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CAPD - A Valid, Rapid, Observational Tool for Screening Delirium in the PICU

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Pediatric Critical Care
656 www.ccmjournal.org March 2014 • Volume 42 • Number 3
Objective: To determine validity and reliability of the Cornell Assess-
ment of Pediatric Delirium, a rapid observational screening tool.
Design: Double-blinded assessments were performed with the
Cornell Assessment of Pediatric Delirium completed by nursing
staff in the PICU. These ratings were compared with an assess-
ment by consultation liaison child psychiatrist using the Diagnostic
and Statistical Manual IV criteria as the “gold standard” for diagno-
sis of delirium. An initial series of duplicate Cornell Assessment of
Pediatric Delirium assessments were performed in blinded fashion
to assess interrater reliability. Nurses recorded the time required
to complete the Cornell Assessment of Pediatric Delirium screen.
Setting: Twenty-bed general PICU in a major urban academic
medical center over a 10-week period, March–May 2012.
Patients: One hundred eleven patients stratified over ages rang-
ing from 0 to 21 years and across developmental levels.
Intervention: Two hundred forty-eight paired assessments
Measurements and Main Results: The Cornell Assessment of
Pediatric Delirium had an overall sensitivity of 94.1% (95% CI,
83.8–98.8%) and specificity of 79.2% (95% CI, 73.5–84.9%).
Overall Cronbach’s α of 0.90 was observed, with a range of
0.87–0.90 for each of the eight items, indicating good internal
consistency. A scoring cut point of 9 demonstrated good inter-
rater reliability of the Cornell Assessment of Pediatric Delirium
when comparing results of the screen between nurses (overall
κ = 0.94; item range κ = 0.68–0.78). In patients without sig-
nificant developmental delay, sensitivity was 92.0% (95% CI,
85.7–98.3%) and specificity was 86.5% (95% CI, 75.4–97.6%).
In developmentally delayed children, the Cornell Assessment of
Pediatric Delirium showed decreased specificity of 51.2% (95%
CI, 24.7–77.8%) but sensitivity remained high at 96.2% (95% CI,
86.5–100%). The Cornell Assessment of Pediatric Delirium takes
less than 2 minutes to complete.
Conclusions: With an overall prevalence rate of 20.6% in our study
population, delirium is a common problem in pediatric critical care.
The Cornell Assessment of Pediatric Delirium is a valid, rapid, obser-
vational nursing screen that is urgently needed for the detection of
delirium in PICU settings. (Crit Care Med 2014; 42:656–663)
Key Words: Cornell Assessment of Pediatric Delirium; critical
care; delirium; pediatric critical care; pediatrics; screening tool
elirium is acute cerebral dysfunction caused by systemic
illness or the effects of treatment (1). There is an urgent
need for pediatric-specific research into delirium (2–
5). Recognition of delirium in children in the PICU has been
suboptimal; therefore, the impact of delirium and therapeutic
interventions have been understudied (6–9). Pediatric delirium
is associated with increased length of PICU stay (10), posttrau-
matic symptoms (11), and possible neurocognitive dysfunction
Copyright © 2013 by the Society of Critical Care Medicine and Lippincott
Williams & Wilkins
DOI: 10.1097/CCM.0b013e3182a66b76
*See also p. 751.
Pediatric Critical Care Medicine, Weill Cornell Medical College, New
York, NY.
Department of Child Psychiatry, Weill Cornell Medical College, New York, NY.
Department of Pediatrics and Psychiatry, Memorial Sloan-Kettering Can-
cer Center, New York, NY.
Department of Pediatrics, NY Presbyterian Hospital, New York, NY.
Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering
Cancer Center, New York, NY.
Department of Psychiatry, NY Presbyterian Hospital, New York, NY.
Jefferson Medical College, Philadelphia, PA.
Department of Public Health, Weill Cornell Medical College, New York, NY.
This work was performed at Weill Cornell Medical College/NY Presbyte-
rian Hospital.
Drs. Traube and Silver contributed equally to this article.
Drs. Traube and Greenwald received support for travel from Weill Cornell
Medical College. Dr. Greenwald received support for travel from the Soci-
ety of Critical Care Medicine. Dr. Greenwald consults for various law firms.
The remaining authors have disclosed that they do not have any potential
conflicts of interest.
