3. Length of stay in the intensive care unit (ICU)
is recognized by the Joint Commission on Healthcare
Organizations as an important outcome measure
for ICU treatment,4
which is one of the most costly
and resource-intensive aspects of caring for patients.5
Mean costs are more than $10000 on the first day
of admission and nearly $5000/day afterward.6
Careful attention to ICU length of
stay by critical care nurses, combined
with targeted adjustments in patient
care planning, can help reduce asso-
ciated costs and complications.
ICU length of stay for patients
with acute, life-threatening injuries
can vary widely.5
Factors that influence
ICU length of stay include patients’
demographic variables such as age5
and physiological changes that occur
within the first 24 hours of admis-
sion.7
An example of an important
physiological change that occurs within the first 24
hours is the quality of the systemic inflammatory
response to injury.
In the hours after an acute life-threatening
injury, patients are at risk for development of the
systemic inflammatory response syndrome (SIRS), a
severe hyperinflammatory condition observed in
29% to 61% of patients after life-threatening
injury.8-14
The occurrence and severity of SIRS are
determined by calculating a SIRS score. This score is
increasingly being used to predict injury outcomes.
Studies have shown validity for the SIRS score in
predicting deadly complications seen in the ICU,
including infection and sepsis.8,10,12,13
The predictive
validity of the SIRS score for ICU length of stay has
not been tested, however.
A valid and easy-to-use bedside tool (such as the
SIRS score) that could be used to predict ICU length
of stay could help nurses maximize planning effi-
ciency for interventions aimed at preventing compli-
cations, reducing ICU costs, and improving patients’
outcomes. In contrast, existing predictor tools such as
the Acute Physiology and Chronic Health Evaluation
(APACHE) and the injury severity score (ISS) are not
helpful to bedside nurses. These tools were designed
to be used at the system level by health care adminis-
trators and require complicated computer software
to estimate ICU lengths of stay. The purpose of this
study was to investigate the validity of the SIRS score
as well as demographic and clinical variables for pre-
dicting ICU length of stay in patients with acute life-
threatening injuries.
Methods
Design and Sample
The institutional review board for the Medical
College of Georgia and MCGHealth gave approval
to conduct the study. A retrospective chart review
was conducted to measure the usefulness of the SIRS
score in predicting ICU length of stay. The study
sample consisted of charts entered into the trauma
registry database (National Trauma Registry of the
American College of Surgeons, Version 4.1.14, Forest
Hill, Maryland) at MCGHealth, a level I trauma
center, between 1998 and 2007. Inclusion criteria
were (1) age between 18 and 44 years, (2) presence
of acute, life-threatening injuries defined as an ISS
of 15 or greater, and (3) admission to the ICU for
at least 24 hours. Exclusion criteria were (1) blood
transfusion; (2) spinal cord injury; (3) comorbid
diseases that could affect immune function and
inflammatory response, including HIV infection,
cancer, and autoimmune disease; (4) regular use of
L
ife-threatening injury is the leading cause of death among persons aged 15 to 44
years and costs Americans nearly $40 billion annually.1,2
Thirty-six billion people
are injured each year, and injury is surpassed only by cardiac disease as the most
significant threat to health and productivity in the United States.1
Experts predict
that by the year 2020, bodily injury will surpass communicable disease as the lead-
ing cause of disability-adjusted life-years around the world.3
About the Authors
Elizabeth G. NeSmith is an assistant professor and Sally
P. Weinrich is a professor emeritus in the school of nurs-
ing at the Medical College of Georgia, Augusta. Jean-
nette O. Andrews is an associate professor and a senior
research scientist in the college of nursing at Medical
University of South Carolina in Charleston. Regina S.
Medeiros is a trauma program manager at MCGHealth.
Michael L. Hawkins is chief of trauma/surgical care in
the department of surgery at Medical College of Geor-
gia. Martin Weinrich is a professor emeritus in the
department of biostatistics at the Medical College of
Georgia.
