RESEARCH ARTICLE

The Association Between Fever and SubsequentDeterioration Among Hospitalized Children WithElevated PEWSJustin Lockwood, MD, MSCS,a,d Jennifer Reese, MD,a,d Beth Wathen, MSN, PNP,b,d Jacob Thomas, MS,c,d Mark Brittan, MD, MPH,a,c,d

Melissa Iwanowski, MPH, BSN, RN,d,e Lisa McLeod, MD, MSCEa,c,d

A B S T R A C TOBJECTIVES: To evaluate the association between fever and subsequent deterioration among patients withPediatric Early Warning Score (PEWS) elevations to $4 to inform improvements to care escalation processes atour institution.

METHODS: We performed a cohort study of hospitalized children at a single quaternary children’s hospital withPEWS elevations to $4 between January 1, 2014 and March 31, 2014. Bivariable analysis was used to comparecharacteristics between patients with and without unplanned ICU transfers and critical deterioration events(CDEs) (ie, unplanned ICU transfers with life-sustaining interventions initiated in the first 12 ICU hours). Amultivariable Poisson regression was used to assess the relative risk of unplanned ICU transfers and CDEs.

RESULTS: The study population included 220 PEWS elevations from 176 unique patients. Of those, 33% hadfever (n 5 73), 40% experienced an unplanned ICU transfer (n 5 88), and 19% experienced CDEs (n 5 42).Bivariable analysis revealed that febrile patients were less likely to experience an unplanned ICU transfer thanthose without fever. The same association was found in multivariable analysis with only marginal significance(adjusted relative risk 0.68; 95% confidence interval 0.45–1.01; P 5 .058). There was no difference in the CDErisk for febrile versus afebrile patients (adjusted relative risk 0.79; 95% confidence interval 0.43–1.44; P 5 .44).

CONCLUSIONS: At our institution, patients with an elevated PEWS appeared less likely to experience anunplanned ICU transfer if they were febrile. We were underpowered to evaluate the effect on CDEs. Thesefindings contributed to our recognition that (1) PEWS may not include all relevant clinical factors used for clinicaldecision-making regarding care escalation and (2) further study is needed in this area.

aSection of HospitalMedicine, Department of

Pediatrics, School ofMedicine, and cAdult and

Child Consortium forHealth Outcomes

Research and DeliveryScience, University of

Colorado, Aurora,Colorado; and bPICU and

eQuality and PatientSafety, dChildren’sHospital Colorado,Aurora, Colorado

www.hospitalpediatrics.orgDOI:https://doi.org/10.1542/hpeds.2018-0187Copyright © 2019 by the American Academy of Pediatrics

Address correspondence to Justin Lockwood, MD, MSCS, Section of Hospital Medicine, Department of Pediatrics, Children’s HospitalColorado, 13123 E 16th Ave, Box B302, Aurora, CO 80045. E-mail: justin.lockwood@childrenscolorado.org

HOSPITAL PEDIATRICS (ISSN Numbers: Print, 2154-1663; Online, 2154-1671).

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

FUNDING: Supported by National Institutes of Health National Center for Advancing Translational Sciences Colorado Clinical andTranslational Sciences Institute grant ULI TR001082. Contents are the authors’ sole responsibility and do not necessarily representofficial National Institutes of Health views. Funded by the National Institutes of Health (NIH).

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

Dr Lockwood is a pediatric hospitalist who assisted with the study design and data analysis before drafting the manuscript; Dr Reese isthe section head of pediatric hospital medicine who assisted with the study design and provided mentorship; Mr Thomas is abiostatistician who performed the statistical analysis; Ms Wathen is a clinical practice specialist in the PICU at Children’s HospitalColorado who assisted in study design and data collection; Dr Brittan is a pediatric hospitalist who assisted with the study design anddata analysis; Ms Iwanowski is a quality improvement specialist who assisted in the study design and data collection; Dr McLeod is apediatric hospitalist who assisted with study design, assisted with data analysis, and provided mentorship; and all authors approvedthe final manuscript as submitted.