For information regarding this article, E-mail: chr9008@med.cornell.edu
Cornell Assessment of Pediatric Delirium: A Valid,
Rapid, Observational Tool for Screening Delirium
in the PICU*
Chani Traube, MD
; Gabrielle Silver, MD
; Julia Kearney, MD
; Anita Patel, MD
Thomas M. Atkinson, PhD
; Margaret J. Yoon, MD
; Sari Halpert, MD
; Julie Augenstein, MD
Laura E. Sickles, BA
; Chunshan Li, MA
; Bruce Greenwald, MD

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Critical Care Medicine www.ccmjournal.org 657
in children after discharge (12, 13). A growing body of literature
in adult critical care describes delirium as exacerbated by the use
of various sedative medications and has identified risk factors
that predispose to delirium (5, 14–17). An impediment to the
progress of pediatric delirium research has been the absence of
an easily administered and widely applicable screening tool.
The clinical diagnosis of delirium in children more than
12 months old, based on Diagnostic and Statistical Manual IV
(DSM-IV) criteria, is considered valid with a presentation that
is similar to adults (14, 18–24). Delirium in infants less than
12 months old has not been systematically studied, but clini-
cal reports suggest that with developmental considerations in
diagnosis, infants present with delirium with detectable deficits
in awareness, cognition, and arousal (21, 25, 26). Subtypes of
delirium, including hyperactive, hypoactive, and mixed type,
are considered valid in children as well as adults (27).
The limitations of existing tools in the PICU popula-
tion, including the Delirium Rating Scale (DRS), Pediatric
Confusion Assessment Method for the ICU (pCAM-ICU),
and the Pediatric Anesthesia Emergence Delirium (PAED)
screen, have been discussed (6, 28–32). In brief, the DRS (33)
was designed for psychiatrists’ use and is labor intensive. The
pCAM-ICU (34) is an elegant cognitive tool but requires
patient cooperation, is restricted to children more than 5
years old, limited in patients with developmental delay, and
requires extensive nurse training. The PAED (35) designed, for
immediate postoperative use by anesthesiologists, selects for
the hyperactive subtype of delirium. An ideal screening tool
would detect all types of delirium (hyperactive, hypoactive,
and mixed), in patients of all ages and developmental levels.
Our primary objective was to describe the development of
the Cornell Assessment of Pediatric Delirium (CAPD) and test
its validity and reliability as a screening tool. In addition, we
explored the instrument’s performance in subgroups defined
by developmental delay, gender, respiratory support, prematu-
rity, and severity of illness.
Phase I: Development of the CAPD
The CAPD is an adaptation of the PAED. As the original PAED
was designed to detect transient emergence delirium following
anesthesia, it selects for patients with a hyperactive, agitated
delirium subtype and would be incomplete for assessing the
PICU population. Therefore, we added two elements (ques-
tions 7 and 8, Fig. 1) to improve the detection of hypoactive
and mixed-type delirium. We changed the scale items from
statements to questions and renamed the tool to reflect the
comprehensive nature of the assessment. An initial pilot study
showed feasibility for use as a rapid nursing screen (28).
Based on the pilot study, we made additional changes. To
better capture a fluctuating course of delirium over a nurse’s
shift, response options were changed from the original (not at
all/just a little/quite a bit/very much/extremely) to the format
always". To better reflect the
DSM-IV criteria for delirium,
and detect alteration in cogni-
tive functioning, we added a
third novel item (question 4,
Fig. 1), to assess the ability to
communicate needs and wants.
Content validity of the revised
CAPD (Fig. 1) was evaluated
by experts in the fields of pedi-
atric critical care, development,
delirium, and psychometrics.
Anchor Points. Orientation,
arousal, and appropriate cogni-
tion (which are all affected in
delirium) are difficult to assess in
young children and even harder
to measure in infants. Because of
concerns about accurate screen-
ing in children under 2 years old,
developmental anchor points
were delineated. Based on clas-
sic texts and established scales of
child development, each anchor
point characterizes the normal
developing child for each item
on the CAPD (Table 1). Anchor
points describe the associated Figure 1. Cornell Assessment of Pediatric Delirium revised. RASS = Richmond Agitation and Sedation Scale.

Traube et al
658 www.ccmjournal.org March 2014 • Volume 42 • Number 3
observable behaviors in a PICU setting (rather than in the child’s
natural environment) (36, 37). After piloting with nurses for
clarity of language and concepts, a short training session was
done and anchor point charts were provided for reference to the
approximately 100 critical care nurses who participated.