Corresponding author: Elizabeth G. NeSmith, RN, MSN,
PhD, School of Nursing, Medical College of Georgia,
Augusta, GA 30912 (e-mail: bnesmith@mcg.edu).
Systemic inflam-
matory response
syndrome occurs
in up to 61% of
patients following
life-threatening
injury.
340 AJCC AMERICAN JOURNAL OF CRITICAL CARE, July 2009, Volume 18, No. 4 www.ajcconline.org
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4. using data contained in the nursing admission
assessment database. These data are routinely col-
lected and documented by the admitting nurse
from the patient or the patient’s next of kin.
Degree of acute, life-threatening injury was
measured by using the ISS. The ISS is a statistical
scoring system used by injury researchers that quan-
tifies multiple injuries and provides guidelines for
defining life-threatening injury for
the purpose of scientific study.18
The score has predictive validity:
research has validated the ISS as a
classic predictor of injury morbid-
ity and mortality since the score
was defined in 1974. The ISS is cal-
culated by the trauma registry soft-
ware. Scores range from 0 to 75. A
score between 0 and 15 indicates
mild injury, a score of 16 to 29 indicates moderate
injury, and 30 or greater indicates severe injury. ICU
length of stay was measured in whole (not partial)
24-hour units by counting the number of 24-hour
periods spent in the ICU, using times documented
in the chart. Time units were based on hour and
date of admission to the ICU and hour and date of
transfer to the medical-surgical step-down unit.
Procedures
A report was generated from the trauma registry
database for use as a screening tool to identify patients
for inclusion in the study. The trauma registry data-
base contains information on injury and demographic
characteristics, as well as diagnostic and disposition
data. The American College of Surgeons Committee
on Trauma19
mandates that all trauma centers main-
tain a trauma registry database. The ISS was collected
from the trauma registry database.
Analysis
Descriptive analysis of sample
variables was conducted and
included mean, median, and quar-
tile data. Univariate linear regres-
sion modeling was used to examine
the relationship between SIRS score
and ICU length of stay. The distri-
bution of ICU length of stay and
ISS was normalized by using loga-
rithmic transforms. Race, sex, age, smoking status,
and ISS were also included in the univariate regres-
sion modeling. The multiple regression model was
generated by using all variables of interest, including
race, sex, age, smoking, ISS, and SIRS score. All of the
models included linear and quadratic effects for the
nonsteroidal anti-inflammatory drugs; and/or (5)
missing data required to calculate the SIRS score.
The age range of 18 to 44 years was chosen to be
consistent with the injury-reporting age ranges for
adults defined by the Centers for Disease Control
and Prevention.2
All patients who met inclusion and
exclusion criteria, regardless of SIRS score, were
included in the study. Charts were screened and
data were collected by the primary author.
A total of 552 charts were screened: 101 (18%)
were excluded for blood transfusions, 108 (20%) for
missing data, 79 (14%) for ICU stays of less than 24
hours, 41 (7%) for spinal cord injury, and 6 (1%)
for comorbid diseases that could influence the devel-
opment of SIRS, such as HIV infection, cancer ther-
apy, or use of anti-inflammatory medications. Some
patients were excluded for meeting more than 1 of
these criteria. Of the 79 patients excluded for an ICU
stay of less than 24 hours, 40 were patients who died
less than 24 hours after injury (7% of the 552 charts
screened). Most of these deaths occurred in the emer-
gency department before arrival in the ICU. Excluded
deaths resulted primarily from severe traumatic brain
injuries caused from gunshot wounds to the head or
motor vehicle crashes.
Instruments
The independent variables for this study were
(1) SIRS; (2) demographic variables including race,
sex, and age; (3) smoking status; and (4) degree of
acute, life-threatening injury, operationalized as ISS.
ICU length of stay was the dependent variable.
