Assignment in Biostatistics

Assignment in Biostatistics
See the pdf files it will help doing the HWThe HW is starting from slide 22-25 ..

Tutorial 1
DR. MAHMOUD ZAKI EL-READI
ASSOCIATE PROFESSOR OF BIOCHEMISTRY
mzreadi@uqu.edu.sa
DR. ALAA FALEMBAN
ASSOCIATE PROFESSOR OF CLINICAL PHARMACOLOGY
ahfalemban@uqu.edu.sa
BIOSTATISTICS
Postgraduate studies program at the Department of Pharmacology and Toxicology
Master’s in Clinical Toxicology
 Which of the following statements are true?
I. All variables can be classified as quantitative or categorical variables.
II. Categorical variables can be continuous variables.
III. Quantitative variables can be discrete variables.
A. I only
B. II only
C. III only
D. I and II
E. I and III
1
Imagine you’ve designed a survey…
 Which of the following questions will give you discrete data?
A. What is your age?
B. What is your sex?
C. What is your pulse rate?
D. How many times do you visit a doctor in a year?
2
 Which of the following statements are true?
Continuous variables are
A. Measured, not counted
B. Can be made qualitative, if categories are determined
C. Both a and b
D. None of the above
3
4
► This distribution has
A. Negative skew
B. No skew
C. Positive skew
You are trying to determine what the best combination of diet and exercise to provide
the most weight loss. You decided to try three different diets (Atkins, Paleo, McDonald’s
only), along with no dieting, and two different forms of exercise (Yoga, high cardio),
along with no exercise. You try each combination possible, and track weight loss for
each.
 How many independent variables do you have?
A. 2
B. 4
C. 8
D. 12
5
You are trying to determine what the best combination of diet and exercise to provide
the most weight loss. You decided to try three different diets (Atkins, Paleo, McDonald’s
only), along with no dieting, and two different forms of exercise (Yoga, high cardio),
along with no exercise. You try each combination possible, and track weight loss for
each.
 How many treatments do you have?
A. 2
B. 4
C. 7
D. 12
6
 What is the standard deviation of this sample?
Y
11
15
8
11
12
12
12
6
7
8
Blood concentrations of certain toxic substance are 95, 80, 75, 97, 75, 88.
► Which measure of central tendency would be the highest?
A. Mean
B. Median
C. Mode
We can perform different operations on the various type of data. For each of
the following state the type of data (Nominal, Ordinal, Numerical)
 on which we can perform the operation
A. count the frequencies
B. put in order
C. add items
9
A social researcher wanted to link the number of offspring to the socioeconomic status
of the individual. He got the following results:
 According to this data,
1. Which is the predictor variable and which is the outcome variable?
2. What is the type of data for both variables?
Socioeconomic status Number of offspring
Low 10
Average 5
Above average 2
High 1
10
In a randomized controlled trial (RCT), among 100 patients who were assigned to the
study intervention, the average age was 50 with standard deviation (SD) being 10.
 Choose a proper statement which describes the distribution of age of the 100
patients.
A. The minimum age is 40, and maximum age is 60.
B. 95% of patients’ age lies between 40 to 60.
C. 95% of patients’ age lies between 30 to 70.
D. If this study is repeated, 95% of studies would have mean age between 30 to 70.
11
 Which of the following measure of data variation should we use to graphically report
a study finding which indicates that mean blood pressure was statistically
significantly different between 2 groups.
A. SD
B. SE
C. 95% CI
D. SD and SE
12
13
 Find the mean of following data: 10, 15, 12, 9, 2, 6.
A. 12
B. 9
C. 54
D. 10.9
14
 The measures of central tendency for the data set 1, 3, 9, 11, 2 are:
A. Mean=5.2 median=3 mode=no mode
B. Mean=5.2 median=9 mode=zero
C. Mean=5.2 median=3 mode=zero
D. Mean=5.2 median=9 mode=no mode
15
The costs of six drugs in a certain pharmacy are: SAR 15, SAR 20, SAR 32, SAR 1,250, SAR
27, SAR 50 Which measure of central tendency should be used?
A. Mode
B. Mean
C. Range
D. Median
16
When the distribution is positively skewed, the relationship between the mean, median
and mode will be:
A. Mean = Median = Mode
B. Mean > Median > Mode
C. Mean < Median < Mode
D. Cannot be determined Median
17
What is the appropriate measure for the data that represent the marital status (married,
divorced, widowed, single)?
A. Median
B. Range
C. Mean
D. Mode
18
If the CVar for an cancer biomarker A is 6.9%, and the CVar for cancer biomarker B is
4.9%, compare the variations.
A. The biomarker A is more variable
B. The biomarker B is more variable
C. Both tests have the same variation
D. Cannot be determined Mode
19
The mean of a distribution is 80, and the standard deviation is 7. If the distribution is bellshaped, approximately 99.7% of the data values will fall between ………
A. 59 and 94
B. 59 and 101
C. 66 and 94
D. 66 and 101
20
If the mean of the number of sales of houses is 56, and the variance is 36, then the
coefficient of variation is ………
A. 10.7%
B. 0.643%
C. 64.3%
D. 0.107%
Home Assignments
 “who are the patients” – who participated to this study?
 How do you utilize the number of 8.1 given in the article?
 Table 2 showed daily and cumulative doses of sedative and analgesic medication. Mean
lorazepam use was 4.8 mg with the standard deviation being 12.8. Calculate CI. What are
your observations?
 By the help of table 1, which
describes patients’
characteristics, Describe data
regarding benzodiazepines
intake
SPSS Assignment
 Small sample study was done to evaluate the effectiveness of educational interventions on
improving the control of blood pressure in patients with hypertension.
 BP was measured for 4 times in two groups:
1. Study group A (education)
• Group A get educational course
• Group B did not get any educational course
1. Study group B (medications)
• Group A: Monotheapy antihypertensive drug
• Group B: Combination therapy of antihypertensive drugs.
Tasks
✓ Use the data of the attached excel sheet to generated SPSS data file
✓ Do the descriptive Statistic → Frequency (Tables and Graphs)
✓ Send me the word file contain this tables and Graphs.
✓ Send me the output and data file of SPSS

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CARING FOR THE
CRITICALLY ILL PATIENT
Delirium as a Predictor of Mortality
in Mechanically Ventilated Patients
in the Intensive Care Unit
E. Wesley Ely, MD, MPH
Ayumi Shintani, PhD, MPH
Brenda Truman, RN, MSN
Theodore Speroff, PhD
Sharon M. Gordon, PsyD
Frank E. Harrell, Jr, PhD
Sharon K. Inouye, MD, MPH
Gordon R. Bernard, MD
Robert S. Dittus, MD, MPH
Itients are cared for daily in more than 6000 intensive care units (ICUs). The most common reason for ICU N THE UNITED STATES, 55000 PA- 1
admission is respiratory failure and the
need for a mechanical ventilator.2 Although hospital mortality for such patients ranges from 30% to 50%,3 only
16% of patients receiving mechanical
ventilation die directly of respiratory failure.4 In fact, nonpulmonary acute organ dysfunction contributes importantly to mortality.5,6 Delirium is one of
these nonpulmonary considerations yet
remains understudied in critically ill patients. Although scoring systems for severity of illness have included the
Glasgow Coma Scale7,8 as an important
predictor of outcome, there has been no
in-depth analysis focusing on the direct
contribution of delirium to clinical outcomes in critically ill ICU patients.
Management of patients with sepsis
and multiorgan failure has tradition- Author Affiliations Corresponding Author: are listed at the end of this article. E. Wesley Ely, MD, MPH,
Division of Allergy/Pulmonary/Critical Care Medicine, Center for Health Services Research, Sixth Floor
Medical Center East #6109, Vanderbilt University
Medical Center, Nashville, TN 37232-8300
(wes.ely@vanderbilt.edu; www.icudelirium.org).
Caring for the Critically Ill Patient Section Editor:
Deborah J. Cook, MD, Consulting Editor, JAMA.
Advisory Board: David Bihari, MD; Christian BrunBuisson, MD; Timothy Evans, MD; John Heffner, MD;
Norman Paradis, MD; Adrienne Randolph, MD.
Context In the intensive care unit (ICU), delirium is a common yet underdiagnosed
form of organ dysfunction, and its contribution to patient outcomes is unclear.
Objective To determine if delirium is an independent predictor of clinical outcomes,
including 6-month mortality and length of stay among ICU patients receiving mechanical ventilation.
Design, Setting, and Participants Prospective cohort study enrolling 275 consecutive mechanically ventilated patients admitted to adult medical and coronary
ICUs of a US university-based medical center between February 2000 and May 2001.
Patients were followed up for development of delirium over 2158 ICU days using the
Confusion Assessment Method for the ICU and the Richmond Agitation-Sedation
Scale.
Main Outcome Measures Primary outcomes included 6-month mortality, overall
hospital length of stay, and length of stay in the post-ICU period. Secondary outcomes were ventilator-free days and cognitive impairment at hospital discharge.
Results Of 275 patients, 51 (18.5%) had persistent coma and died in the hospital.
Among the remaining 224 patients, 183 (81.7%) developed delirium at some point
during the ICU stay. Baseline demographics including age, comorbidity scores, dementia scores, activities of daily living, severity of illness, and admission diagnoses were
similar between those with and without delirium (P.05 for all). Patients who developed delirium had higher 6-month mortality rates (34% vs 15%, P=.03) and spent
10 days longer in the hospital than those who never developed delirium (P.001).
After adjusting for covariates (including age, severity of illness, comorbid conditions,
coma, and use of sedatives or analgesic medications), delirium was independently associated with higher 6-month mortality (adjusted hazard ratio [HR], 3.2; 95% confidence interval [CI], 1.4-7.7; P=.008), and longer hospital stay (adjusted HR, 2.0; 95%
CI, 1.4-3.0; P.001). Delirium in the ICU was also independently associated with a
longer post-ICU stay (adjusted HR, 1.6; 95% CI, 1.2-2.3; P=.009), fewer median days
alive and without mechanical ventilation (19 [interquartile range, 4-23] vs 24 [19-
26]; adjusted P=.03), and a higher incidence of cognitive impairment at hospital discharge (adjusted HR, 9.1; 95% CI, 2.3-35.3; P=.002).
Conclusion Delirium was an independent predictor of higher 6-month mortality and
longer hospital stay even after adjusting for relevant covariates including coma, sedatives, and analgesics in patients receiving mechanical ventilation.
JAMA. 2004;291:1753-1762 www.jama.com
See also Patient Page.
©2004 American Medical Association. All rights reserved. (Reprinted) JAMA, April 14, 2004—Vol 291, No. 14 1753
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ally been centered on dysfunction in the
heart, lungs, or kidneys rather than the
brain, though the brain is one of the organs most commonly involved.9-13 Delirium has received little attention in
ICU settings because it is (1) rarely a
primary reason for admission, (2) often believed to be iatrogenic due to
medications, (3) frequently explained
away as “ICU psychosis,” and (4) believed to have no adverse consequences in terms of patients’ ultimate
outcome.14-16 Last, there is a paucity of
published trials of prevention or treatment of delirium showing altered outcomes17 and none in ICU patients.