Criterion Standard. The “gold standard” diagnosis for pedi-
atric delirium is an assessment by a child psychiatrist using the
DSM-IV criteria that require acute onset, fluctuating course,
and disturbance of awareness and cognition (1). A short train-
ing session for the six psychiatric evaluators was completed.
Phase II: Assessing Psychometric Properties
Study Design. The study took place in a 20-bed general PICU
in a major urban academic medical center over a 10-week
period from March to May 2012.
All patients in the PICU on a given study day were eli-
gible if there was a parent or guardian available to provide
informed consent. The only exclusion criterion was a sedation
score of less than –3 (deeply sedated or unarousable), using
the Richmond Agitation and Sedation Scale (RASS) (38, 39).
Demographic and clinical data were collected on each subject.
Reliability Testing. After informed consent was obtained, a
set of paired, double-blinded assessments was performed. The
bedside nurse completed the CAPD as a paper checklist. Sub-
sequently, the psychiatrist conducted a diagnostic interview
and examination. If a child was diagnosed with delirium by the
psychiatrist, this was reported to the medical team caring for
the child so that appropriate interventions could be taken. If
the subject was still present in the PICU on the next study day,
TABLE 1. Selected Cornell Assessment of Pediatric Delirium Developmental Anchor Points
and Diagnostic and Statistical Manual IV Delirium Domain Correlates
Cornell Assessment of
Pediatric Delirium Item
Diagnostic and
Statistical Manual
Delirium Domains
Selected Normal Developmental Anchor Points
Age (8 wk) Age (1 yr)
1. Does the child make eye
contact with the caregiver?
Consciousness Follows moving object past
midline, regards hand holding
object, focused attention
Holds gaze. Prefers primary parent.
Looks at speaker
2. Are the child’s actions
Cognition Symmetric movements, will
passively grasp handed object
Reaches and manipulates objects, tries
to change position, if mobile may try
to get up
3. Is the child aware of his/her
Facial brightening or smile in
response to nodding head,
frown to bell, coos
Prefers primary parent, upset when
separated from preferred caregivers.
Comforted by familiar objects (i.e.,
blanket or stuffed animal)
4. Does the child communicate
needs and wants?
Consciousness Cries when hungry or
Uses single words or signs
Psychomotor activity
5. Is the child restless? Cognition
Psychomotor activity
No sustained awake alert state No sustained calm state
6. Is the child inconsolable? Orientation
Not soothed by usual comforting
actions, for example, rocking
and singing
Not soothed by usual comforting
actions, for example, singing, holding,
talking, and reading
7. Is the child underactive—very
little movement while
Little if any purposive grasping,
control of head and arm
movements, such as pushing
things that are noxious away
Little if any play, efforts to sit up, pull up,
and if mobile crawl or walk around
8. Does it take the child a
long time to respond to
Consciousness Not cooing, smiling, or
focusing gaze in response to
Not following simple directions. If
verbal, not engaging in simple
dialogue with words or jargon
Psychomotor activity
Anchor points were developed for newborn and 4 wk, 6 wk, 8 wk, 28 wk, 1 yr, and 2 yr olds.
Figure 2. Subject recruitment flow. RASS = Richmond Agitation and
Sedation Scale.

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the paired assessments were repeated, up to a predetermined
maximum of 5 per subject. When the assessments were com-
pleted, CAPD screening results were compared with the psy-
chiatric diagnosis and the interrater agreement was computed.
The first 70 CAPD screens were each performed by two
blinded nurses. Interrater reliability was quantified using
Cohen’s κ coefficient, whereas internal consistency of the eight
items was evaluated by Cronbach’s α.
Validity Testing. The enrollment goal was a minimum of
100 subjects overall and 250 encounters. The sample size calcu-
lation was based on an assumed prevalence of pediatric delir-
ium of 15%, sensitivity of 0.90 and α level of 0.05, and inclusion
of subjects from all age groups and children with and without
developmental delay. The definition of “significant clinical
developmental delay” was based on clinical assessment and/
or parental report of developmental problems that affected the
child’s behavior or ability to communicate. Children with mild
or transient history of developmental problems (i.e., needing
occupational therapy or motor or speech delays) but who did
not have current abnormalities in communication or behavior
were classified as normal for the purpose of the study.
The receiver operating characteristic (ROC) analysis was
performed to find the optimal CAPD cutoff score; subse-
quently, sensitivity and specificity were calculated for the over-
all sample. In addition, in order to explore CAPD performance
in subgroups, validity measures were described by age groups,
developmental delay status, gender, respiratory support, pre-
maturity, and illness severity. All CIs have been adjusted for
the possible correlation between observations within subjects
using a ratio estimator method (40, 41).