SIRS was measured by using the SIRS score, an
instrument developed by a panel of experts at the
1991 American College of Chest Physicians/Society
of Critical Care Medicine consensus conference.15
This instrument has appropriate content validity.15,16
The SIRS score is determined by assigning 1 point
for each vital sign measure that meets the following
criteria: (1) body temperature greater than 38°C or
less than 36°C, (2) heart rate greater than 90/min,
(3) respiratory rate greater than 20/min or PaCO2 less
than 32 mm Hg, and (4) white blood cell count
greater than 12000/µL or less than 4000/µL or pres-
ence of 10% immature neutrophils.15
A SIRS score of
0 or 1 indicates absence of SIRS. A SIRS score of 2
(mild), 3 (moderate), or 4 (severe) indicates the
occurrence of SIRS.17
Intrarater reliability for the data
collector was assessed by calculating the SIRS score
for the same 50 patients on 2 separate occasions.
Intrarater reliability was 97%.
Demographic variables of race, sex, and age were
measured by using information contained in the
patient’s chart. Smoking status was measured by
www.ajcconline.org AJCC AMERICAN JOURNAL OF CRITICAL CARE, July 2009, Volume 18, No. 4 341
The SIRS score
assigns 1 point for
each vital sign
measure that
meets the criteria.
In this study,
79% of patients
met criteria for
SIRS on admission
to the ICU.
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5. SIRS score. For effect sizes that differed by SIRS
score and race, the terms were estimated separately
(nested within). The models were compared by
using partial and multiple partial F tests. Statistical
significance was determined on the basis of the F
statistic and an α less than .05.
Results
Most patients in the final sample of 246 were
white (n=133, 54%) and male (n=178, 72%). The
mean age was 29 years (Table 1). Of the 246 patients,
118 (52%) were smokers. Two-hundred forty-one
patients had blunt injuries resulting from motor
vehicle crashes, falls, or assaults (98%). Five patients
(2%) had penetrating injuries, all of which resulted
from gunshot wounds. Thirty-five patients (14%)
had severe traumatic brain injuries, defined as a score
of 3 on the Glasgow Coma Scale upon admission to
the ICU. The ISS ranged from 16 to 59, with a median
score of 22 (moderate injury).
The ICU length of stay was from 1 to 74 days,
with a mean of 8 days (Table 1). Eleven patients
(4%) included in the sample died. All 11 patients
died of traumatic brain injury or a combination of
traumatic brain injury with sepsis and multiple organ
failure. The ICU length of stay for these patients was
from 1 to 7 days (mean, 4 days). One patient outlier
had an ICU stay of 73 days. This patient died while
awaiting long-term placement after acute care and
was excluded from the analysis. Of the 35 patients
with a score of 3 on the Glasgow Coma Scale on
admission to the ICU, 17 (7% of the total sample)
had ICU stays longer than the mean of 8 days.
Seventy-nine percent (n=194) of patients met
criteria for SIRS on admission to the ICU. Of these,
31% had mild SIRS (score of 2), 37% had moderate
Table 1
Characteristics of patients and length of stay in the intensive care unit
Overall
Race
Whiteb
Minority
African American
Hispanic
Other
Sex
Male
Female
Age, y
Mean (SD)
Range
18-26
27-35
36-44
Injury severity score
Median (SD)
Range
Score 16-29b
Score ≥30
Smoking
Nonsmoker
Smoker
Unknown
Systemic inflammatory response syndrome
None (score 0 or 1)
Mild (score 2)
Moderate (score 3)
Severe (score 4)b
246 (100)
133 (54)
113 (46)
94 (83)
16 (14)
3 (3)
178 (72)
68 (28)
29 (8.1)
18-44
112 (45)
65 (26)
69 (28)
22 (7.1)
16-59
211 (86)
35 (14)
109 (48)
118 (52)
19 (8)
53 (22)
75 (39)
92 (48)
26 (13)
8.0
9.8b
6
6.6
3.7
2.7
8.3
7
6.3
9.6
8.3
6.6b
15
6.1
8.5
4.7
6.3
8.2
19.2b
3
4
3
3
3
3
3
4
3
4
3
3
6
3
3
2.5
3
4
10
2
2
2
2
1
2
2
2
2
2
2
2
3
2
2
2
2
2
6
8
10
5
6
4
3
9
6
6
9
10
7
25
6
8
4
6
8.3
27
a Values are number (%) unless otherwise indicated.
b Significance at α level <.05.