Even among clinicians who exhibit an
overall appreciation for delirium as an
important form of organ dysfunction, recent data point to a general disconnect
between its perceived importance and
current monitoring practices. Despite recent guidelines suggesting that ICU patients be monitored daily for delirium,18 only 6.4% (58/912) of critical
care professionals surveyed in 2001-
2002 reported objectively monitoring for
this condition.19 Indeed, delirium, especially the hypoactive subtype,20,21 goes
unrecognized in more than two thirds
of the patients in clinical practice.22-25
The original Confusion Assessment
Method of Inouye et al26 popularized
monitoring of delirium by nonpsychiatrists. In non-ICU hospital settings, delirium has been associated with prolonged stay, greater dependency,
subsequent institutionalization, and increasedmortality.17,27-34 However,onlyrecently have valid and reliable instruments to measure both level of
arousal35-37 and delirium38-40 in ICU patients become available. Using these instruments, our pilot study showed that
delirium in the ICU was an important determinant of length of hospital stay.41 We
undertook the current study to test the
hypothesis that delirium in the ICU is an
independent predictor of 6-month mortality and length of stay among patients
receiving mechanical ventilation even after adjusting for other covariates.
METHODS
Patients
The Vanderbilt University institutional review board approved this study,
and written informed consent was obtained from patients or their surrogates. Enrollment criteria included any
adult, mechanically ventilated patient
admitted to medical or coronary ICUs
of the 631-bed Vanderbilt University
Medical Center between February 2000
to May 2001. While no outcomes data
from this report have been previously
published, other data from this cohort
have been published.37,39,42 Exclusion
criteria, defined a priori, are outlined
in the patient flow diagram (FIGURE 1).
Study Protocol
Study nurses enrolled patients each
morning and recorded baseline demographic information. Information collected at enrollment included patient
demographics and severity of illness using the most abnormal values obtained during the first 24 hours of ICU
stay to calculate Acute Physiology and
Chronic Health Evaluation II (APACHE
II) (scale range, 0-71)7 and Sequential
Organ Failure Assessment (SOFA)
(scale range, 0-24) scores.8 The Charlson Comorbidity Index, which represents the sum of a weighted index that
takes into account the number and seriousness of preexisting comorbid conditions, was calculated as per Deyo et
al.43 Surrogate assessments were used
for baseline activities of daily living
(scale range, 0-12),44 visual and hearing deficits, and the modified Blessed
Dementia Rating Scale (mBDRS) (scale
range, 0-17),45 an instrument validated against brain pathological specimens to measure a patient’s baseline
likelihood of dementia.
Terminology
Delirium has more than 25 synonyms,
including acute encephalopathy, septic encephalopathy, toxic psychosis,
ICU psychosis, and acute confusional
state.10,11,14,46,47 Delirium will be the term
used herein, because the neurologic
monitoring instrument used in this investigation (described below) was developed and validated using Diagnostic and Statistical Manual of Mental
Disorders, Fourth Edition criteria for delirium.48
Explanatory Variable
Definitions and Patient Assessments. Patients’ neurologic status was
assessed daily by the study nurses and
defined as normal, delirious, or comatose using a 1- to 2-minute neurologic
assessment that objectively measured
patients’ arousal and delirium status.
Arousal was measured using the
Richmond Agitation-Sedation Scale
(RASS).36,37 The RASS is a wellvalidated and highly reliable 10-point
scale with scores from +1 to +4 assigned for levels of agitation through
combativeness, 0 assigned for alert and
calm state, and –1 to –5 assigned for
successive levels of depressed arousal
or coma.37 Delirium, the independent
variable, was measured using a wellvalidated and highly reliable instrument, the Confusion Assessment
Method for the ICU (CAM-ICU).39,40
The CAM-ICU assessment was positive if patients demonstrated an acute
change or fluctuation in the course of
Figure 1. Flow of Patients in Study Cohort
224 Included in Outcomes
Analyses
51 Persistently Comatose and
Unable to Be Evaluated for
the Primary Independent
Variable (Delirium)
280 Excluded
86 Had Stroke Syndrome or
Other Primary Neurologic
Disease
13 Were Deaf or Were Unable
to Speak or Understand
English
69 Were Extubated Prior
to Enrollment
27 Had Been Previously
Enrolled
41 Patient or Family
Refused to Participate
44 Died Before Study
Nurses’ Assessments
275 Enrolled
555 Mechanically Ventilated
Patients Admitted to
the ICU
ICU indicates intensive care unit.
DELIRIUM IN MECHANICALLY VENTILATED PATIENTS
1754 JAMA, April 14, 2004—Vol 291, No. 14 (Reprinted) ©2004 American Medical Association. All rights reserved.
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their mental status (as determined by
abnormalities or fluctuations in the
RASS scores), plus inattention and
either disorganized thinking or an altered level of consciousness.39,40 By definition, patients were delirious if they responded to verbal stimulation with eye
opening (RASS scores of –3 to +4) and
had positive CAM-ICU assessments. Patients were defined as comatose if they
responded only to physical/painful
stimulation with movement but had no
eye opening (RASS score, –4) or if they
had no response to verbal or physical
stimulation (RASS score, –5). Patients
were defined as normal if they were not
delirious or comatose.
Categorization by Explanatory Variable. Using daily assessments described above, it was determined a priori
that patients would be included in a “delirium” group if they ever had delirium
while in the ICU, and all others would
be included in a “no delirium” group.
To understand the phenomenology of
these groups, patients in the delirium
group were further categorized as “delirium only” (ie, delirium but no episodes of coma) or as “delirium-coma”
(ie, delirium and coma). Likewise, patients in the no delirium group were categorized as “normal” (ie, no episodes of
delirium or coma) or as “comanormal” (ie, transient coma [eg, coma
due to sedative medications] followed
by consistently normal examinations).
Patients who were comatose on all ICU
evaluations during the study were categorized as “persistent coma.”
Outcome Variables
The primary outcome variables included 6-month mortality, overall hospital length of stay, and length of stay
in the post-ICU period. In addition, we
included 2 secondary outcome variables: ventilator-free days and cognitive impairment at discharge. Ventilatorfree days were defined as the number of
days alive and free of mechanical ventilation between study enrollment and
day 28.49 Cognitive impairment at discharge was defined as a Mini-Mental
State Examination score50 of less than 24
out of a possible 30 points.51-53
Statistical Analysis
Patients’ baseline demographic and clinical variables were assessed using Wilcoxon rank sum tests for continuous
variables; Fisher exact tests were used
for comparing proportions. For analysis of analgesics (morphine, fentanyl)
and sedatives (lorazepam, propofol),
mean daily ICU dose and cumulative
dose per patient during the ICU stay
were used as summary measures. Administered benzodiazepines were either
lorazepam or midazolam, and midazolam dose was converted to “lorazepam equivalents” (henceforth referred
to as lorazepam) by dividing by 3 to
achieve equipotent dose.54 Wilcoxon
rank sum tests were used to compare distributions of the drugs between the no
delirium and delirium groups.
Six-month mortality, overall hospital length of stay, and length of stay after first ICU discharge were analyzed using time-to-event analyses. Patients were
followed up from time of enrollment until hospital discharge. All survivors were
then followed up using the hospital’s
electronic record system, monthly telephone calls, and in-person visits for survival status. Kaplan-Meier survival
curves were used for graphical presentation of time to death or hospital discharge, and log-rank statistics were used
to assess difference by overall delirium
status.55 For 6-month mortality analyses, patients were censored at the time
of last contact alive or at 6 months from
enrollment, whichever was first. Censoring for length-of-stay analyses occurred at time of hospital death.
Cox proportional hazard regression
models with time-dependent covariates56-58 were used to obtain hazard ratios (HRs) of death up to 6 months from
enrollment and HRs of remaining in
hospital. Details of the model construction are described below. The 11 covariates in the multivariable Cox
regression models included a timedependent coma variable, 6 additional
baseline covariates chosen a priori based
on clinical relevance (patient age at enrollment, Charlson Comorbidity Index,43 mBDRS score,45 APACHE II
score,7 SOFA score,8,59,60 admitting
diagnoses of sepsis or acute respiratory distress syndrome), and the 4 sedative and analgesic medications used in
this cohort (lorazepam, propofol, morphine, and fentanyl). Patients’ neurologic status (normal, delirious, comatose) was updated daily in the ICU,
and time-dependent variables were
used for delirium and coma separately. This time-dependent delirium incidence variable was coded as 0 for the
days prior to the first delirious event,
and coded as 1 thereafter. The timedependent coma incidence variable was
coded similarly.
In addition, we performed a similar
analysis that considered the duration of
delirium using cumulative number of
days of delirium, coding the timedependent delirium duration variable
as 0 until a delirium event occurred, and
then incrementally adding 1 when each
additional day of delirium occurred.
The time-dependent coma duration
variable was created similarly for this
additional analysis.
The time-dependent delirium incidence variable was used as the main independent variable in all Cox models
with adjustment for time-dependent
coma incidence variable. Cox regression models were then used to further
control for the additional 6 baseline covariates mentioned above and the 4
sedative and analgesic medications.
Dummy coding was used for missing
observations with the mBDRS. Because coma was already being handled
as a covariate in the model, the
APACHE II and SOFA scores were calculated without inclusion of the
Glasgow Coma Scale. To incorporate
sedative (lorazepam, propofol) and analgesic (morphine, fentanyl) medications in a time-dependent fashion, daily
use of medication was coded as 1 for
each of 4 drug variables separately if any
amount was administered prior to daily
assessment of neurologic status and was
coded as 0 otherwise. In an additional
analysis, time-dependent cumulative
dose of sedatives and narcotics were incorporated into the model. Collinearity among all independent variables was
evaluated by examining the variance inDELIRIUM IN MECHANICALLY VENTILATED PATIENTS
©2004 American Medical Association. All rights reserved. (Reprinted) JAMA, April 14, 2004—Vol 291, No. 14 1755
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flation factor.61 Assumptions of proportional hazard for the final models
were evaluated by examining interactions between time and each variable
in the model. When significant interactions were found, those interaction
terms were included in the final model.
Ventilator-free days were calculated
as described in the “Dependent Variables” section above and compared between the delirium and no delirium
groups. A Poisson regression model
with overdispersion correction was used
to control for the set of covariates stated
above. Presence or absence of cognitive impairment at hospital discharge
was assessed as described in the “Dependent Variables” section and compared between the delirium and no delirium groups using Fisher exact tests,
and a logistic regression model was used
to adjust for the set of 11 covariates. All
data analyses were performed using SAS
8.02 (SAS Institute, Cary, NC); a significance level of .05 was used for statistical inferences.