The study was approved by the Institutional Review Board
of Weill Cornell Medical College.
Average PICU census on study days was 16. Approximately
68% of patients were eligible. Seventeen percent of patients
had a RASS of less than –3. Fifteen percent of patients did not
have a parent available to provide consent or were off the unit
at the time of the study. Consent rate was 88.5% of eligible
patients. In total, 111 subjects were enrolled (Fig. 2).
Subject Characteristics
Admitting diagnoses are shown in Table 2. Sixty-seven subjects
(60%) were male. Twenty-two subjects (20%) had significant
developmental delay. Fifty-three subjects (48%) were receiving
supplemental oxygen, 30 subjects (27%) were on noninvasive
positive pressure ventilation, and 19 subjects (17%) were on
invasive mechanical ventilation. Sixty assessments (24% of
encounters) were completed with children who were intubated.
Criterion Standard
Interrater reliability of the initial 38 psychiatric evaluations
performed by two blinded psychiatrists was excellent (Cohen’s
κ = 0.95; 95% CI, 0.79–1.00), consistent with our expectation
for the criterion standard.
Prevalence of Delirium
Prevalence of delirium by psychiatric assessment was 20.6%
(n = 51). Among children with multiple encounters who received
a diagnosis of delirium at least once (n = 21), 89.5% showed a
TABLE 2. Demographic Details and Admission
Diagnoses of Subjects (n = Total 111)
Characteristic n (%)
Male 67 (60)
Female 44 (40)
0–24 mo 37 (33)
2–5 yr 24 (22)
6–12 yr 25 (22.5)
13–21 yr 25 (22.5)
Developmental delay
No 89 (80)
Ye s 22 (20)
Respiratory support
Oxygen 53 (48)
Noninvasive mechanical
30 (27)
Ventilator 19 (17)
None 9 (8)
Ye s 22 (20)
No 89 (80)
Cardiac 12
Genetic disorder 13
Hematologic/oncologic 19
Infectious/inflammatory 38
Metabolic 11
Neurologic 16
Neurosurgical 30
Respiratory insufficiency 50
Postoperative/other 56
Pediatric Index of Mortality II, %
Overall Median = 3.00 (range, 0–57)
Pediatric delirium Median = 4.05 (range, 0–57)
No pediatric delirium Median = 2.00 (range, 0–57)
See text for description of categories.
Including all primary and secondary diagnoses.

Traube et al
660 www.ccmjournal.org March 2014 • Volume 42 • Number 3
fluctuating course. Developmental delay was a significant risk
factor for delirium as children with developmental delay were
diagnosed with delirium almost three times as often as children
without delay (38.8% vs 13.9% of assessments, respectively).
Prevalence of delirium in the “sicker” patients, as measured by
Pediatric Index of Mortality II (PIM2) score above the median,
was notably higher than in those children with PIM2 score below
the median (29.7% vs 12.3%). This is consistent with prior pedi-
atric delirium research (42). The lowest delirium prevalence was
observed in children more than 13 years old (3.6%) and in chil-
dren not on respiratory support (5.2%).
CAPD Performance
Cut point analysis showed the best sensitivity and specificity
for the screening instrument (prioritizing high sensitivity) at
a total CAPD score of 9 or greater. Sensitivity was 94.1% (95%
CI, 83.8–98.8%) and specificity 79.2% (95% CI, 73.5–84.9%).
At a cut point of greater than or equal to 9, there were three
false-negative CAPD screens (Table 3) and 41 false-positive
screens. Concordance between CAPD and psychiatric diagno-
sis was 82.3% (r = 0.62). Nurses’ CAPD interrater reliability
was also highest at a cut point of 9, with κ = 0.94. κ ranged
from 0.68 to 0.78 for each of the eight CAPD items.
CAPD performance compared with the “gold standard”
psychiatric diagnosis by subgroups is reported in Table 4. In
patients without significant developmental delay (73% of our
population), the CAPD had both high sensitivity and specificity
(92%; CI, 85.7–98.3% and 86.5%; CI, 75.4–97.6%, respectively).