Days in intensive care unit
75th %ile25th %ileMedianMeanTotal groupaCharacteristic
342 AJCC AMERICAN JOURNAL OF CRITICAL CARE, July 2009, Volume 18, No. 4 www.ajcconline.org
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6. Severe SIRS (score of 4) was predictive of length
of stay with nearly the same level of significance as
the ISS (F=15.83; P<.001, vs F=20.23; P<.001). This
finding is important because the ISS serves as the ref-
erence standard in comparing the validity of the SIRS
score for predicting ICU length of stay. Physicians and
administrators use the ISS to predict ICU length of
stay retrospectively and to evaluate associated costs,
resource utilization, and health outcomes.
Nurses and physicians in the ICU have no such
tools with which to predict ICU length of stay objec-
tively in real time. The ISS was designed for use at
the system level and is difficult to apply at the bed-
side because of cumbersome calcu-
lation methods and lack of data
required to calculate the score on
admission. Unlike SIRS, which is
easily determined by using infor-
mation collected on admission, the
ISS is based on the final determina-
tion of all anatomic injuries, includ-
ing those that were initially hidden
during the first hours or days after
admission. To calculate the ISS, one must assign an
individual score for each injured body region,
square each score, and then add the 3 highest
scores. Compared with calculating the SIRS score,
this process is much more complicated. Because of
this complexity, the ISS is most frequently deter-
mined after discharge by the trauma data manager
or registrar by using a computer software program.
Race
In the exploratory analysis, white race was also
a strong predictor of ICU length of stay (F=9.7;
P=.002). This finding is a new and important addi-
tion to the injury literature, because race is often
overlooked as a variable in injury research. A recent
SIRS (score of 3), and 11% had severe SIRS (score
of 4). The mean ICU length of stay for patients with
severe SIRS (score of 4) on admission was 19.2 days.
Patients with moderate SIRS (score of 3) stayed a
mean of 8.2 days, whereas patients with mild SIRS
(score of 2) stayed a mean of 6.3 days. Patients with
no SIRS (score of 1 or 0) on admission stayed a mean
of 4.7 days in the ICU (Table 1).
Univariate Analyses
Univariate regression analyses were performed
for each SIRS score to determine predictive validity
for ICU length of stay. Mild SIRS was classified as a
score of 2, moderate was a score of 3, and severe was
a score of 4. Severe SIRS on admission to the ICU was
predictive of ICU length of stay (F=15.83; P<.001),
although mild and moderate SIRS were not.
Univariate regression analyses were also per-
formed on individual variables of race, sex, age,
smoking status, and ISS. White race (F=9.70; P=.002)
and ISS (F=20.23; P<.001) were predictors of ICU
length of stay (Table 2), whereas age, sex, and smok-
ing status were not predictors.
Multivariate Analysis
Three multivariate models were analyzed. The
first model included all of the dependent variables
of interest regardless of their significance level in the
univariate analysis, including SIRS score, race, sex,
age, smoking status, and ISS. This model was not
significant. A second model was analyzed that elimi-
nated the nonsignificant variables of sex, age, and
smoking from the univariate analysis and included
the significant variables of SIRS score, race, and ISS.
This model explained 21% of the variance (R2 =0.21)
for ICU length of stay (F=3.51; P=.06). The final
model included only nested values for SIRS and race.
This model explained 15% of the variance (R2 =.15)
for predicting ICU length of stay (F=7.7; P=.006).