RESULTS
Patients’ Baseline Characteristics
During the study period, 555 mechanically ventilated ICU patients were admitted, of whom 275 (49.5%) were enrolled within a mean and median of 1
day and 280 met exclusion criteria (Figure 1). On enrollment, 23 (8.4%) patients were defined as normal, 89
(32.4%) as delirious, and 163 (59.3%)
as comatose. FIGURE 2 shows the proportion of patients in each neurologic
category (as well as death or ICU discharge) over the first 14 days from study
enrollment. Of the 275 enrolled patients, 51 (18.5%) never woke up from
coma and experienced 100% ICU mortality after a median of 3 (interquartile
range [IQR], 1-5) days. These 51 patients with persistent coma had a mean
age of 55 (SD, 16) years and similar
baseline characteristics compared with
the remaining 224 patients, with the exception of greater severity of illness at
enrollment as measured by mean
APACHE II scores (29.5 [SD, 9]) and
SOFA scores (12.1 (SD, 3.8]) and by
greater rates of malignancy (14%) and
sepsis/acute respiratory distress syndrome (63%) as admission diagnoses
(P.05 for all). Due to their 100% mortality and the inability to evaluate them
for the independent variable (delirium),
patients categorized as experiencing
persistent coma were not included in
outcomes analyses. The remaining 224
patients were used for these analyses;
their baseline characteristics are shown
in TABLE 1. The cohort was divided into
2 groups according to whether they ever
developed delirium in the ICU. There
were no significant differences between the delirium and no delirium
groups for demographic variables, baseline comorbidities, activities of daily living, severity-of-illness scores, organ dysfunction scores, or admission diagnoses.
Prevalence of Delirium and Coma
All 224 patients were followed up for development of delirium over 2158 ICU
days. Forty-one patients (18.3%) never
demonstrated delirium in the ICU (ie,
the no delirium group); of those, 24
(58.5%) were in a coma for a median of
1.5 (IQR, 1-3) days, during which time
21 (87.5%) received sedative or analgesic medications. Delirium in the ICU developed in 183 (81.7%) patients (ie, the
delirium group) for a median of 2 (IQR,
1-3) days, of whom 123 also were in a
coma for a median of 2 (IQR, 1-4) days.
Delirium occurred in 77.9% (60/77) of
those without coma and in 83.7% (123/
147) of those with coma (P=.29). Overall, patients spent 21.6% of their ICU
days as normal, 43.1% as delirious, and
35.3% as comatose. Of patients who
were alert or easily arousable as measured by a RASS score of 0 or −1, more
than half (54.5%) were delirious.
Sedative and Analgesic
Medication Use
Mean daily dose and cumulative administered dose of sedative and narcotic medications (ie, lorazepam, propofol, morphine, and fentanyl) used in
this cohort are presented in TABLE 2.
Both mean daily and cumulative doses
of these medications were higher in patients in the delirium group, but only
lorazepam was significantly different between the 2 groups.
Delirium and Associated
Clinical Outcomes
Six-Month Mortality. During the
6-month follow-up period, 34% (63/
183) of the patients in the delirium group
Figure 2. Daily Neurologic Status of 275 Patients in the ICU, Through the First 14 Days of the Study
Days After Enrollment
Percentage
Normal
1 3 5 7 9 11 13
60
40
50
20
30
10
0
Days After Enrollment
Delirium
1 3 5 7 9 11 13
Days After Enrollment
Coma
1 3 5 7 9 11 13
Days After Enrollment
Discharged From ICU
1 3 5 7 9 11 13
Days After Enrollment
Death
1 3 5 7 9 11 13
Denominator is identical (N = 275) for all 14 days. ICU indicates intensive care unit.
DELIRIUM IN MECHANICALLY VENTILATED PATIENTS
1756 JAMA, April 14, 2004—Vol 291, No. 14 (Reprinted) ©2004 American Medical Association. All rights reserved.
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died vs 15% (6/41) of the patients in the
no delirium group (P=.03) (TABLE 3).
FIGURE 3A shows Kaplan-Meier curves
of survival to 6 months among the patients in both groups, with significantly
higher mortality among patients with delirium in the ICU. Figure 3B further depicts the patients’ survival according to
both delirium and coma status.
Using a time-dependent multivariable Cox proportional hazards model
to adjust for all 11 of the covariates (including coma incidence and administration of sedative and analgesic
medications), delirium was associated
with a more than 3-times higher risk
of dying by 6 months (Table 3). In an
additional analysis (data not shown),
time-dependent cumulative doses of
sedatives and narcotics were incorporated into the model, with similar results compared with the primary analysis. No collinearity was identified
among the covariates used in these
analyses (all variance inflation factors
were 2, well below the threshold
of 10 used to indicate potential
collinearity). To complement the mortality analysis presented in Table 3, a
similar analysis that considered the duration of delirium found that after adjusting for the covariates, each additional day an ICU patient spent in
delirium was associated with a 10% increased risk of death (HR, 1.1; 95% confidence interval [CI], 1.0-1.3; P=.03).
Hospital Lengths of Stay. Compared with patients in the no delirium
group, those who did develop delirium
spent a median of 10 days longer in the
hospital overall (Table 3). FIGURE 4A
shows Kaplan-Meier curves of the probability of remaining in the hospital according to the clinical distinction of no
delirium vs delirium. Figure 4B shows
the no delirium and delirium groups further categorized by coma status, as in
Figure 3B. At any given time during the
hospital stay, patients diagnosed with delirium had an adjusted risk of remaining in the hospital that was twice as high
as those who never developed delirium
and a 60% greater risk of remaining in
the wards after ICU discharge (Table 3).
In a separate analysis, time-dependent
cumulative doses of sedatives and narTable 1. Baseline Characteristics of the Patients*
Characteristic
No. (%)†
No Delirium
(n = 41)
Delirium
(n = 183)
Age, mean (SD), y 54 (17) 56 (17)
Men 18 (44) 95 (52)
Race
White 32 (78) 145 (79)
Black 9 (22) 38 (21)
Charlson Comorbidity Index, mean (SD) 3.2 (2.8) 3.2 (2.8)
Vision deficits, No./total (%)‡ 23/33 (70) 104/153 (68)
Hearing deficits, No./total (%)‡ 5/32 (16) 29/152 (19)
mBDRS score, mean (SD) 0.14 (0.6) 0.23 (0.8)
Activities of daily living, mean (SD) 0.81 (2.4) 0.91 (2.3)
APACHE II score, mean (SD) 23.2 (9.6) 25.6 (8.1)
SOFA score, mean (SD) 9.5 (2.9) 9.6 (3.4)
ICU admission diagnosis§
Sepsis and/or acute respiratory distress syndrome 24 (59) 78 (43)
Pneumonia 6 (15) 35 (19)
Myocardial infarction/congestive heart failure 4 (10) 15 (8)
Hepatic or renal failure 0 11 (6)
Chronic obstructive pulmonary disease 2 (5) 18 (10)
Gastrointestinal bleeding 2 (5) 18 (10)
Malignancy 0 7 (4)
Drug overdose 3 (7) 8 (4)
Other 14 (34) 53 (29)
Abbreviations: APACHE II, Acute Physiology and Chronic Health Evaluation; ICU, intensive care unit; mBDRS, modified Blessed Dementia Rating Scale; SOFA, Sequential Organ Failure Assessment.
*All comparisons between the no delirium and delirium groups were nonsignificant (P.05). See “Methods” section for
descriptions of scales and for scale ranges.
†Except where noted otherwise.
‡Denominators indicate number of patients with available information.
§Recorded by the patients’ medical team as the diagnoses most representative of the reason for admission to the ICU.
Patients were sometimes given more than 1 admission diagnosis by the medical team, resulting in column totals
100%.
Table 2. Daily and Cumulative Doses of Sedative and Analgesic Medications
Drug
Daily ICU Dose, Mean (SD), mg Cumulative ICU Dose, Mean (SD), mg*
No Delirium
(n = 41)
Delirium
(n = 183) P Value†
No Delirium
(n = 41)
Delirium
(n = 183) P Value†
Lorazepam 1.12 (2.2) 4.8 (12.8) .01 9.0 (20.0) 49.2 (131.3) .001
Propofol 36.6 (258.6) 48.4 (172.9) .19 362.1 (1265.4) 591.2 (3942.2) .20
Morphine 5.8 (17.0) 17.3 (163.8) .79 48.0 (147.0) 168.1 (1321.9) .66
Fentanyl 0.53 (1.7) 0.78 (1.7) .22 3.1 (10.3)‡ 8.7 (22.9)‡ .12
Abbreviation: ICU, intensive care unit.
*In the persistently comatose patients, the mean (SD) cumulative doses of these medications were: lorazepam, 15 (27) mg; propofol, 318 (1434) mg; morphine, 107 (345) mg; and
fentanyl, 3 (12) mg.
†By Wilcoxon rank sum test for no delirium vs delirium.
‡Fentanyl is commonly reported to be 100 times more potent than morphine.54 Therefore, using a dose conversion factor of 0.01, the median cumulative “morphine equivalent”
dose of fentanyl given to patients in the no delirium and delirium groups would equate to 310 mg and 870 mg, respectively. While this mathematical conversion may be flawed
or confounded in vivo, such large values are plausible considering fentanyl’s initially short duration of action,18 the potential for rapid tolerance to fentanyl,62-64 and the administration of fentanyl as a continuous infusion rather than an intermittent bolus.
DELIRIUM IN MECHANICALLY VENTILATED PATIENTS
©2004 American Medical Association. All rights reserved. (Reprinted) JAMA, April 14, 2004—Vol 291, No. 14 1757
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cotics were incorporated into the model
with similar results (data not shown)
compared with the primary analysis. To
complement the length-of-stay analyses presented in Table 3, similar analyses that considered the duration of delirium found that after adjusting for the
covariates, each additional day spent in
delirium by an ICU patient was associated with a 20% and a 10% increased risk
of remaining in the hospital or in the
wards, respectively (hospital length of
stay: adjusted HR, 1.2; 95% CI, 1.1-1.3;
P=.002; post-ICU length of stay: adjusted HR, 1.1; 95% CI, 1.0-1.2; P=.04).
Secondary Outcomes. Secondary
outcomes included ventilator-free days
in the ICU and neurologic impairment
at discharge. There were significantly
fewer days alive and free of the ventilator among patients in the delirium group
(median, 19; IQR, 4-23) vs those in the
no delirium group (median, 24; IQR, 19-
26) (P.001). After adjusting for the 11
covariates, this difference remained significant (P = .03). Cognitive assessments were not available at the time of
hospital discharge for 51 of 179 survivors, due either to inability to complete
testing or to unexpected discharge. One
hundred twenty-eight survivors were
tested, of whom 63 (49.2%) had discharge cognitive impairment as defined
in the “Methods” section. Of those tested,
twice as many patients in the delirium
group vs the no delirium group exhibited cognitive impairment at hospital discharge (54.9% [56/102] vs 26.9% [7/26],
respectively; P=.01), and multivariable
analysis revealed that the patients in the
delirium group were 9 times more likely
to be discharged with cognitive impairment than were those in the no delirium group (adjusted HR, 9.1; 95% CI,
2.3-35.3; P=.002).