In children with developmental delay, the screen remained quite
sensitive (96.2%; CI, 86.5–100%) but demonstrated a loss of
specificity (51.2%; CI, 24.7–77.8%). Despite this, ROC analysis
of the CAPD in children with developmental delay had an area
under the curve of 0.86 (Fig. 3), demonstrating its applicability
in this hard-to-assess population. The negative predictive value
remained quite high at 98.5% (95% CI, 94.8–99.8%).
The CAPD screen performed similarly in all age groups of
children from 0 to 13 years old. The exceptional group was
adolescents (> 13–21 years old) where sensitivity was lower
(50%; 95% CI, 1.3–99%) and specificity was high (98.1%; 95%
CI, 94.3–100%), but this is based on only two confirmed diag-
noses of delirium (out of 56 total encounters) in this age group.
The performance of the CAPD by gender, respiratory support,
prematurity, and illness severity as determined by PIM-2 score
is presented in Table 4.
CAPD Psychometric Properties
Item fit/overlap analysis showed that each of the eight items was
highly correlated with the overall CAPD scale (Table 5). Cron-
bach’s α overall was 0.90 and for each separate item ranged from
0.87 to 0.90, indicating good internal consistency. Items 5, 6, and
TABLE 3. Incidents of False-Negative Cornell Assessment of Pediatric Delirium (n = 3, 1.2%)
Defined as Score Less Than 9 but Psychiatrist Rated “Delirious”
Delay Clinical
of Pediatric
Delirium Score
Observations Other
2–5 Ye s Patient had Trisomy 21 and
respiratory failure, on
sedatives, opiates
6 Restless, less
aware, and less
than baseline per
Patient well known
to psychiatrist and
Next shift CAPD
scored 12, possible
fluctuating MSE
13–21 No Patient had DiGeorge
Syndrome, anxiety and
mood disorders, and
Asperger Syndrome at
baseline; history of Epstein-
Barr virus-lymphoma post
stem cell transplant, in
PICU for management of
cerebral hemorrhage, on
sedatives, opiates
7 Restless, more
withdrawn than
baseline per
Fluctuating MSE
assessed over 5 d
and was delirious
by CAPD 2/5 and
by psychiatrist 2/5.
Had one false-
positive CAPD and
one false-negative
CAPD. Patient was
difficult to assess
6–12 No Patient in PICU for
postoperative management
after thoracoabdominal
resection of neuroblastoma,
on opiates
5 Withdrawn affect,
speech, anger/
mood changes,
Possible fluctuating
MSE, previous day
had concordant
Possible improper
use of CAPD
CAPD = Cornell Assessment of Pediatric Delirium, MSE = mental status examination.

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7 were the least well correlated (0.65, 0.62, and 0.68, respectively)
but still well above the generally accepted threshold of 0.20.
With an overall prevalence rate of 20.6% in our study popula-
tion, delirium is a common problem in pediatric critical care.
The CAPD was designed to fill a critical gap in the ability of
PICU staff to identify patients who may be suffering from
Elements of the Screen
The CAPD items are intended to correlate directly to the
DSM-IV definition of delirium, which requires alteration in
consciousness (including attention and awareness), and cog-
nition (including memory, orientation, perception, and lan-
guage) (Table 1). Each item was determined to fit well in the
overall scale. The CAPD screen is designed to allow for behav-
ioral, developmentally informed observations to be scaled and
summarized in a total score, which indicates whether a child is
likely to be delirious.
A Sensitive Screening Tool
With a sensitivity of 94.1%, the CAPD produced three false
negatives out of 248 assessments. Of these (Table 3), two of
the three children screened positive on a prior or subsequent
CAPD. By performing the screen twice daily, these subjects
would have been detected. Because one of these children had
significant developmental delay, and the other a preexist-
ing psychiatric illness, it is possible that these factors com-
plicated the nursing assessment. The third screen may not
have been performed accurately as it conflicts with the psy-
chiatric assessment in many item responses. Larger studies
are needed to further assess factors that confound detection
of delirium.
Specificity in Diagnosing Delirium
Although each individual item in the tool may describe behav-
iors or symptoms that can be associated with other causes of
cerebral dysfunction (such as sedation, agitation, pain, and
anxiety), the combination of these items with a total cutoff
score of 9 successfully selects for delirium.