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Hospitalized children requiring anunplanned transfer to the ICU experienceworse clinical outcomes than patientsadmitted directly to the ICU.1,2 To improvethese outcomes, a bedside consult with arapid response team (RRT) composed of ICUpersonnel is often incorporated into careescalation systems to facilitate earlyidentification and intervention for patientsoutside the ICU at risk for deterioration. Theuse of RRTs is associated with reductions inhospital-wide mortality, codes andcardiopulmonary arrests outside of the ICU,and emergent, unplanned ICU transfers.3–8

To facilitate early RRT activation, earlywarning scores (illness severity scoresbased primarily on objective vital-sign data)are used in many care escalation systemsas a trigger for RRT activation. These scoresare widely used for the purpose ofidentifying children at risk fordeterioration,9 although data supportingtheir effectiveness are weak.10–14

One commonly used early warning score isthe Brighton Pediatric Early Warning Score(PEWS) created by Monaghan15 in 2005.Authors of multiple single-center studieshave reported potential benefits of usingPEWS to identify hospitalized children atrisk for deterioration.16–22 PEWS redirectscare team members’ attention to patientswho are at risk for a more in-depthevaluation of changes in the patient’scondition,23 empowers nurses to escalatecare up the hierarchy of the care team,24

and provides standardized language whenescalating care.25 However, there isconflicting evidence on the superiority ofPEWS at identifying deterioration comparedwith provider intuition and clinicalrecognition,26,27 and care team membersmay not feel that acuity scores like PEWSare helpful in patients who are wellappearing or those with abnormalphysiology due to chronic underlyingconditions.24,25 A recent large multisiterandomized control trial revealed noimprovement in mortality after theimplementation of an early warning systemin which a similar early warning scorewas used.28 Regardless, using PEWS as atrigger tool for RRT activation significantlyincreases the frequency of RRT activations,22

and 1 study revealed that it led to increased

resource use without improved patientoutcomes.29

During the study period, PEWS was used atour institution as a trigger for mandatoryRRT activation whenever the score elevatedto $4 (Fig 1). Compliance with this protocolwas low at 40% to 60%, and care teamsoffered many reasons for why they did notfeel RRT activation was indicated despite anelevated PEWS. One common explanationwas the presence of fever as a physiologiccause of the elevated PEWS such that thescore was not felt to be representative ofimpending deterioration. As many as 8%to 10% of hospitalized children have adocumented temperature .38.0°C,30,31

largely because fever is present in themajority of children with acute viralrespiratory infections, which represent asignificant proportion of hospitalizedchildren.32,33 Serious bacterial infectionsalso cause fever but are rare in childrenbecause only 3% of patients in theemergency department who are febrilehave a urinary tract infection, 3% havepneumonia, and ,1% have bacteremia.34

Regardless of etiology, fever can increase achild’s respiratory rate by 2.2 breaths perminute and can increase a child’s heart rateby 9.9 to 14.1 beats per minute with every 1°C rise in body temperature.30,35–37 As evidentby the PEWS criteria outlined in Fig 1,changes in vital signs can significantly altera patient’s PEWS. Consequently, care teammembers in certain circumstances may feela PEWS is falsely elevated because oftransient, physiologic vital sign changes inresponse to a fever rather than a morenefarious cause necessitating ICUinterventions.

Our purpose for this study is to determine ifthere is an association between fever andsubsequent deterioration among patientswith an elevated PEWS at our institution. Wehypothesize that hospitalized children whoare febrile at the time of the PEWS elevationare less likely to be transferred to the ICUand to experience critical deteriorationevents (CDEs) (unplanned ICU transfers withlife-sustaining interventions in the first12 ICU hours38) than children who are notfebrile. To date, authors of no studies haveevaluated these associations despite the

frequent use of fever at our institution as abenign, physiologic explanation for PEWSelevations, justifying a lack of careescalation. With the results of this study, wewill provide evidence as to whether ourphysicians are appropriately using thepresence of fever in their clinicalassessment of patients with an elevatedPEWS. We will apply the findings to efforts toimprove our local care escalation systembecause these results may informdiscussions on provider behavior and theoptimal use of PEWS within our broadercare escalation system.