Discussion
Severe SIRS (score of 4) on admission to the
ICU was a very strong predictor of ICU length of
stay (F=15.83; P <.001). The prevalence of SIRS
found in this study (79%) is comparable to that
reported by Bochicchio and colleagues11
(61%). It
is higher, however, than that found in other stud-
ies10,12,13
of patients with acute, life-threatening injuries
(29%-35%). Results of similar studies10,12
have vali-
dated severe SIRS as a predictor of hospital length
of stay in patients with acute, life-threatening injuries.
However, the present study is the only one in which
severe SIRS (score of 4) was a predictor of ICU length
of stay in patients with acute, life-threatening injuries.
Table 2
Predictors of length of stay in intensive care unit:
univariate regression analysis
White racea
Sex
Age
Smoking
Injury Severity Scorea,b
Severe systemic inflammatory
response syndrome (score of 4)a,c
0.04
0.0003
0.003
0.0001
0.08
0.12
1
1
1
1
1
2
.002
.81
.41
.88
.001
.001
a Significance at α level <.05.
b Injury Severity Score calculated as log10.
c Calculated by using a quadratic fit.
PFdfR2Predictor
9.70
0.06
0.69
0.02
20.23
15.83
Nurses can use
SIRS scores to
quickly predict
ICU length of stay
on admission.
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7. review20
showed that race was measured as a depend-
ent variable for acute outcomes of life-threatening
injury in only 2% of studies (7 of 352). By compar-
ison, race is measured more often as a dependent
variable in chronic disease research, and significant
findings are not uncommon.21
Age, Sex, and Smoking
Age, sex, and smoking were not predictive of
ICU length of stay. The findings related to age and
sex contrast with results of other research reports.5,22
One explanation for the difference in these results
may be that the patients’ age ranges and means in
previous studies were much wider (0-104 years old;
mean, 44-46 years old) than the age
range and mean for this study (18-
44 years old; mean, 29 years old). In
studies23,24
for which the age statistics
were comparable, the results of the
present study were supported.
Previous research has also
shown that female sex is a predictor
for decreased ICU length of stay in
this population of patients, even
when females were injured more
severely than males.25,26
These find-
ings may be related to recent results
by Frink et al,27
who reported that injured females
in the ICU had fewer complications related to
inflammatory response. It is difficult to compare the
results of Frink and colleagues directly, however,
because the complications measured in their study
were not measured in the present research.
The findings related to smoking in this research
are inconclusive when compared with results of other
injury and critical care studies. Two studies show
agreement with the present study, and 2 other stud-
ies show disagreement. Consistent with the findings
of the present research, Jurkovich and colleagues28
reported that smoking did not increase the odds for
prolonged ICU length of stay in patients with acute
injuries. Similarly, Delgado-Rodriguez et al29
reported
that smoking was not a significant predictor for ICU
length of stay in general surgery patients, although
smokers in their study did have longer adjusted ICU
lengths of stay (11.3 days vs 6.4 days). In contrast,
when Baldwin and colleagues30
examined both med-
ical and surgical ICU patients, smoking was a signif-
icant predictor for ICU length of stay (P=.008), as
it was in a study of patients who underwent coronary
bypass surgery (P<.05).31
All 4 of these studies28-31
were prospective analyses in which smoking status
was obtained from chart documentation based on
patient interviews.
Clinical Significance of Nested Model
In the multivariate analysis, the nested model,
which included severe SIRS (score of 4) and white
race, was a significant predictor of ICU length of
stay (P=.006). Multivariable models of predictors
of ICU length of stay that combine demographic
characteristics such as race with physiological
responses to injury such as severe SIRS have not
been previously reported in the injury literature.