TABLE 4. Performance of the Cornell Assessment of Pediatric Delirium Reported by
Receiver Operating Characteristic Analysis, Sensitivity, and Specificity
Number of
Assessments Prevalence (%)
Area Under Curve by
Receiver Operating
Characteristic Analysis Sensitivity (95% CI) Specificity (95% CI)
All PICU patients 248 20.6 94 94.1 (83.8–98.8) 79.2 (73.5–84.9)
Age (yr)
< 2 76 19.5 92 100 (100–100) 67.7 (45.9–89.6)
2–5 49 43.5 94 100 (100–100) 69.0 (36.7–100)
6–12 67 20.3 85 86.7 (65.6–100) 76.8 (55.3–98.3)
13–21 56 3.6 99 50 (0.2–100) 98.1 (94.3–100)
Developmental delay
No 181 13.9 93 92.0 (85.7–98.3) 86.5 (75.4–97.6)
Ye s 67 38.8 86 96.2 (86.5–100) 51.2 (24.7–77.8)
Male 152 21.7 94 93.9 (88.8–99.1) 76.5 (59.0–93.9)
Female 96 18.8 94 94.4 (81.4–100) 83.5 (67.8–99.3)
Respiratory support
No 115 5.2 98 100 (100–100) 86.9 (73.8–100)
Ye s 133 33.8 89 93.6 (87.2–100) 71.6 (54.9–88.2)
No 186 20.3 95 94.6 (90.5–98.7) 83.9 (71.7–96.1)
Ye s 62 22.6 87 92.9 (78.9–100) 64.6 (37.6–91.6)
Pediatric Index of
Mortality II
Below median 124 12.3 93 90.0 (66.9–100) 79.8 (61.7–97.9)
Above median 124 29.7 93 95.1 (91.7–98.5) 78.6 (62.6–94.7)

Traube et al
662 www.ccmjournal.org March 2014 • Volume 42 • Number 3
The screen produced 41 false positives, 20 in patients with
significant developmental delay. This speaks to the difficulty of
diagnosing delirium in this population as these children may
have other reasons for behavioral and emotional dysregulation
at baseline. Psychiatric assessment for these children is more spe-
cific and would be appropriate for children with developmen-
tal delay who score greater than 9 on the CAPD. However, the
screen still has high negative predictive value in this population.
Nearly half (48%) of the
subjects who received a false-
positive CAPD score were diag-
nosed with delirium at a later
point in their PICU stay. We
theorize that the CAPD score
may trend with the patient’s
waxing and waning clinical sta-
tus and may be useful in identi-
fying evolving delirium.
It is significant that 31% of our
assessments were in children
less than 2 years old, and 27%
of our assessments were in
children who are developmen-
tally delayed. Our study indi-
cates that the CAPD is a valid
and reliable delirium screen in
these vulnerable populations.
The developmental anchor
points for each item were a
valuable point-of-use reference
for assessing the youngest of
patients. With the addition of
these anchor points and mini-
mal training, the critical care
nursing staff became adept at
using the CAPD in all but the
most developmentally delayed patients. The nurses completed
the assessment midshift, after several hours of observing the
child’s behavior. In every assessment, the nurses required less
than 2 minutes to complete the CAPD screen.
Study Limitations
The CAPD was developed and validated in a single institution
and needs to be replicated in a multi-institutional study. Prepa-
rations for such a study are ongoing.
This study found a very low prevalence of delirium in ado-
lescents (children > 13 years old), limiting adequate determi-
nation of sensitivity and specificity of the tool in this subgroup.
A larger sample size will be required for this age group.
In patients with significant developmental delay, the false-
positive rate was higher, reflecting the difficulty of assess-
ing these patients. In our study cohort, children with delay
were more often diagnosed with delirium, suggesting that
these patients may be at greater risk. More research is needed
to reproduce this finding and address the best diagnostic
approaches in this vulnerable population, who likely have
baseline brain alterations or abnormalities. The possibility of a
higher CAPD cut point, or a modification of scoring adjusting
for baseline functioning, needs to be assessed in larger studies.
For study purposes, the CAPD and psychiatric evaluations
happened during the daylight hours, at approximately noon
each day. To more accurately capture delirious patients, who
Figure 3. Cornell Assessment of Pediatric Delirium performance by receiver operating curves. Thick line
represents area under the cure (AUC) = 0.9364; dashed line represents AUC = 0.9582; and dashed and
dotted line represents AUC = 0.8602. All = all subjects, DT = developmentally typical subjects,
DD = developmentally delayed subjects.
