse within the first 10 minutes of the
resuscitation, only to lose it again at 10 minutes, would not satisfy the
decision aid and would have resuscitative efforts withdrawn. Since the
registry used for this study recorded when patients had any return of
spontaneous rhythm, we ensured that patients who regained a pulse for longer
than 2 minutes within the first 10 minutes of resuscitation satisfied the
decision aid. Second, the decision aid only identified 12% of the study
group as patients with no chance of survival. However, this is comparable to
other decision aids used to identify patients with poor outcomes postarrest
such as the Pre-Arrest Morbidity score, 12
<http://jama.ama-assn.org/issues/v285n12/rfull/#r12> , 23
<http://jama.ama-assn.org/issues/v285n12/rfull/#r23> , 24
<http://jama.ama-assn.org/issues/v285n12/rfull/#r24> the Prognosis After
Resuscitation score, 12 <http://jama.ama-assn.org/issues/v285n12/rfull/#r12>
, 23 <http://jama.ama-assn.org/issues/v285n12/rfull/#r23> and the APACHE
(Acute Physiology and Chronic Health Evaluation) III index, 12
<http://jama.ama-assn.org/issues/v285n12/rfull/#r12> each of which applied
to between 5% and 20% of all resuscitations. Third, we were criticized for
both ignoring prearrest patient factors that are associated with outcomes
and attempting to derive a simple decision aid to be applied to such a
diverse population of patients having a broad range of survival
probabilities. As we demonstrated in this article, physicians could combine
the negative likelihood ratio of the decision aid with estimated prearrest
survival probabilities to improve prognostication. 18
<http://jama.ama-assn.org/issues/v285n12/rfull/#r18> However, we believe
that freeing physicians from having to calculate a pretest probability of
survival based on various factors is a strength of the aid. Since many
patients with a good prognosis have some return of spontaneous circulation
within the first 10 minutes of the resuscitation, our aid innately accounts
for these patients. Finally, we agree that any time patients are interactive
with their environment after resuscitationeven if they end up dying lateris
valuable. However, we do not feel that this advocates adopting a "never give
up" mind-set during resuscitative efforts. Our data show that for each
person who did not satisfy the decision aid but regained consciousness,
approximately 15 people did not. In many of these cases, family members are
put in the unenviable position of having to decide whether to withdraw care
from a loved one. Given the stress that this causes, 25
<http://jama.ama-assn.org/issues/v285n12/rfull/#r25> , 26
<http://jama.ama-assn.org/issues/v285n12/rfull/#r26> it is arguably a high
price to pay.
We believe that the decision aid validated in this study can be used by
physicians to identify patients who are extremely unlikely to benefit from
ongoing resuscitation efforts. Further validation of the aid in multiple
sites with prospectively collected data would be welcome. In addition, this
decision aid might also help patients be more directive regarding their
resuscitation attempts. Our data could allow patients and physicians to
precisely quantify when resuscitative efforts would be stopped, such as when
our decision aid is not satisfied. Since patients are often afraid of being
resuscitated only to remain on life support, our decision aid could be used
to help patient decision making that might avoid such a situation.
Author/Article Information
Author Affiliations: Department of Medicine, University of Ottawa, Ottawa,
Ontario (Drs van Walraven, Forster, and Stiell); Department of Internal
Medicine, Mercer University School of Medicine, Macon, Ga (Drs Parish, Dane,
Chandra, Mr Durham, and Ms Whaley); Clinical Epidemiology Unit, Loeb Health
Research Institute, Ottawa Hospital, Ottawa, Ontario (Drs van Walraven and
Stiell); and Institute for Clinical Evaluative Sciences, Toronto, Ontario
(Dr van Walraven).
Corresponding Author: Carl van Walraven, MD, FRCPC, MSc, F-660, 1053 Carling
Ave, Ottawa, Ontario, Canada K1Y 4E9 (e-mail: [log in to unmask]
<mailto:[log in to unmask]> ).
Author Contributions: Study concept and design: van Walraven, Stiell,
Parish, Forster.
Acquisition of data: Dane, Parish, Whaley, Durham, Chandra.
Analysis and interpretation of data: van Walraven, Dane, Parish.
Drafting of the manuscript: van Walraven, Durham, Forster.
Critical revision of the manuscript for important intellectual content: van
Walraven, Stiell, Dane, Parish, Whaley, Durham, Chandra.
Statistical expertise: van Walraven, Stiell, Dane, Forster.
Administrative, technical, or material support: Dane, Parish, Whaley,
Durham, Chandra.
Funding/Support: Dr van Walraven was supported by the Physicians' Services
Foundation Arthur Bond Scholarship and an Ontario Ministry of Health Career
Scientist Award. Dr Forster is an R. Samuel McLaughlin Fellow with the
Division of General Medicine, Brigham and Women's Hospital, Harvard Medical
School. Dr Dane is the Kilpatrick Professor at Mercer University, Macon, Ga.
Dr Stiell is a scientist of the Canadian Institute of Health Research.
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