Implications for Practice and Research
Critical care nurses and physicians need tools
that are easy to use at the bedside, like the SIRS score,
to help prioritize preventive care. Based on this
research, nurses can expect that patients with severe
SIRS (score of 4) will spend more days in the ICU
than will patients with mild or moderate SIRS (score
of 2 or 3, respectively). The practical application of
this information for nurses is that it provides a basis
for preventive care in (1) educating and preparing
patients and their families for the challenges associ-
ated with recovery from life-threatening injuries, (2)
ordering specialty beds to reduce skin breakdown,
and (3) prioritizing and planning for the discharge
needs of patients and their families.
Unlike physicians, who recommend using the
SIRS score on admission to help make practice deci-
sions for immediate care,13,14
nurses could use the
score to guide practice decisions for longer term
preventive care. Further, the SIRS score on admis-
sion could be added to acuity level assessments and
used by nurse managers for planning nurse staffing
on the basis of predicted length of stay.
Further research is needed to evaluate prospec-
tively the usefulness of the SIRS score as a tool for
critical care nurses in planning preventive care. The
present study should be replicated prospectively. All
variables known to influence ICU length of stay
should be included in conjunction with the physio-
logical influence of SIRS. Additional research is needed
to explore the findings of this study that race is a
predictor of ICU length of stay in patients with acute,
life-threatening injuries. Research is also needed to
assess the practical use of the SIRS score for priori-
tizing nursing care in the ICU for patients with acute,
life-threatening injuries.
Limitations
This study was conducted in 1 hospital, which
limited the sample size. However, the characteristics
of the patients in this study, including race, sex, mean
ISS, and percentages of mild, moderate, and severe
SIRS scores were comparable to characteristics of
patients in other studies with similar variables and
Severe SIRS
predicted length
of stay with nearly
the same level
of significance
as the injury
severity score.
344 AJCC AMERICAN JOURNAL OF CRITICAL CARE, July 2009, Volume 18, No. 4 www.ajcconline.org
at Medical College of Georgia Greenblatt Library on June 25, 2009ajcc.aacnjournals.orgDownloaded from
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purpose statements.10-13
This makes it useful to
inform the design of future studies to determine
how other, more hospital-based variables affect the
validity of the SIRS score for predicting ICU length
of stay. Generalizability is limited to patients with
mild, moderate, or severe SIRS (score of 2, 3, or 4).
A comparison of ICU length of stay in patients with
no SIRS (score of 0 or 1) was not made because of
the relatively small number of patients in this sub-
sample (n=52). Further, ICU length of stay is affected
by other variables that may not be reflected in the
chart, such as communication and family issues,
stress and depression, palliative care and ethical
issues, 24-hour presence of a physician, and avail-
ability of a unit-specific social worker.7
Use of the SIRS score in this research is sup-
ported by (1) the outcomes of the 2001 consensus
conference,16
(2) research that correlates the pres-
ence of SIRS with inflammatory biomarkers,32-35
and
(3) research that validates its use for predicting out-
comes in critically ill patients, including those with
acute, life-threatening injuries.10-13
Conclusions
This research supports that severe SIRS (score of
4) on admission to the ICU is a valid predictor of
ICU length of stay for patients with acute life-threat-
ening injuries. This information can be used to help
critical care nurses and physicians maximize resource
utilization within a known time frame and reduce
the possibility of poor outcomes.
ACKNOWLEDGMENTS
The authors acknowledge and thank the following for
their assistance in the conduct of this research and
preparation of this manuscript:Traci Hentges, BSN, RN,
CCRN, Shawn Roberson, BSN, RN, CCRN, VeronicaTurner, BSN,
RN, and Brendell Collins, BSN, RN, for their knowledgeable
and practical clinical advisement; Melissa Brown and
Cindy Bishop for their invaluable assistance with the
trauma registry database and record retrieval; and mem-
bers of the MCG Scholarship Club for their excellent
content reviews.
FINANCIAL DISCLOSURES
Support for this research was provided by the Center for
Nursing Research at Medical College of Georgia.