METHODS

This project was determined not to behuman-subjects research and was approvedfor conduct by our institutionalorganizational research risk and qualityimprovement review panel.

Study Design

To inform our local care escalation systemand culture, we sought to answer thefollowing question: Among hospitalizedchildren with PEWS elevations to $4 at ourinstitution, are patients who are febrile atthe time of the elevation less likely toexperience unplanned ICU transfers andCDEs in the subsequent 12 hours thanpatients who are afebrile?

To best answer this question, we used aretrospective cohort study design tocompare subjects with and withoutsubsequent unplanned ICU transfers andCDEs. All subjects had PEWS elevationsto $4.

Data Source and Context

Data collection was limited to hospitalizedchildren at our primary children’s hospital.Our site is a quaternary care children’shospital with on-site PICU and pediatricsubspecialty services. During the studyperiod, certain higher acuity interventionswere permitted outside the ICU, includingheated high-flow nasal cannula (HHFNC),continuous albuterol, and, if it wasthe patient’s established baselinerespiratory support, positive pressureventilation (PPV).

Clinical and demographic data wereextracted from our electronic health record

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on all patients admitted to non-ICU,noncardiology, and nonpsychiatry unitsbetween January 1, 2014, and March 31,2014, with PEWS elevations to $4. Allhospitalizations were evaluated, includingrecurrent hospitalizations for the samepatient. Multiple consecutive elevatedPEWS on the same patient were combinedinto a single event for further analysis(Fig 2). The automated data were

supplemented by a manual chart reviewperformed by 3 of the study authors withexpertise in this field.

Measures

Our primary explanatory variable was feverat the time of the PEWS elevation. Thiswas defined as having a temperature.38.0°C as the most recently documentedtemperature at or before the time of

elevation. This was a dichotomous,categorical variable.

Our primary outcome was a subsequentunplanned ICU transfer after the PEWSelevation. This was defined as an ICUtransfer within 12 hours of the timeof elevation as documented in ourelectronic health record. This wasa dichotomous, categoricalvariable.

FIGURE 1 The PEWS scoring rubric and associated care escalation algorithm in place during the study period. The scoring rubric was adaptedfrom the Brighton PEWS15 for use at our institution. The algorithm recommended automatic RRT activation for patients whose PEWSelevated to $4. FIO2 fraction of inspired oxygen; HR, heart rate; RN, registered nurse; RR, respiratory rate.

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Our secondary outcome was a subsequentCDE, defined by Bonafide et al38 as anunplanned ICU transfer with a life-sustaining intervention in the first 12 hoursin the ICU. On the basis of a review of thecriteria by Bonafide et al38 and consensus ofthe study team to resolve ambiguity, wecharacterized life-sustaining interventionsas noninvasive ventilation (excludinghigh-flow nasal cannula), intubation, andvasopressor infusion. An event wascharacterized as a CDE if the unplannedICU transfer happened within 12 hours ofthe PEWS elevation, and $1 of the listedlife-sustaining interventions were initiatedwithin 12 hours of the transfer. Thissecondary outcome was included toaddress the concern that our primaryoutcome, an unplanned ICU transfer, mayin certain scenarios represent physicianbehavior rather than the patient’s true needfor life-sustaining interventions.