COMMENT
The development of delirium in these
mechanically ventilated patients was associated with a 3-fold increase in risk of
death after controlling for preexisting comorbidities, severity of illness, coma, and
the use of sedative and analgesic mediTable 3. Delirium Status and Clinical Outcomes Including 6-Month Mortality and Lengths of
Stay
No Delirium Delirium Adjusted P Value
6-Month Mortality
No. 41 183
Rate, No. (%) 6 (15) 63 (34)
Adjusted HR (95% CI)* Reference 3.2 (1.4-7.7) .008
Hospital Stay
No. 41 183
Median (IQR), d 11 (7-14) 21 (19-25)
Adjusted HR (95% CI)* Reference 2.0 (1.4-3.0) .001
Post-ICU Stay†
No. 40 156
Median (IQR), d 5 (2-7) 7 (4-15.5)
Adjusted HR (95% CI)* Reference 1.6 (1.1-2.3) .009
Abbreviations: CI, confidence interval; HR, hazard ratio; ICU, intensive care unit; IQR, interquartile range.
*Multivariable model incorporating baseline covariates including patient age at enrollment, Charlson Comorbidity Index,43 modified Blessed Dementia Rating Scale score,45 Acute Physiology and Chronic Health Evaluation II (APACHE
II) score,7 Sequential Organ Failure Assessment (SOFA) score,59,60 admitting diagnoses of sepsis or acute respiratory
distress syndrome, and time-varying covariates for coma and use (yes/no) of lorazepam, propofol, morphine, and
fentanyl. Assumptions of proportional hazard for the final models were evaluated by examining interactions between
time and each variable in the model. Interaction terms were included in the model whenever nonproportionality of
hazards was observed. For analysis of hospital length of stay, interactions were detected between time and APACHE
II scores, SOFA scores, presence of coma, and use of lorazepam. No other significant interactions were observed.
†Twenty-eight patients died in the ICU (1 in the no delirium group and 27 in the delirium group, P = .03) and were
therefore not included in the post-ICU length-of-stay analysis.
Figure 3. Kaplan-Meier Analysis of Delirium in the Intensive Care Unit and 6-Month Survival
100
30
60
50
40
70
80
90
20
10
0
No. at Risk
No Delirium
Delirium
0
41
183
1 2 3 4 5 6
34
138
25
111
28
116
21
98
19
88
22
104
Months After Enrollment
Probability of Survival, %
No Delirium
Delirium
A
Delirium Only
No Delirium Delirium
Delirium-Coma
Normal
Coma-Normal
100
30
60
50
40
70
80
90
20
10
0
No. at Risk
No Delirium
0 1 2 3 4 5 6
Normal
Coma-Normal
Delirium
Delirium Only
Delirium-Coma
17
24
60
123
15
19
51
87
11
15
39
72
11
17
42
74
10
11
33
65
10
9
29
59
10
12
34
70
Months After Enrollment
Probability of Survival, %
B
DELIRIUM IN MECHANICALLY VENTILATED PATIENTS
1758 JAMA, April 14, 2004—Vol 291, No. 14 (Reprinted) ©2004 American Medical Association. All rights reserved.
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cations. While development of coma is
well recognized as a risk factor for
death,7,8,10,11 this investigation is the first
to document a strong relationship between delirium and clinical outcomes after adjusting for coma. These data
showed not only that ever developing
this type of organ dysfunction was a predictor of death by 6 months after ICU
discharge, but also that the number of
days spent in a delirious state predicted mortality. In addition, delirium
was not simply a transition state from
coma to normal, as delirium occurred
just as often among those who never developed coma as it did among those who
did develop coma at some stage, and persisted in 11% of patients at the time of
hospital discharge.
Monitoring for Delirium in the ICU
In the absence of data linking delirium to outcomes, few ICUs routinely monitor for delirium. Monitoring for delirium with the CAM-ICU,
which is easily incorporated by nurses
into their daily work and takes only 1
to 2 minutes, could allow the medical
team to consider causes and modifications in their treatment of the patient
experiencing this organ dysfunction65,66 (downloadable materials and
discussion available at http://www
.icudelirium.org). We have found during a year-long implementation study
incorporating more than 22000 patient observations that nursing staff
readily incorporated such measurements into routine care,67 in keeping
with recently issued guidelines of the
Society of Critical Care Medicine.18
Perhaps the greatest benefit of incorporating delirium monitoring would be
the enhanced detection of the hypoactivedeliriumsubtype,oftencalled“quiet”
delirium because it is characterized by
a flat affect or apathy and often present
in otherwise calm and seemingly alert patients.68 This is in contrast to the readily
detected hyperactive delirium that is
characterized by agitation, restlessness,
attempting to remove catheters or tubes,
hitting, biting, and emotional lability.68
In this study, hypoactive delirium was
present in over 50% of patients with normal or near-normal arousal. This type of
brain dysfunction may portend a worse
prognosis than hyperactive delirium, accounts for the majority of delirium observations, and is the most commonly
missed subtype of delirium.21,47,68-70
Potentially Modifiable Risk Factors
Our findings suggest that an important opportunity for improving the care
of critically ill patients may be the determination of modifiable risk factors
for delirium in the ICU. Numerous risk
factors for delirium have been identified, including preexisting cognitive impairment; advanced age; use of psychoactive drugs; mechanical ventilation;
untreated pain; and a variety of medical conditions such as heart failure, prolonged immobilization, abnormal blood
pressure, anemia, sleep deprivation, and
sepsis.17,34,71-81
Some of the most readily implemented opportunities for improving
care could be to correct brain ischemia/
hypoxemia,82 to modify the administration of psychoactive medications,78
and to aggressively treat both underlying infection and the manifestations
of severe sepsis, especially in elderly patients.11,17,83-86 Regarding hypoxemia,
Hopkins et al82 found in 55 mechanically ventilated patients with acute lung
injury that mean oxygen saturations
were below 90% for 122 hours and below 85% for 13 hours per patient. Regarding use of psychoactive drugs, recent studies87-89 have shown that
reducing unnecessary use of sedatives
and analgesics may improve patients’
outcomes. Another approach to intervention would be to treat delirious patients with procognitive medications
such as haloperidol, as recommended
Figure 4. Kaplan-Meier Analysis of Delirium in the Intensive Care Unit and Hospital Length of Stay
100
30
60
50
40
70
80
90
20
10
0
No. at Risk
No Delirium
Delirium
0
41
183
10 20 30 40 50 60
23
137
3
43
8
82
1
13
04
3
20
Days After Enrollment
Probability of Being in the Hospital, %
No Delirium
Delirium
A
Delirium Only
Delirium
Delirium-Coma
No Delirium
Normal
Coma-Normal
100
30
60
50
40
70
80
90
20
10
0
No. at Risk
No Delirium
0 10 20 30 40 50 60
Normal
Coma-Normal
Delirium
Delirium Only
Delirium-Coma
17
24
60
123
8
15
38
99
21
17
26
35
25
57
10 58
00 22
21 8
12
Days After Enrollment
Probability of Being in the Hospital, %
B
DELIRIUM IN MECHANICALLY VENTILATED PATIENTS
©2004 American Medical Association. All rights reserved. (Reprinted) JAMA, April 14, 2004—Vol 291, No. 14 1759
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by the Society of Critical Care Medicine guidelines.18 However, such interventions need to be tested in future research. Our multivariable analysis did
demonstrate that delirium influenced
outcomes even after adjusting for these
medications.89 Thus, the development
of delirium was of clinical relevance
above and beyond that attributed to iatrogenic administration of sedative and
analgesic medications.
Long-term Cognitive Impairment
At the time of hospital discharge, there
was substantial cognitive impairment in
1 out of every 2 survivors tested, which
was significantly more common among
patients who ever developed delirium
compared with those who did not. An
important limitation regarding this observation is that the patients were not
tested for the presence of preexisting (ie,
prior to ICU admission) cognitive impairment (a problem not easily resolved due to the emergent nature of
these patients’ illnesses). However, we
did use a well-validated surrogate assessment of dementia to estimate and adjust for this possible confounder.
While long-term neuropsychological
impairment following mechanical ventilation is now recognized with increasing frequency,42,82 its relationship with
delirium during ICU stay is not known
and deserves further study. Ongoing delirium has been observed by others, including Levkoff et al,32 who found that
the majority of hospitalized elderly patients did not experience complete resolution of delirium symptoms prior to discharge. More recently, McNicoll and
colleagues90 reported that 40% of older
ICU patients had ongoing delirium during the post-ICU period, and Kiely et al91
found that almost 20% of elderly patients had delirium at the time of admission to postacute facilities.
Limitations and Future Directions
Four limitations of this study should be
noted. The first limitation has to do with
the delirium coding and the fact that
study protocol mandated only oncedaily CAM-ICU assessments. Assessing patients more often with the
CAM-ICU will help to improve our
understanding of the phenomenology
of delirium in these patients. In the
year-long implementation study mentioned above,67 nurses adopted delirium monitoring so readily that they
assessed patients more often than the
twice-daily requirement. Our coding of
patients as having or not having delirium for a given day has to do with
the Diagnostic and Statistical Manual of
Mental Disorders, Fourth Edition definition of this disorder. However, it is
important to remember that delirium,
by definition, fluctuates over time. Due
to the fluctuating nature of this disorder, it is considered present until cleared
for 24 hours. It would be feasible to
code the patients in 12-hour intervals.
Even using such a schema, the delirium “episode” will be considered as
ongoing until there are 2 consecutive
12-hour shifts with negative CAMICU assessments. Second, we did not
examine the impact from the broad
range of psychoactive medications
other than sedatives and analgesics, patients’ pharmacological interindividual variability in transport and metabolism of medications, or genetic
predisposition to this form of brain injury. Third, while our cohort did incorporate a broad range of diagnoses in
the medical ICU population, other types
of critically ill patients should be investigated, including patients in trauma
and surgical ICUs as well as those with
baseline neurologic comorbidities.
Lastly, this observational study was
not designed to prove a cause-andeffect relationship between delirium
and clinical outcomes. However, there
are data to support a pathophysiologic
rationale for the brain as a potentiator
(rather than merely a marker) of totalbody injury during critical illness. The
brain responds to systemic infections
and injury with an inflammatory
response of its own that also includes
the production of cytokines, cell
infiltration, and tissue damage.92,93
Reports also indicate that local inflammation in the brain and subsequent
activation of the central nervous system’s immune responses are accompanied by peripheral manifestations of
systemic inflammation, including production of large amounts of peripherally produced tumor necrosis factor ,
interleukin 1, and interferon .92,94-96
Such centrally mediated inflammation
could influence the development or
resolution of multiple organ dysfunction syndrome. Direct injury to the
central nervous system induced by
intracerebral endotoxin has also been
shown to result in loss of the liver’s
ability to metabolize drugs independent of intraperitoneally administered
endotoxin.97-99 Thus, the brain produces its own signaling that likely
influences the overall outcome of the
patient. The exact nature of the signaling between the brain and other systemic organs remains to be elucidated.