REFERENCES
1. Agency for Healthcare Research and Quality [AHRQ]. Heart
disease, cancer, and trauma injury top the list of the 15 most
costly medical conditions in the United States. http://
www.ahrq.gov/research/jun03/0603ra14.htm. Accessed
eLetters
Now that you’ve read the article, create or contribute to an
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www.ajcconline.org and click “Respond toThis Article”
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at Medical College of Georgia Greenblatt Library on June 25, 2009ajcc.aacnjournals.orgDownloaded from
9. 28. Jurkovich GJ, Rivara FP, Gurney JG, et al.The effect of
acute alcohol intoxication and chronic alcohol abuse on
outcome from trauma. JAMA. 1993;270(1):51-56.
29. Delgado-Rodriguez M, Medina-Cuadros M, Martinez-
Gallego G, et al. A prospective study of tobacco smoking
as a predictor of complications in general surgery. Infect
Control Hosp Epidemiol. 2003;24(1):37-43.
30. Baldwin WA, Rosenfeld BA, Breslow MJ, BuchmanTG,
Deutschman CS, Moore RD. Substance abuse-related
admissions to adult intensive care. Chest. 1993;103(1):21-25.
31. Christakis GT, Fremes SE, Naylor CD, Chen E, Rao V, Gold-
man BS. Impact of preoperative risk and perioperative
morbidity on ICU stay following coronary by-pass surgery.
Cardiovasc Surg. 1996;4(1):29-35.
32. Miyaoka K, Iwase M, Suzuki R, et al. Clinical evaluation of cir-
culating interleukin-6 and interleukin-10 levels after surgery-
induced inflammation. J Surg Res. 2005;125(2):144-150.
33. Ogura H,Tanaka H, KohT, et al. Enhanced production of
endothelial microparticles with increased binding to leuko-
cytes in patients with severe systemic inflammatory
response syndrome. JTrauma. 2004;56(4):823-831.
34. Iwasaki A, ShirakusaT, Maekawa SE, Maekawa S. Clinical
evaluation of systemic inflammatory response syndrome
(SIRS) in advanced lung cancer (T3 andT4) with surgical
resection. Eur J Cardiothorac Surg. 2005;27(1):14-18.
35. Wanner GA, Keel M, Steckholzer U, Beier W, Stocker R,
Ertel W. Relationship between procalcitonin plasma levels
and severity of injury, sepsis, organ failure, and mortality
in injured patients. Crit Care Med. 2000;28(4):950-957.
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10. Name Member #
Address
City State ZIP
Country Phone E-mail address
RN License #1 State
RN License #2 State
Payment by: K Visa K M/C K AMEX K Check
Card # Expiration Date
Signature
CE Test TestIDA0918042:SystemicInflammatoryResponseSyndromeScoreandRaceasPredictorsofLengthofStayintheIntensiveCareUnit.
Learning objectives: 1. Identify the significant results found in this study. 2. Describe practical applications of using the systemic inflammatory response syndrome
score. 3. Discuss further areas of research on this topic.
Program evaluation
Yes No
Objective 1 was met K K
Objective 2 was met K K
Objective 3 was met K K
Content was relevant to my
nursing practice K K
My expectations were met K K
This method of CE is effective
for this content K K
The level of difficulty of this test was:
K easy K medium K difficult
To complete this program,
it took me hours/minutes.
7. The research method used by the authors was which of the following?
a. Qualitative, phenomenological
b. Quantitative, prospective
c. Qualitative, focus group
d. Quantitative, retrospective
8. Based on the authors’ recommendations, what further research
needs to be done?
a. No further research is needed
b. A meta-analysis of all studies utilizing the SIRS score
c. A replication of their study using a prospective sample
d. A replication of their study using severe sepsis patients
What is identified as one of the limitations of this study?
a. Nonhomogeneous sample group
b. Study conducted at only 1 hospital
c. Small sample size
d. There was no control group or randomization
10.ThisresearchwasabletoshowthatasevereSIRSscoreisavalidpredic-
tor of increased length of stay for what type of patients?