Additional clinically relevant variables wereconsidered as possible confounders forinclusion in the analysis (Table 1). Toaccount for care team familiarity with thepatient, we created a repeat events variableto control for potential differences betweenfirst-time events and repeat events. Becauseconsecutive elevated PEWS on a singlepatient were grouped into a single event foranalysis, these repeat events must beseparated by time and include a PEWS,4 in the interim. The presence of an

underlying complex chronic condition(CCC) was determined by using the CCCclassification system by Feudtner et al.39 Thepatient’s primary admission diagnoses werecollapsed into 3 clinically relevant groupsby consensus of the research team: acuterespiratory, oncologic, and other (composedprimarily of neurologic diagnoses). Anighttime event was defined as a PEWSelevation that occurred between 9:00 PM and9:00 AM to capture the perceived difficulty ofbehavior assessments overnight and thedifferences in our normal heart rate rangeswhen awake versus asleep.40 Age wasstratified to ,1 year and $1 year.

Analysis

A bivariable analysis was first used tocompare clinical and demographiccharacteristics between those with andwithout unplanned ICU transfers and CDEs.Wilcoxon rank sum tests were used tocompare median values of continuousvariables, and x2 tests were used to compareproportions for categorical variables.

Age and sex were identified a priori forinclusion in the multivariable model becauseof their significant clinical relevance to theresearch question. Additionally, covariateswith P , .2 on the bivariable analysis forunplanned ICU transfers and CDEs wereconsidered in the respective multivariablemodels. The primary multivariable modelfor unplanned ICU transfers included all

additional covariates with P , .2 in themultivariable analysis. The number ofcovariates permissible in the multivariablemodel for our sensitivity analysis was limitedby the low number of events in our subjectpopulation,41 and only those deemed themost clinically relevant were included. Forboth models, covariates were evaluatedfor correlation, and, if present, the mostclinically relevant variables were chosen forinclusion.

The multivariable analysis was performedby using Poisson regression with robusterror variance to calculate adjusted relativerisks (aRRs) and 95% confidence intervals(CIs), comparing the primary explanatoryvariable to the outcomes of interest afteradjusting for covariates. Poisson regressionwith robust error variance was chosenbecause it allowed us to calculate relativerisks (rather than odds ratios) withimproved accuracy of the SE and CIs withincreasing outcome incidence.42,43

Certain variables were identified on thebasis of previous knowledge in the fieldas potential effect modifiers for therelationship between fever and bothoutcomes. These included age, primarydiagnosis, HHFNC, and CCC. Because ofrestrictions in sample size, we tested theseinteractions using Zelen’s exact test (anexact test version of the Cochran-Mantel-Haenszel test) for multiway 2-by-2 tablesrather than in multivariable models.

RESULTS

The study population included 220 uniquePEWS elevation events, none of which wereexcluded (Fig 2). Of the 220 PEWS elevations,40% required an unplanned ICU transfer, and19% experienced a CDE in the subsequent12 hours. The population was composed ofpatients admitted to the following services:general pediatrics and other medicalsubspecialties (51.4%); hematology, oncology,and bone marrow transplant (27%);pulmonology (16%); and surgical servicesand inpatient rehabilitation (6%). Additionalpatient and clinical event characteristics areshown in Table 1.

Bivariable Analysis

Bivariable comparisons are shown inTable 2. For patient-specific characteristics

FIGURE 2 Diagram of the distribution of all PEWS across the 3-month study period.

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expected to remain constant throughout thestudy period (age, sex, CCCs, and chronicdependence on PPV), comparisons wereperformed by using only the first event foreach individual patient (n 5 176). For allother characteristics, the full studypopulation was used for the bivariableanalysis (N 5 220).

Final Multivariable Models

Total PEWS, the PEWS subset scores, andchange from the previous PEWS were highlycorrelated, and total PEWS was chosen forinclusion in the model because of both itsstatistical significance in the bivariableanalysis and its clinical relevance. On thebasis of the results of the bivariableanalysis, our final multivariable model forour primary analysis of unplanned ICUtransfers included the following covariates:

presence of fever, age, sex, repeat patient,CCCs, primary diagnosis, total PEWS, andacute dependence on HHFNC. The finalmultivariable model for our secondaryanalysis of CDEs was limited to the followingcovariates: presence of fever, age, sex, totalPEWS, and HHFNC. Of the variables withP , .2 on the bivariable analysis of CDEs,HHFNC and total PEWS were chosen forinclusion in our multivariable model becauseof their clinical relevance to the study question.