In the meantime, this study has demonstrated an important clinical association as well as the need for further
examination, including etiologic and
interventional studies.
CONCLUSIONS
In this single-center observational
study, we found that delirium among
mechanically ventilated patients in the
ICU was associated with higher
6-month mortality and longer lengths
of stay even after adjusting for numerous covariates. This study raises the
question of how diligently delirium
should be monitored in acutely ill
patients, especially considering that
validated instruments can be implemented with a high degree of reproducibility and rates of compliance at the
bedside by those routinely caring for patients in the ICU. Some recent systematic reviews of sedation practices and
their consequences in the ICU have not
mentioned delirium,100,101 while others have suggested that missing delirium in acutely ill patients should be
considered a medical error.25 Future
studies are needed to determine
whether prevention or treatment of delirium would change clinical outcomes including mortality, length of
stay, cost of care, and long-term neuropsychological outcomes among survivors of critical illness.
DELIRIUM IN MECHANICALLY VENTILATED PATIENTS
1760 JAMA, April 14, 2004—Vol 291, No. 14 (Reprinted) ©2004 American Medical Association. All rights reserved.
Downloaded From: https://jamanetwork.com/ on 10/13/2020
Author Affiliations: Department of Medicine, Division of General Internal Medicine and Center for Health
Services Research and the Veterans Affairs Tennessee Valley Geriatric Research, Education and Clinical
Center (GRECC) (Drs Ely, Shintani, Speroff, Gordon,
Inouye, Dittus, and Ms Truman), Division of Allergy/
Pulmonary/Critical Care Medicine (Drs Ely
and Bernard, Ms Truman), Department of Biostatistics (Drs Shintani, Speroff, and Harrell), and Department of Psychiatry (Dr Gordon), Vanderbilt University School of Medicine, Nashville, Tenn; and
Department of Medicine, Yale University School of
Medicine, New Haven, Conn (Dr Inouye)
Author Contributions: Drs Ely, Shintani, Speroff, and
Dittus and Ms Truman had full access to the all of the
data in the study and take responsibility for the integrity of the data and the accuracy of the data analyses.
Study concept and design: Ely, Shintani, Truman,
Gordon, Bernard, Dittus.
Acquisition of data: Ely, Truman.
Analysis and interpretation of data: Ely, Shintani,
Truman, Speroff, Gordon, Harrell, Inouye, Bernard,
Dittus.
Drafting of the manuscript: Ely, Shintani, Truman.
Critical revision of the manuscript for important intellectual content: Ely, Truman, Speroff, Gordon,
Harrell, Inouye, Bernard, Dittus.
Statistical expertise: Ely, Shintani, Speroff, Harrell,
Dittus.
Obtained funding; study supervision: Ely, Bernard,
Dittus.
Administrative, technical, or material support: Ely,
Truman, Gordon, Inouye, Bernard, Dittus.
Funding/Support: Dr Ely is a recipient of the Paul Beeson Faculty Scholar Award from the Alliance for Aging Research and of a K23 from the National Institutes of Health (AG01023-01A1) and the Veterans
Affairs Tennessee Valley Geriatric Research, Education, and Clinical Center. Dr Inouye is a recipient of a
Midcareer Award (K24AG00949) from the National
Institute on Aging and a Donaghue Investigator Award
(DF98-105) from the Patrick and Catherine Weldon
Donaghue Medical Research Foundation.
Role of the Sponsor: The Alliance for Aging Research, National Institutes of Health, National Institute on Aging, and the Patrick and Catherine Weldon Donaghue Medical Research Foundation had no
role in the design or conduct of the study; in the collection, management, analysis, or interpretation of the
data; or in the preparation, review, or approval of the
manuscript.
Acknowledgment: We thank all of the dedicated and
open-minded ICU staff and Meredith Gambrell, who
contributed to this work. In addition, we thank Geeta
Mehta, MD; Derek Angus, MB, MPH; Craig Weinert, MD, MPH; and Jean-Louis Vincent, MD, PhD, who
provided important early feedback on the manuscript.
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Articles
126 www.thelancet.com Vol 371 January 12, 2008
Efficacy and safety of a paired sedation and ventilator
weaning protocol for mechanically ventilated patients in
intensive care (Awakening and Breathing Controlled trial):
a randomised controlled trial
Timothy D Girard, John P Kress, Barry D Fuchs, Jason W W Thomason, William D Schweickert, Brenda T Pun, Darren B Taichman, Jan G Dunn,
Anne S Pohlman, Paul A Kinniry, James C Jackson, Angelo E Canonico, Richard W Light, Ayumi K Shintani, Jennifer L Thompson, Sharon M Gordon,
Jesse B Hall, Robert S Dittus, Gordon R Bernard, E Wesley Ely
Summary
Background Approaches to removal of sedation and mechanical ventilation for critically ill patients vary widely. Our
aim was to assess a protocol that paired spontaneous awakening trials (SATs)—ie, daily interruption of sedatives—
with spontaneous breathing trials (SBTs).
Methods In four tertiary-care hospitals, we randomly assigned 336 mechanically ventilated patients in intensive care
to management with a daily SAT followed by an SBT (intervention group; n=168) or with sedation per usual care plus
a daily SBT (control group; n=168). The primary endpoint was time breathing without assistance. Data were analysed
by intention to treat. This study is registered with ClinicalTrials.gov, number NCT00097630.
Findings One patient in the intervention group did not begin their assigned treatment protocol because of withdrawal
of consent and thus was excluded from analyses and lost to follow-up. Seven patients in the control group discontinued
their assigned protocol, and two of these patients were lost to follow-up. Patients in the intervention group spent
more days breathing without assistance during the 28-day study period than did those in the control group (14·7 days
vs 11·6 days; mean difference 3·1 days, 95% CI 0·7 to 5·6; p=0·02) and were discharged from intensive care (median
time in intensive care 9·1 days vs 12·9 days; p=0·01) and the hospital earlier (median time in the hospital 14·9 days
vs 19·2 days; p=0·04). More patients in the intervention group self-extubated than in the control group (16 patients vs
six patients; 6·0% difference, 95% CI 0·6% to 11·8%; p=0·03), but the number of patients who required reintubation
after self-extubation was similar (five patients vs three patients; 1·2% difference, 95% CI –5·2% to 2·5%; p=0·47), as
were total reintubation rates (13·8% vs 12·5%; 1·3% difference, 95% CI –8·6% to 6·1%; p=0·73). At any instant
during the year after enrolment, patients in the intervention group were less likely to die than were patients in the
control group (HR 0·68, 95% CI 0·50 to 0·92; p=0·01). For every seven patients treated with the intervention, one life
was saved (number needed to treat was 7·4, 95% CI 4·2 to 35·5).
Interpretation Our results suggest that a wake up and breathe protocol that pairs daily spontaneous awakening trials
(ie, interruption of sedatives) with daily spontaneous breathing trials results in better outcomes for mechanically
ventilated patients in intensive care than current standard approaches and should become routine practice.
Introduction
A third of patients in intensive care worldwide are
mechanically ventilated.1 Although instituted to save
lives, mechanical ventilation is nearly universally
accompanied by the administration of large doses of
sedatives;2 together these interventions are associated
with significant morbidity.3–6 Efforts to reduce the
duration of mechanical ventilation in intensive-care
populations via ventilator weaning protocols and sedation
protocols can improve clinical outcomes.7–9 Unfortunately,
only a few patients are managed with these strategies
since there is ongoing disagreement among health-care
professionals with regard to benefits and risks and
because weaning protocols and sedation protocols are
viewed as separate concerns—often handled in a
cumbersome fashion by different members of the
patient-care team (eg, sedation by nurses and ventilator
weaning by respiratory therapists and physicians). Since
the process of discontinuing ventilatory support is
affected by heavy use of sedatives, there is an unmet need
to combine approaches to sedation and ventilator
weaning and to optimise their management.
Numerous randomised trials support the use of
ventilator weaning protocols that include daily
spontaneous breathing trials (SBTs) as their centrepiece;
such protocols are standard of care, having reduced the
duration of mechanical ventilation in diverse populations
of patients with acute respiratory failure.7,10–14 Recent
clinical trials, seeking to identify ways to manage sedation
that might also facilitate earlier extubation, have shown
that both intermittent use of sedatives and spontaneous
awakening trials (SATs)—ie, daily interruption of
sedatives—can reduce the duration of mechanical
ventilation without compromising patient comfort or
Lancet 2008; 371: 126–34
See Comment page 95
Department of Medicine
(A E Canonico MD) and
Saint Thomas Research
Institute (J G Dunn RN), Saint
Thomas Hospital, Nashville,
TN, USA; Department of
Medicine, Division of Allergy,
Pulmonary, and Critical Care
Medicine (T D Girard MD,
J W W Thomason MD,
B T Pun RN, J C Jackson PsyD,
Prof R W Light MD,
Prof G R Bernard MD,
Prof E W Ely MD), Center for
Health Services Research
(T D Girard, J C Jackson,
S M Gordon PsyD,
Prof R S Dittus MD, E W Ely),
and Department of
Biostatistics (A K Shintani PhD,
J L Thompson MPH), Vanderbilt
University School of Medicine,
Nashville, TN, USA; VA
Tennessee Valley Geriatric
Research, Education and
Clinical Center (GRECC), VA
Service, Department of
Veterans Affairs Medical
Center, Tennessee Valley
Healthcare System, TN, USA
(S M Gordon, R S Dittus,
E W Ely); Department of
Medicine, Section of
Pulmonary and Critical Care,
University of Chicago,
Chicago, IL, USA (J P Kress MD,
W D Schweickert MD,
A S Pohlman RN,
Prof J B Hall MD); and
Department of Medicine,
Division of Pulmonary, Allergy
and Critical Care Medicine,
University of Pennsylvania
School of Medicine,
Philadelphia, PA, USA
(B D Fuchs MD,
D B Taichman MD,
P A Kinniry MD)
Articles
www.thelancet.com Vol 371 January 12, 2008 127
safety.8,9,15 The paucity of additional evidence supporting
the routine use of SATs, however, as well as anecdotal
concerns regarding patient safety and agitation, have led
to limited use of this sedation strategy. Whereas some
intensive-care practitioners report only lightly sedating
patients during most of their time on the ventilator, less
than half of practitioners worldwide have implemented
daily interruption of sedatives—eg, 34% in Germany,16
40% in Canada,17 and 40% in the USA.18,19 Also, proponents
of patient-targeted sedation strategies argue that titration
of sedatives according to patients’ needs produces
outcomes equivalent to those resulting from a protocol
that promotes daily SATs.20,21
To test our hypothesis that routine SATs improve
patient outcomes when combined with routine SBTs, we
undertook the Awakening and Breathing Controlled
(ABC) trial, a multicentre, randomised controlled trial in
which we assessed the efficacy and safety of a protocol of
daily SATs paired with SBTs versus a standard SBT
protocol in patients receiving patient-targeted sedation as
part of usual care.