TABLE 5. Cornell Assessment of Pediatric
Delirium Internal Consistency and Item-
Test Correlations
Item Item-Test Correlation α if Item Deleted
1 0.83 0.88
2 0.85 0.87
3 0.86 0.87
4 0.88 0.87
5 0.65 0.90
6 0.62 0.90
7 0.68 0.90
8 0.77 0.88
Test scale 0.90

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may be more symptomatic at night, the CAPD will need to be
performed a minimum of twice daily, once by each shift nurse.
The CAPD is a promising new clinical screening tool designed
and validated for use in the PICU setting to detect delirium in
most children. Future work will address further clinical appli-
cations of the CAPD, such as diagnostic algorithms for spe-
cial populations in which delirium diagnoses are challenging.
The CAPD may facilitate the development of much needed
research investigating the causes, pathophysiology, treatment,
and long-term implications of pediatric delirium.
1. American Psychiatric Association: Task Force on DSM-IV. Diagnostic
and Statistical Manual of Mental Disorders: DSM-IV-TR. Fourth
Edition. Washington, DC, American Psychiatric Association, 2000
2. Schieveld JN, Leentjens AF: Delirium in severely ill young children in
the pediatric intensive care unit (PICU). J Am Acad Child Adolesc
Psychiatry 2005; 44:392–394; discussion 395
3. Potts MB, Koh SE, Whetstone WD, et al: Traumatic injury to the
immature brain: Inflammation, oxidative injury, and iron-mediated dam-
age as potential therapeutic targets. NeuroRx 2006; 3:143–153
4. Martini DR: Commentary: The diagnosis of delirium in pediatric
patients. J Am Acad Child Adolesc Psychiatry 2005; 44:395–398
5. Jakob SM, Ruokonen E, Grounds RM, et al; Dexmedetomidine for
Long-Term Sedation Investigators: Dexmedetomidine vs midazolam or
propofol for sedation during prolonged mechanical ventilation: Two
randomized controlled trials. JAMA 2012; 307:1151–1160
6. Schieveld JN, van der Valk JA, Smeets I, et al: Diagnostic consider-
ations regarding pediatric delirium: A review and a proposal for an
algorithm for pediatric intensive care units. Intensive Care Med 2009;
7. Creten C, Van Der Zwaan S, Blankespoor RJ, et al: Pediatric delirium
in the pediatric intensive care unit: A systematic review and an update
on key issues and research questions. Minerva Anestesiol 2011;