Multivariable Analysis

Results of the multivariable analyses areshown in Fig 3.

Our primary analysis revealed withmarginal significance that patients withfever at the time of the PEWS elevation were32% less likely than those without fever toexperience an unplanned ICU transfer in the

subsequent 12 hours (aRR 0.68; 95% CI0.45–1.01; P 5 .058). Patients acutelydependent on HHFNC were 57% more likelythan patients not requiring HHFNC (aRR 1.57;95% CI 1.15–2.13; P 5 .004), and boys were27% less likely than girls to experience anunplanned ICU transfer in the subsequent12 hours (aRR 0.73; 95% CI 0.54–0.996;P 5 .047). Additionally, the risk of asubsequent unplanned ICU transfer went up40% with every 1-point increase in totalPEWS (aRR 1.40; 95% CI 1.23–1.59; P ,.0001). The aRR was not statisticallysignificant for all other variables in theprimary model.

Our secondary analysis did not reveal astatistically significant risk of CDEs basedon the presence or absence of fever at thetime of a PEWS elevation (aRR 0.79; 95% CI0.43–1.44; P 5 .44). The risk of a CDE in thesubsequent 12 hours after a PEWS elevationwent up 50% with every 1-point increasein total PEWS (aRR 1.50; 95% CI 1.19–1.89;P 5 .001). The aRR was not statisticallysignificant for all other variables in thesecondary model.

Assessment of Effect Modification

The analysis of potential effect modifiers didnot yield statistically significant results,although the primary diagnosis approachedsignificance (P 5 .068). Among subjectswith a respiratory diagnosis, the odds ofhaving a CDE for subjects with fever (versusthose without) was noticeably higher thanin the other 2 diagnosis groups.

DISCUSSION

Children hospitalized at our institution whohad fever at the time of a PEWS elevationwere less likely than patients without feverto experience an unplanned ICU transfer inthe subsequent 12 hours after a PEWSelevation to $4, although this associationwas only marginally significant, with a Pvalue slightly above the traditional a valueof .05. This trend may support anecdotalreports that the inclusion of fever indecision-making regarding care escalationfor patients with an elevated PEWS may havemerit. Because we were underpoweredto demonstrate the effect of fever onsubsequent CDEs, we do not know to whatdegree these associations reflect the

TABLE 1 Patient Demographics and Event Characteristics for Full Study Population

Variable Results

Total population, n (%) 220 (100)

First patient event only, n (%) 176 (80)

Second or repeat patient event, n (%) 44 (20)

Age, n (%)

,1 y 40 (22.7)

$1 y 136 (77.3)

Sex, n (%)

Girls 93 (53)

Boys 83 (47)

CCC,39 n (%) 79 (45)

Chronic PPV dependence, n (%) 15 (9)

Primary diagnosis category, n (%)

Respiratory 122 (56)

Oncologic 50 (23)

Surgical 8 (4)

Nonrespiratory infection 13 (6)

Other 27 (12)

Fever, n (%) 73 (33)

Total PEWS, median (IQR) 4.0 (4.0–5.0)

PEWS subset scores, median (IQR)

Cardiovascular 1.0 (1.0–1.0)

Respiratory 2.0 (1.0–3.0)

Behavior 1.0 (1.0–2.0)

Change from previous PEWS, median (IQR) 2.0 (1.0–3.0)

Acute HHFNC, n (%) 61 (28)

Continuous albuterol, n (%) 19 (9)

Nighttime event, n (%) 99 (45)

IQR, interquartile range.