Methods
Patients
We recruited participants at four large medical centres:
Saint Thomas Hospital (Nashville, TN, USA), University
of Chicago Hospitals (Chicago, IL, USA), Hospital of the
University of Pennsylvania (Philadelphia, PA, USA), and
Penn Presbyterian Medical Center (Philadelphia).
Vanderbilt Coordinating Center (Nashville, TN, USA)
supervised the trial; a Vanderbilt investigator was
available 24 h a day to answer questions and respond to
reports of adverse events.
Study personnel screened all patients in intensive care
every day to identify adult patients (≥18 years old) who
required mechanical ventilation for 12 h or more. Patients
receiving full ventilatory support and those whose
support was being weaned were eligible. Patients were
excluded from enrolment for the following reasons:
admission after cardiopulmonary arrest, continuous
mechanical ventilation for 2 weeks or longer, moribund
state (ie, death was perceived to be imminent), withdrawal
of life support, profound neurological deficits (eg, large
stroke or severe dementia), or current enrolment in
another trial.
The institutional review boards at each participating
centre approved the study protocol, and written informed
consent was obtained from participants or their
authorised surrogates.
Procedures
Patients were randomly assigned in a 1:1 manner to
management with paired SAT and SBT protocols (the
intervention group) or usual care, including patienttargeted sedation and an SBT protocol (the control group).
A computer-generated, permuted-block randomisation
scheme was stratified according to study centre by a
Vanderbilt biostatistician. Each assignment was
designated on a tri-folded piece of paper enclosed in a
consecutively numbered, sealed, opaque envelope. After
informed consent was obtained, before data were
collected, the appropriate envelope was opened by local
study personnel.
According to each study centre intensive-care unit’s
usual practice of care, physicians and nurses managed all
patients with patient-targeted sedation, titrating sedative
and analgesic doses to maintain the level of arousal and
comfort deemed clinically appropriate for each patient.
Each intensive-care unit used a validated sedation scale
to monitor depth of sedation. Beginning the morning
after enrolment, intensive-care nurses and respiratory
therapists or study personnel managed patients according
to the study protocols. Figure 1 displays the steps in each
study protocol.
In accordance with the SBT protocol, patients in the
control group were assessed every morning with an SBT
Control
(usual care including SBT)
Intervention
(SAT plus SBT) SAT safety screen
SBT safety screen
Restart sedatives
at half dose
Go to SBT
safety screen
Do SBT Prompt ICU team
Do SAT
Enrolment and
randomisation
Every 24 h
Every 24 h
Every 24 h
Every 24 h
Pass Pass
Pass
Fail
Fail
Fail
Fail
Pass
Figure 1: Treatment protocols
ICU=intensive-care unit. SAT=spontaneous awakening trial. SBT=spontaneous breathing trial.
Correspondence to:
Dr Timothy D Girard, Division of
Allergy, Pulmonary, and Critical
Care Medicine, Center for Health
Services Research, 6th Floor MCE
6110, Vanderbilt University
School of Medicine, Nashville,
TN 37232-8300, USA
timothy.girard@vanderbilt.edu
Articles
128 www.thelancet.com Vol 371 January 12, 2008
safety screen. Patients passed the screen if they had
adequate oxygenation (oxygen saturation [SpO2] ≥88% on
a fraction of inspired oxygen [FIO2] ≤50% and a positive
end-expiratory pressure [PEEP] ≤8 cm H2O), any
spontaneous inspiratory effort in a 5-min period, no
agitation, no evidence of myocardial ischaemia in the
previous 24 h, no significant use of vasopressors or
inotropes (dopamine or dobutamine ≥5 µg/kg per min,
norepinephrine ≥2 µg/min, or vasopressin or milrinone
at any dose), and no evidence of increased intracranial
pressure. Patients who failed the screen were reassessed
the following morning.
Patients who passed underwent an SBT: ventilatory
support was removed, and the patient was allowed to
breathe through either a T-tube circuit or a ventilatory
circuit with continuous positive airway pressure of
5 cm H
2O or pressure support ventilation of less than
7 cm H
2O.22 No change was made in FIO2 or PEEP during
the SBT. Patients failed the SBT if they developed a
respiratory rate of more than 35 or less than eight breaths
per min for 5 min or longer, hypoxaemia (SpO2 <88% for
≥5 min), abrupt changes in mental status, an acute
cardiac arrhythmia, or two or more signs of respiratory
distress, including tachycardia (>130 bpm), bradycardia
(<60 bpm), use of accessory muscles, abdominal paradox,
diaphoresis, or marked dyspnoea. Patients who failed the
SBT were ventilated immediately with the ventilator
settings used before the trial. Patients passed the SBT if
they did not develop any failure criteria during a 120-min
trial. If the SBT was successful, the patients’ physicians
were notified verbally. Study personnel did not participate
in decisions to extubate patients.
In accordance with the SAT protocol, patients in the
intervention group were assessed every morning with an
SAT safety screen. SATs were prescribed by protocol only
for patients in the intervention group, although patients
in the control group were not prevented from undergoing
SATs if the managing clinician felt that they were
indicated. Patients passed the screen unless they were
receiving a sedative infusion for active seizures or alcohol
withdrawal, were receiving escalating sedative doses due
to ongoing agitation, were receiving neuromuscular
blockers, had evidence of active myocardial ischaemia in
the previous 24 h, or had evidence of increased intracranial
pressure. Patients who failed the screen were reassessed
the following morning.
Patients who passed the screen underwent an SAT: all
sedatives and analgesics used for sedation were
interrupted. Analgesics needed for active pain were
continued. Patients were monitored by intensive-care
staff or study personnel for up to 4 h. Patients passed the
SAT if they opened their eyes to verbal stimuli or tolerated
sedative interruption for 4 h or more without exhibiting
failure criteria. Patients failed the SAT if they developed
sustained anxiety, agitation, or pain, a respiratory rate of
more than 35 breaths per min for 5 min or longer, an
SpO2 of less than 88% for 5 min or longer, an acute
cardiac dysrhythmia, or two or more signs of respiratory
distress, including tachycardia, bradycardia, use of
accessory muscles, abdominal paradox, diaphoresis, or
marked dyspnoea. When patients failed an SAT,
intensive-care staff restarted sedatives at half the previous
dose and then titrated the medications to achieve patient
comfort. Patients who passed the SAT were immediately
managed with the SBT protocol.
The primary endpoint was defined a priori as the
number of days patients were breathing without
assistance (ventilator-free days) during the 28-day study
period, which began at the time of enrolment. Patients
who died during the study period were assigned
0 ventilator-free days.23 A period of unassisted breathing
began with extubation (or removal of ventilatory support
for patients with tracheostomies) if the period of
unassisted breathing lasted at least 48 consecutive hours.
Secondary endpoints included time to discharge from
the intensive-care unit and from the hospital, all-cause
28-day mortality, 1-year survival, and duration of coma
and delirium.
Trained study personnel did neurological assessments
every day with two well-validated instruments: level of
1658 patients considered eligible
336 randomised
167 analysed
1 lost to follow-up 2 lost to follow-up
1322 excluded
324 had their surrogate
or physician refuse
306 were unable to
provide consent
243 were admitted post-cardiac arrest
155 had been ventilated ≥2 weeks*
137 were enrolled in another trial
134 were moribund or not committed
to full support
23 had profound neurological deficits
168 allocated to spontaneous
awakening trial plus
spontaneous breathing trial
167 initiated protocol
0 discontinued protocol
1 did not initiate protocol due
to early withdrawal‡
168 analysed
168 allocated to usual care including
spontaneous breathing trial
168 initiated protocol
7 discontinued protocol
3 withdrew from study†
4 transferred for surgery
Figure 2: Trial profile
*Patients who were excluded because of ≥2 weeks of mechanical ventilation were transferred from other
intensive-care units after periods of prolonged mechanical ventilation. †Withdrew from the study: discontinued
the study protocol but allowed study personnel to track study outcomes, which were included in analysis. ‡One
person was excluded from analysis due to study withdrawal by the surrogate immediately after randomisation,
before any data collection.
Articles
www.thelancet.com Vol 371 January 12, 2008 129
arousal was assessed with the Richmond agitation-sedation
scale (RASS),24,25 and delirium was diagnosed with the
confusion assessment method for the intensive-care unit
(CAM-ICU).26–28 Duration of coma was defined as the
number of days in the study period that patients had no
response to verbal or physical stimulation (RASS –5) or
responded to physical or painful stimulation with
movement but without eye opening (RASS –4). Duration
of delirium was defined as the number of days in the
study period during which patients were CAM-ICU
positive and were not comatose.
Patients were followed up from enrolment until death
or discharge, and survivors were followed up for vital
status until 1 year after enrolment using the hospitals’
electronic record systems, telephone calls, in-person
visits, and a commercial version of the Social Security
Death Master File.29
Study personnel monitored patients for adverse events
during the trial and reported all serious, unexpected, and
study-related adverse events to an independent data and
safety monitoring board. Self-extubation and reintubation
were tracked as safety endpoints. The data and safety
monitoring board reviewed two interim analyses of
adverse events after enrolment of 30 and 100 patients. No
interim analysis of efficacy was done.
Statistical analysis
On the basis of a pilot database, we expected a mean
of 12·9 (SD 10·4) ventilator-free days in the control group.
Thus, we calculated that a sample size of 334 patients
would be needed to detect a 25% increase in ventilator-free
days to 16·1 days within the intervention group with
80% power and a two-sided significance level of 0·05.30
Data were analysed with an intention-to-treat approach.
We used χ² tests to compare categorical variables between
the study groups, and the Wilcoxon-Mann-Whitney
two-sample rank-sum test to compare continuous
variables, including the primary endpoint. We also used
bootstrapping with 2000 samples to calculate a
non-parametric 95% CI for the difference in mean
ventilator-free days, because the variable had an unusual
distribution.31 Specifically, we calculated the difference in
mean ventilator-free days in each of 2000 samples
randomly generated from the original data using
resampling with replacement and determined the 95%
CI using the 2·5 and 97·5 percentiles of the results of
these calculations.