8. Neto AS, Nassar AP Jr, Cardoso SO, et al: Delirium screening in
critically ill patients: A systematic review and meta-analysis. Crit Care
Med 2012; 40:1946–1951
9. Hatherill S, Flisher AJ: Delirium in children and adolescents: A sys-
tematic review of the literature. J Psychosom Res 2010; 68:337–344
10. Smeets IA, Tan EY, Vossen HG, et al: Prolonged stay at the paediat-
ric intensive care unit associated with paediatric delirium. Eur Child
Adolesc Psychiatry 2010; 19:389–393
11. Colville G, Kerry S, Pierce C: Children’s factual and delusional memo-
ries of intensive care. Am J Respir Crit Care Med 2008; 177:976–982
12. Prugh DG, Wagonfeld S, Metcalf D, et al: A clinical study of delirium
in children and adolescents. Psychosom Med 1980; 42:177–195
13. Saczynski JS, Marcantonio ER, Quach L, et al: Cognitive trajectories
after postoperative delirium. N Engl J Med 2012; 367:30–39
14. Balas MC, Rice M, Chaperon C, et al: Management of delirium in criti-
cally ill older adults. Crit Care Nurse 2012; 32:15–26
15. Friedlander MM, Brayman Y, Breitbart WS: Delirium in palliative
care. Oncology (Williston Park) 2004; 18:1541–1550; discussion
16. Girard TD, Pandharipande PP, Ely EW: Delirium in the intensive care
unit. Crit Care 2008; 12(Suppl 3):S3
17. Barr J, Fraser GL, Puntillo K, et al: Clinical practice guidelines for the
management of pain, agitation, and delirium in adult patients in the
intensive care unit. Crit Care Med 2013; 41:263–306
18. Turkel SB, Braslow K, Tavaré CJ, et al: The delirium rating scale in
children and adolescents. Psychosomatics 2003; 44:126–129
19. Turkel SB, Tavaré CJ: Delirium in children and adolescents.
J Neuropsychiatry Clin Neurosci 2003; 15:431–435
20. Turkel SB, Trzepacz PT, Tavaré CJ: Comparing symptoms of delirium
in adults and children. Psychosomatics 2006; 47:320–324
21. Silver GH, Kearney JA, Kutko MC, et al: Infant delirium in pediatric
critical care settings. Am J Psychiatry 2010; 167:1172–1177
22. Smith HA, Fuchs DC, Pandharipande PP, et al: Delirium: An emerg-
ing frontier in the management of critically ill children. Crit Care Clin
2009; 25:593–614, x
23. Schieveld JN, Leroy PL, van Os J, et al: Pediatric delirium in critical
illness: Phenomenology, clinical correlates and treatment response
in 40 cases in the pediatric intensive care unit. Intensive Care Med
2007; 33:1033–1040
24. Hatherill S, Flisher AJ, Nassen R: Delirium among children and ado-
lescents in an urban sub-Saharan African setting. J Psychosom Res
2010; 69:187–192
25. Schieveld JN, Staal M, Voogd L, et al: Refractory agitation as a marker
for pediatric delirium in very young infants at a pediatric intensive care
unit. Intensive Care Med 2010; 36:1982–1983
26. Madden K, Turkel S, Jacobson J, et al: Recurrent delirium after surgery
for congenital heart disease in an infant. Pediatr Crit Care Med 2011;
27. Leentjens AF, Schieveld JN, Leonard M, et al: A comparison of the phe-
nomenology of pediatric, adult, and geriatric delirium. J Psychosom
Res 2008; 64:219–223
28. Silver G, Traube C, Kearney J, et al: Detecting pediatric delirium:
Development of a rapid observational assessment tool. Intensive
Care Med 2012; 38:1025–1031
29. Schieveld JN: On pediatric delirium and the use of the Pediatric
Confusion Assessment Method for the Intensive Care Unit. Crit Care
Med 2011; 39:220–221
30. Smith MJ, Breitbart WS, Platt MM: A critique of instruments and
methods to detect, diagnose, and rate delirium. J Pain Symptom
Manage 1995; 10:35–77
31. Blankespoor RJ, Janssen NJ, Wolters AM, et al: Post-hoc revi-
sion of the pediatric anesthesia emergence delirium rating scale:
Clinical improvement of a bedside-tool? Minerva Anestesiol 2012;
32. Janssen NJ, Tan EY, Staal M, et al: On the utility of diagnostic instru-
ments for pediatric delirium in critical illness: An evaluation of the
Pediatric Anesthesia Emergence Delirium Scale, the Delirium Rating
Scale 88, and the Delirium Rating Scale-Revised R-98. Intensive
Care Med 2011; 37:1331–1337
33. Trzepacz PT, Mittal D, Torres R, et al: Validation of the Delirium Rating
Scale-revised-98: Comparison with the delirium rating scale and the
cognitive test for delirium. J Neuropsychiatry Clin Neurosci 2001;
34. Smith HA, Boyd J, Fuchs DC, et al: Diagnosing delirium in critically ill
children: Validity and reliability of the Pediatric Confusion Assessment
Method for the intensive care unit. Crit Care Med 2011; 39:
35. Sikich N, Lerman J: Development and psychometric evaluation of
the pediatric anesthesia emergence delirium scale. Anesthesiology
2004; 100:1138–1145
36. Shapiro T, Hertzig M: Normal growth and development. In: Textbook
of Psychiatry. Fourth Edition. Talbot J, Hales R (Eds). Washington,
DC, American Psychiatric Press, 2003
37. Ball RS: The Gesell Developmental Schedules: Arnold Gesell (1880-
1961). J Abnorm Child Psychol 1977; 5:233–239
38. Ely EW, Truman B, Shintani A, et al: Monitoring sedation status over
time in ICU patients: Reliability and validity of the Richmond Agitation-
Sedation Scale (RASS). JAMA 2003; 289:2983–2991
39. Sessler CN, Gosnell MS, Grap MJ, et al: The Richmond Agitation-
Sedation Scale: Validity and reliability in adult intensive care unit
patients. Am J Respir Crit Care Med 2002; 166:1338–1344
40. Zhou XH, Obuchowski NA, McClish DK: Statistical Methods in
Diagnostic Medicine. New York, NY, Wiley, 2002
41. Rao JN, Scott AJ: A simple method for the analysis of clustered binary
data. Biometrics 1992; 48:577–585
42. Schieveld JN, Lousberg R, Berghmans E, et al: Pediatric illness sever-
ity measures predict delirium in a pediatric intensive care unit. Crit
Care Med 2008; 36:1933–1936