a. Acute, life-threatening injuries
b. Postcardiovascular surgery
c. Spinal cord injuries
d. Comatose survivors of cardiac arrest
11. A group of trauma ICU nurses, after reading this study, would like to
do further research using the SIRS score. What is one area the authors
recommend for further research in the practical use of this tool?
a. Budgeting tool for the trauma ICU nurse manager
b. Validation of increased staffing needs
c. Physician treatment decisions
d. Prioritizing nursing care
12. How would a severe SIRS score affect the patient and family edu-
cation plan?
a. Delaying the education plan until the patient is transferred from the ICU
b. Educating and preparing patients and families of the challenges related to
recovering from their injuries
c. Focusing the education on the family as the patient would be unable to
participate
d. Giving the family written material on the subject in the language and
grade level they best understand
For faster processing, take
this CE test online at
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Articles in This Issue”) or
mail this entire page to:
AACN, 101 Columbia,
Aliso Viejo, CA 92656.
Fee: AACN members, $0; nonmembers, $10 Passing score: 9 Correct (75%) Category: A, Synergy CERP A Test writer: Rosemary Koehl Lee, MSN, RN-CNS, ACNP-BC, CCNS, CCRN
9. Ka
Kb
Kc
Kd
8. Ka
Kb
Kc
Kd
7. Ka
Kb
Kc
Kd
6. Ka
Kb
Kc
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5. Ka
Kb
Kc
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4. Ka
Kb
Kc
Kd
3. Ka
Kb
Kc
Kd
2. Ka
Kb
Kc
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1. Ka
Kb
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Kd
12. Ka
Kb
Kc
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10. Ka
Kb
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11. Ka
Kb
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The American Association of Critical-Care Nurses is accredited as a provider of continuing nursing education by the American Nurses Credentialing Center’s Commission on Accreditation.
AACN has been approved as a provider of continuing education in nursing by the State Boards of Nursing of Alabama (#ABNP0062), California (#01036), and Louisiana (#ABN12). AACN
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Test ID: A0918042 Contact hours: 1.0 Form expires: July 1, 2011. Test Answers: Mark only one box for your answer to each question. You may photocopy this form.
1. A patient in the trauma unit has been admitted with blunt chest
and abdominal trauma. He is a 55-year-old white male, with no signif-
icant past medical history. He is currently on a ventilator with an
assist control rate of 14; his current respiratory rate is 28; blood pres-
sure is 100/70 mm Hg; heart rate is 113; and his core temperature via
an esophageal temperature probe is 38.8°C. His arterial blood gases
reveal a pH of 7.48, PaCO2 of 31, PaO2 of 118, HCO3 of 18; the complete
blood cell count reveals a hemoglobin and hematocrit of 11 and 33,
and white blood cell count of 14 000. Based on this patient’s assess-
ment what would his SIRS score be?
a. 1 c. 3
b. 2 d. 4
2. In this study, which of the following was the dependent variable?
a. Degree of acute life-threatening injury
b. Intensive care unit (ICU) length of stay
c. SIRS score
d. White race
3. According to the results of this study, having severe SIRS on admis-
sion to the ICU is correlated significantly with what variable?
a. ICU length of stay c. Smoking history
b. Injury Severity Score d. White race
4. How may an ICU nurse use the information that a trauma patient
has a SIRS score of 4?
a. To plan for preventive care
b. To initiate the 6-hour sepsis bundle
c. To plan a family conference to discuss end-of-life issues
d. To know the patient’s condition warrants transfer to a progressive care unit
5. The SIRS score is noted by the authors to be a validated tool. What
other characteristic do the authors identify that would make this tool
feasible for use in the ICU by a bedside nurse?
a. To predict staffing needs
b. It is based on reliable quadratic equations
c. Simple and easy to use
d. The P value is 0.05
6. The admission into an ICU of a trauma patient on average costs how
much?
a. $1000 c. $10 000
b. $5000 d. $20 000
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