To compare the effects of the two treatment protocols
on length of stay in the intensive-care unit and in the
hospital, we used time-to-event analyses. Patient data
were censored at time of death. Medians and IQRs were
obtained with Kaplan-Meier analyses, and the log-rank
test was used to assess the effect of the treatment
protocols. Kaplan-Meier analysis and the log-rank test
were also used to assess the effect of the treatment
protocols on 1-year survival; patients were censored at the
time of last contact alive or at 1 year from enrolment,
whichever was first. The unadjusted hazard ratio (HR) of
death up to 1 year was obtained with Cox proportional
hazards regression. We assessed the proportional hazards
assumption by examining scaled Schoenfeld’s partial
residuals32 for the independent variable included in the
model; no violation of the assumption was detected. To
Intervention group (n=167) Control group (n=168)
Age (years) 60 (48 to 71) 64 (51 to 75)
Sex (female) 77 (46%) 83 (49%)
APACHE II score 26 (21 to 33) 26·5 (21 to 31)
SOFA score 9 (6 to 11) 8 (6 to 11·5)
Diagnosis on admission to intensive care
Sepsis/acute respiratory distress syndrome 79 (47%) 87 (52%)
Myocardial infarction/congestive heart failure 22 (13%) 29 (17%)
Chronic obstructive pulmonary disease/asthma 17 (10%) 12 (7%)
Altered mental status 18 (11%) 12 (7%)
Hepatic or renal failure 9 (5%) 5 (3%)
Malignancy 3 (2%) 2 (1%)
Alcohol withdrawal 1 (1%) 1 (1%)
Other* 18 (11%) 20 (12%)
RASS on first study day –4 (–5 to –2) –4 (–5 to –2)
Sedation before enrolment
Benzodiazepines (mg)† 8 (4 to 34) 10 (2 to 41)
Opiates (µg)‡ 815 (184 to 4380) 850 (142 to 4685)
Propofol (mg) 5102 (2340 to 9720) 3248 (1455 to 7420)
Time from admission to enrolment (days) 2·2 (1·1 to 3·9) 2·2 (1·1 to 3·9)
Data are n (%) or median (IQR). APACHE II=acute physiology and chronic health evaluation II. RASS=Richmond
agitation-sedation scale. SAT=spontaneous awakening trial. SBT=spontaneous breathing trial. SOFA=sequential organ
failure assessment. *Including gastrointestinal bleeding, metabolic disarray, haemoptysis, pulmonary embolism, and
status epilepticus. †Expressed in lorazepam equivalents.34 ‡Expressed in fentanyl equivalents.34
Table 1: Baseline characteristics
Intervention group (n=167) Control group (n=168) p value
Underwent an SAT 150 (90%)* 0 (0%) <0·0001
Sedatives held before any SBT 150 (90%)* 52 (31%) <0·0001
Underwent an SBT 136 (81%)† 146 (87%)† 0·17
Benzodiazepine use post-enrolment
Patients treated 120 (72%) 111 (66%) 0·25
Total dose (mg)‡ 20 (5–93) 39 (8–213) 0·02
Average daily dose (mg)‡ 2 (0–8) 3 (1–17) 0·12
Opiate use post-enrolment
Patients treated 130 (78%) 128 (76%) 0·87
Total dose (µg)§ 2662 (431–9875) 3700 (772–16 306) 0·07
Average daily dose (µg)§ 327 (49–891) 301 (69–1555) 0·28
Propofol use post-enrolment
Patients treated 117 (70%) 115 (69%) 0·88
Total dose (mg) 8950 (3070–17 159) 8380 (2250–18 980) 0·90
Average daily dose (mg) 1230 (431–2070) 987 (373–2158) 0·40
Data are n (%) or median (IQR). SAT=spontaneous awakening trial. SBT=spontaneous breathing trial. *17 patients in
the intervention group never passed an SAT safety screen or underwent an SAT. †22 patients in the control group and
31 in the intervention group never passed an SBT safety screen or underwent an SBT. ‡Expressed in lorazepam
equivalents.34 §Expressed in fentanyl equivalents.34
Table 2: Protocol adherence and sedative use
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130 www.thelancet.com Vol 371 January 12, 2008
assess for an interaction between study centre and
treatment with respect to the primary endpoint, we
included an interaction term in a proportional odds
logistic regression model with ventilator-free days as the
dependent variable. We used R (version 2.4 patched) for
all statistical analyses.33 An independent biostatistician
re-analysed the final dataset and verified all our results.
This study is registered with ClinicalTrials.gov, number
NCT00097630.
Role of the funding source
The sponsors of the study had no role in study design,
data collection, data analysis, data interpretation, or
writing of the manuscript. The corresponding author
had full access to all the data and had final responsibility
for the decision to submit for publication.
Results
1658 patients were considered eligible for enrolment
between October, 2003, and March, 2006. We enrolled and
randomised 336 of these individuals (figure 2). 168 patients
were randomly assigned to each group. Seven (4%) patients
in the control group discontinued the protocol: surrogates
withdrew three patients from the study, and four patients
were transferred to another service not participating in the
trial. No patient in the intervention group discontinued the
protocol; a surrogate withdrew one patient before protocol
initiation or any data collection, and this patient was
excluded from analyses.
The two groups were similar at baseline (table 1). On
day 1, 87 (52%) patients in the control group and 94 (56%)
patients in the intervention group were comatose. Before
enrolment, the two groups were treated with similar
doses of benzodiazepines and opiates, although patients
in the intervention group received more propofol
(p=0·02). Propofol dose before enrolment, however, was
not associated with study outcomes (data not shown).
Intervention group (n=167) Control group (n=168) p value
Ventilator-free days*
Mean 14·7 (0·9) 11·6 (0·9) 0·02
Median 20·0 (0 to 26·0) 8·1 (0 to 24·3)
Time to discharge (days)
From intensive care 9·1 (5·1 to 17·8) 12·9 (6·0 to 24·2) 0·01
From hospital 14·9 (8·9 to 26·8) 19·2 (10·3 to NA)† 0·04
28-day mortality 47 (28%) 58 (35%) 0·21
1-year mortality 74 (44%) 97 (58%) 0·01
Duration of brain dysfunction (days)
Coma 2 (0 to 4) 3 (1 to 7) 0·002
Delirium 2 (0 to 5) 2 (0 to 6) 0·50
RASS at first successful SBT –1 (–3 to 0) –2·5 (–4 to 0) 0·0001
Complications
Any self-extubation 16 (10%) 6 (4%) 0·03
Self-extubation requiring
reintubation‡
5 (3%) 3 (2%) 0·47
Reintubation‡ 23 (14%) 21 (13%) 0·73
Tracheostomy 21 (13%) 34 (20%) 0·06
Data are mean (SD), n (%), or median (IQR). RASS=Richmond agitation-sedation scale. SAT=spontaneous awakening
trial. SBT=spontaneous breathing trial. *Ventilator-free days from study day 1 to 28. †Greater than 25% of patients in
the SBT group remained in the hospital at study day 28. ‡Reintubation within 48 hours of extubation.
Table 3: Main outcomes
A B C
0
0
20
7 14
Days after randomisation
Days after randomisation
21 28
0 7 14 21 28
167 57 24 9 3
167 89 35 20 10
168
SAT plus SBT
Patients at risk
Usual care plus SBT
SAT plus SBT
Patients at risk
Usual care plus SBT
SAT plus SBT
Patients at risk
Usual care plus SBT
68 30 18 8
165 102 52 33 18
0 7 14
Days after randomisation
21 28
167 126 64 34 24
168 130 72 47 30
Patients Events
167 99
168 81
Patients Events
167 120
168 114
Patients Events
167 117
168 99
40
60
80
100
Patients successfully extubated (%)
0
20
40
60
80
100
0
20
40
60
80
100
Patients discharged from hospital (%) Patients discharged from intensive care (%)
SAT plus SBT
Usual care plus SBT
Figure 3: Probability of successful extubation (A), discharge from intensive
care (B), and hospital discharge (C) during the first 28 days after
randomisation
Events indicate total number of successful extubations (A), discharges from
intensive care (B), and discharges from the hospital (C) in each treatment group
during the 28 days from enrolment.
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150 (90%) patients in the intervention group passed an
SAT safety screen; these patients underwent 895 SATs
(table 2). Analgesics were continued for pain
during 132 (15%) of these SATs. Clinicians discontinued
the sedatives administered to 52 (31%) patients in the
control group before at least one SBT (table 2). The
number of patients in each group treated with
benzodiazepines, opiates, or propofol was similar, as was
the cumulative dose of propofol (table 2). The cumulative
benzodiazepine dose was higher in the control group than
in the intervention group. Only 45 (27%) patients in the
control group and 31 (18%) patients in the intervention
group received haloperidol (p=0·07).
Patients in the intervention group spent more days
breathing without assistance than those in the control
group (3·1 mean ventilator-free days difference, 95% CI
0·7–5·6; p=0·02; table 3). Additionally, the intervention
protocol resulted in discharge about 4 days earlier from
both intensive care and from the hospital (table 3 and
figure 3). There was no significant interaction between
study centre and treatment with respect to the number of
ventilator-free days (data not shown).
The duration of coma was significantly shorter in the
intervention group than in the control group, whereas
the duration of delirium was similar between the two
groups (table 3). Of the assessable patients, delirium
occurred in 124 (74%) in the intervention group and
119 (71%) in the control group (p=0·66).
Patients in the two treatment groups progressed to the
point of passing an SBT at the same rate (median
number of days to first passed SBT 3·8 [IQR 1·1–14·0]
days in the intervention group vs 3·9 [1·0–11·8] days in
the control group; p=0·49). Patients in the intervention
group, however, were more alert than were those in the
control group on the day they first passed an SBT safety
screen (median RASS –2 [IQR –3 to 0] vs –3 [–4 to –1];
p=0·0003) and an SBT (–1 [–3 to 0] vs –2·5 [–4 to 0];
p=0·0001). 59 (54%) of the 109 patients in the
intervention group who ever passed an SBT were
extubated on the day they first passed an SBT compared
with 49 (40%) of the 124 patients in the control group
(14·6% difference, 95% CI 1·0–26·0; p=0·03).
Analysis of 1-year survival showed that, at any instant
during the year after enrolment, patients managed with
the SAT plus SBT strategy were 32% less likely to die
than were patients in the control group (HR 0·68, 95% CI
0·50 to 0·92; p=0·01; figure 4). For every seven patients
treated with the SAT plus SBT protocol, one life was
saved (number needed to treat 7·4, 95% CI 4·2–35·5).
Tracheostomies, which no patient had at enrolment,
were placed in 21 (13%) patients in the intervention group
and in 34 (20%) of those in the control group (absolute
risk reduction 7·6%, 95% CI –0·3% to 15·6%; p=0·06).
Median time to tracheostomy placement was similar in
the two groups (12·7 [IQR 5·9–13·4] days in the
intervention group vs 12·9 [8·0–18·1] days in the control
group; p=0·32).
More patients in the intervention group self-extubated
than in the control group (6·0% difference, 95% CI
0·6–11·8; p=0·03; table 3). Only five individuals in the
intervention group self-extubated, however, during or
within 12 h of an SAT. Also, five patients in the intervention
group required reintubation within 48 h of self-extubation,
Figure 4: Survival at 1 year
Events indicate the number of deaths in each group in the year after enrolment.
Days after randomisation
SAT plus SBT 167 110 96 92 91
Patients at risk
Usual care plus SBT 167 85 73 67 66
86
65
76
59
0 60 120 240 300 180 360
Patients Events
167 74
168 97
0
20
40
60
80
100
Patients alive (%)
SAT plus SBT
Usual care plus SBT
Intervention
group
Control
group
p value
SAT
Total 895 0
Passed 837 (94%) NA NA
Opened eyes to verbal stimuli 731 (82%) NA NA
Tolerated SAT for ≥4 h 106 (11%) NA NA
Failed* 58 (7%) NA NA
Anxiety, agitation, or pain 42 (5%) NA NA
Signs of respiratory distress 25 (3%) NA NA
Tachypnoea 20 (2%) NA NA
Hypoxaemia 12 (1%) NA NA
Dysrhythmia 1 (0%) NA NA
SBT
Total 603 948
Passed 319 (53%) 492 (52%) 0·70
Failed* 284 (47%) 456 (48%) ..
Tachypnoea 221 (37%) 351 (37%) 0·75
Signs of respiratory distress 125 (37%) 217 (23%) 0·27
Hypoxaemia 33 (6%) 51 (5%) 0·98
Abrupt change in mental status 13 (2%) 17 (2%) 0·64
Bradypnoea 8 (1%) 19 (2%) 0·31
Dysrhythmia 15 (3%) 9 (1%) 0·02
Data are n (%). NA=not applicable. SAT=spontaneous awakening trial.
SBT=spontaneous breathing trial. *Some patients had more than one reason for
failure.
Table 4: Results of the spontaneous awakening trials and spontaneous
breathing trials
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132 www.thelancet.com Vol 371 January 12, 2008
compared with three patients in the control group
(1·2% difference, 95% CI –5·2% to 2·5%; p=0·47). The
overall rate of reintubation was similar between the two
groups (1·3% difference, 95% CI –8·6% to 6·1%;
p=0·73).
Patients in the intervention group failed 201 (18%) of
the 1140 SAT safety screens that were done, most often
due to agitation, which was noted during 151 (13%) safety
screens. An SAT was done after 895 (95%) of the 939 SAT
safety screens that were passed. Patients passed 837 (94%) of
these SATs. Patients who failed SATs most often did so
due to anxiety, agitation, or pain, which occurred only
during 42 (5%) SATs (table 4).
Two-thirds of all SBT safety screens were passed (647
[66%] of 983 screens done in the intervention group
vs 1036 [65%] of 1599 in the control group; p=0·59), and
half of all SBTs were passed by patients in both groups
(table 4). The most common reasons for SBT failure in
both groups were tachypnoea and other signs of
respiratory distress. Patients failed a small number of
SBTs in both groups due to acute dysrhythmias; this
occurred more frequently in patients in the intervention
group (1·6% difference, 95% CI 0·3–3·2; p=0·02). None
of these dysrhythmias were deemed to be serious, since
none resulted in clinically adverse sequelae other than
termination of the SBT.
Discussion
Our results show that a paired sedation and ventilator
weaning protocol consisting of daily SATs plus SBTs
resulted in patients spending more time off mechanical
ventilation, less time in coma, and less time in intensive
care and the hospital, and the protocol improved 1-year
survival compared with usual care. This wake up and
breathe strategy was effective and was associated with
few adverse events in a diverse population in intensive
care in both community and university hospitals.
Respiratory failure and mechanical ventilation frequently
result in anxiety and pain.35,36 Thus, clinicians use sedatives
and analgesics to alleviate patient discomfort, decrease
oxygen consumption, facilitate nursing care, and ensure
patient safety.37 These medications, however, are associated
with adverse effects, including oversedation,38 delirium,5
and prolongation of mechanical ventilation.6 The most
appropriate pattern and dose of administration is often
difficult to determine, and many intensive-care practitioners
have the perception that their patients are not oversedated,
even though observational studies in Europe2 and the
USA38 found that nearly half of intensive-care patients are
deeply sedated and unarousable.
In 2000, Kress and colleagues9 reported that a protocol
of daily SATs reduced duration of mechanical ventilation
and length of stay in intensive care. This study showed
that SATs are safe; self-extubation,9 intensive-care-related
complications,39 myocardial ischaemia,40 and posttraumatric stress disorder41 did not occur more
frequently in patients managed with daily SATs than in
those managed without SATs. Kress and colleagues’
trial was limited, however, being a single-centre trial
that did not mandate daily SBTs. Because of the absence
of a multicentre trial supporting the efficacy of SATs
and persistent concerns regarding the safety of this
sedation strategy, most intensive-care patients are not
managed with routine SATs; intensive-care practitioners
often opt instead for individualised, patient-targeted
sedation.16–19
In the current investigation, daily SATs reduced the
likelihood of oversedation so that patients were
neurologically ready for extubation once their respiratory
failure had improved. Patients in the intervention group
were more alert than were patients in the control group
on first passing both an SBT safety screen and SBT. Thus,
these patients were more likely to be extubated shortly
after first passing a breathing trial. Accompanying this
earlier neurological recovery in the intervention group
was a higher rate of self-extubation. Since these events
did not result in more reintubations, the patients were
apparently ready to come off the ventilator earlier than
the intensive-care team had expected. Self-extubation
within the intervention group did not substantially affect
the results of the trial; after excluding all patients who
self-extubated, the difference in ventilator-free days
between treatment groups remained significant (data not
shown).
In both the current trial and that by Kress and
colleagues,9 patients managed with daily SATs were
treated with less total benzodiazepine medication than
were patients who did not undergo SATs, a difference in
drug dose that was considerable over the entire stay in
intensive care but small on any given day of treatment.
Total propofol doses, however, were similar between
groups in both studies, suggesting that a reduction in
drug dose was not the sole factor leading to improved
outcomes. The pattern of administration is apparently an
important factor; the interruption of a sedative infusion—
during the wake up component of the SAT plus SBT
protocol—probably facilitates a decline in plasma drug
concentration and reduces the likelihood of drug
accumulation.
Major strengths of the ABC trial included the parallel
format of the SAT plus SBT protocol, which includes
specific safety screens and failure criteria, making it easy
to replicate; participation by intensive-care staff, including
nurses and respiratory therapists; use of patient-target
sedation and an SBT protocol in both groups; assessment
of coma and delirium with validated and reliable
instruments; and a multicentre study design with
enrolment in both open and closed intensive-care units.
Also, the liberal SBT safety screen criteria used (FIO2 ≤50%
and PEEP ≤8 cm H
2O) facilitated the observation that
many patients might be ready to breathe without assistance
sooner than previously expected. Likewise, the simple
criteria for passing an SAT were part of an SAT plus SBT
protocol that was easy to implement yet effective. The
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www.thelancet.com Vol 371 January 12, 2008 133
format of the SAT plus SBT protocol (ie, linkage of SATs
and SBTs) should facilitate its use, making the typical
practice of devising and implementing sedation protocols
and ventilator weaning protocols as independent constructs unnecessary, thereby avoiding emphasis on one or
the other depending on local strengths and personnel.
Lastly, the patients and critical care communities that
participated in the ABC trial were heterogeneous, greatly
enhancing the generalisability of these findings.
Several limitations should be noted. Research personnel
and intensive-care staff were not blinded to patient
allocation because blinding is not possible in a study of
this kind. Knowledge of group allocation can bias study
results, so we randomly assigned patients to treatment
groups, managed patients in both groups with formal
protocols, followed well-defined outcomes, and used a
statistical analysis plan designed a priori. Although each
participating intensive-care unit used patient-targeted
sedation strategies, we did not mandate the use of a
specific sedation protocol in the control group or particular
short-acting or long-acting sedatives in either group but—
to compare the SAT plus SBT protocol with usual care—
allowed clinicians to use their judgment with regard to the
most appropriate medications and levels of sedation for
individual patients. A detailed description of sedation
practices used to manage patients in the control group is
therefore not available except that sedative doses were
recorded. By chance, patients in the intervention group
received more propofol before enrolment than did those
in the control group, whereas benzodiazepine and opiate
doses were similar between groups. Although increased
propofol doses before enrolment in the intervention group
might have biased the results against showing improved
outcomes in the intervention group, our analysis indicated
that pre-enrolment propofol dose was not associated with
study outcomes. Because we did not track the time spent
executing the SAT plus SBT protocol, we cannot report the
amount of personnel time needed to implement this
intervention. The protocol was designed to be done by
bedside nurses and respiratory therapists during the
course of routine care, and it was implemented largely by
clinical staff during the trial. Lastly, we did not enrol
surgical patients because of their potential need for
continuous analgesia; thus, the wake up and breathe
protocol should be tested separately in a surgical
intensive-care population.
At any instant during the year following enrolment,
patients managed with the wake up and breathe protocol
were about a third less likely to die than were patients in
the control group. Patients with more severe critical
illness, who tend to have prolonged stays in intensive
care—ie, those who accrue the largest cumulative
exposure to sedative medications—could receive the
greatest benefit from management with the SAT plus
SBT strategy, but we are limited in our ability to draw
such conclusions since no data exist to elucidate the
mechanism of the observed survival benefit.
In conclusion, our results suggest that use of a so-called
wake up and breathe protocol that pairs daily spontaneous
awakening trials (ie, interruption of sedatives) with daily
spontaneous breathing trials for the management of
mechanically ventilated patients in intensive care results
in better outcomes than current standard approaches and
should become routine practice.
Contributors
JWWT and EWE conceived the trial. TDG, JPK, BDF, JWWT, BTP, DBT,
JCJ, AKS, SMG, JBH, RSD, GRB, and EWE participated in study design.
TDG, JPK, BDF, JWWT, WDS, BTP, DBT, JGD, ASP, PAK, JCJ, AEC,
RWL, and EWE recruited patients and collected data, and TDG, AKS,
JLT, and EWE analysed the data. All authors participated in
interpretation of results. TDG drafted the manuscript, and all authors
contributed to the critical review and revision of the manuscript. All
authors have seen and approved the final version of the manuscript.
Conflict of interest statement
EWE has received grant support or honoraria from Pfizer, Hospira, Lilly,
and Aspect Medical. All other authors declare that they have no conflict
of interest.
Acknowledgments
We thank the Saint Thomas Foundation (Nashville, TN, USA), the
National Institutes of Health (AG001023, HL007123, and RR024975), the
Veterans Affairs Tennessee Valley Geriatric Research, Education, and
Clinical Center (GRECC), the Hartford Geriatrics Health Outcomes
Research Scholars Award Program, and the Vanderbilt Physician
Scientist Development Program for financial support. We thank the
ABC trial study personnel at University of Chicago Hospitals
(Joseph Levitt, Celerina Nigos, Stacey Sandbo, and Ajeet Vinayak),
Hospital of the University of Pennsylvania (Megan Carr-Lettieri,
Joan Hoch, and Edward Tollok), and Penn Presbyterian Medical Center
(Hernan Alvarado Jr, Sandra Kaplan, William E Laury, and
Jennifer Shin); the members of the data and safety monitoring board
(Daniel W Byrne, Brian W Christman, and John H Newman);
Frank E Harrell Jr for his expert statistical guidance; Daniel W Byrne for
independently verifying all statistical results; and the staff of the
intensive care units at Saint Thomas Hospital, the University of Chicago
Hospitals, the Hospital of the University of Pennsylvania, and Penn
Presbyterian Medical Center for their invaluable participation in the
ABC trial.
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