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provider’s behavior and/or preferencesversus the patient’s true need for ICUinterventions. However, we do feel that anICU transfer offers clinical benefits topatients with deteriorating conditions(eg, smaller nursing ratios, continuousmonitoring, experienced personnel)even inthe absence of life-sustaining interventionsas defined by CDEs. Thus, our results maymost accurately be represented as follows:among children with an elevated PEWS,those with fever appeared less likely torequire an ICU transfer than those withoutfever. Such a conclusion has implicationsfor resource use born from the potentialovercalling of deterioration by anincomplete illness severity score.

A review of the remaining analysis revealedthat the risk of experiencing an unplanned

ICU transfer was higher if patients wereacutely dependent on HHFNC than if theywere not. This is not surprising becausethese patients are already experiencingrespiratory failure and are often requiringthe maximum allowable respiratory supportoutside of the ICU at our institution. Any signsof continued distress may represent the needfor higher levels of respiratory support thatcan only be instituted in the ICU.

Our results also revealed that the risk ofboth unplanned ICU transfers and CDEsincreased as PEWS increased, even afteradjusting for confounders. These resultssuggest PEWS may have predictive valuegenerally, although all relevant inputs maynot be considered in the score for reliableuse on individual patients. Thus, the abilityto predict the need for care escalation with

PEWS may vary significantly across differentclinical scenarios. For example, 2 patientswhose PEWS are elevated because oftachycardia may have significantly differentrisks of deterioration if 1 is febrile and theother is not. In that way, with our study,we may begin to offer care teams at ourinstitution the ability to make moreinformed decisions at the point of care byoffering evidence on the impact of fever onboth PEWS and patient outcomes. Thisevidence should then be part of bedsidediscussions with patients with a high PEWS.

Further study is needed. An adequatelypowered study used to evaluate theassociation between additional clinicalfactors and patient outcomes in thispopulation would contribute to theimprovement of the current PEWS and

TABLE 2 Bivariable Analysis Used to Compare Characteristics Between Events With and Without Unplanned ICU Transfers and CDEs in the12 Hours After a PEWS Elevation

Variable No ICU Transfer ICU Transfer P No CDE CDE P

Total population, n (%) 132 (100) 88 (100) N/A 178 (100) 42 (100) N/A

First event only, n (%) 100 (76) 76 (86) N/A 141 (79) 35 (83) N/A

Repeat event, n (%) 32 (24) 12 (14) .054 37 (21) 7 (17) .548

Age, y, n (%) .038 .984

,1 17 (17) 23 (30) 32 (23) 8 (23)

$1 83 (83) 53 (70) 109 (77) 27 (77)

Sex, n (%) .060 .186

Boys 59 (59) 34 (45) 78 (55) 15 (43)

Girls 41 (41) 42 (55) 63 (45) 20 (57)

CCC, n (%) 50 (50) 29 (38) .118 63 (45) 16 (46) .912

Chronic PPV dependence, n (%) 8 (8) 7 (9) .776 9 (6) 6 (17) .082

Primary diagnosis category, n (%) .016 .285

Respiratory 61 (46) 61 (69) 93 (52) 29 (69)

Oncologic 38 (29) 12 (14) 45 (25) 5 (12)

Surgical 6 (5) 2 (2) 6 (3) 2 (5)

Nonrespiratory infection 9 (7) 4 (5) 11 (6) 2 (5)

Other 18 (14) 9 (10) 23 (13) 4 (10)

Fever, n (%) 53 (40) 20 (23) .008 61 (34) 12 (29) .540

Total PEWS, median (IQR) 4.0 (4.0–4.0) 4.0 (4.0–5.0) .002 4.0 (4.0–5.0) 4.0 (4.0–5.0) .086

PEWS subset scores, median (IQR)

Behavior 1.0 (0.0–1.0) 1.0 (1.0–1.0) .162 1.0 (0.0–1.0) 1.0 (1.0–1.0) .224

Respiratory 2.0 (1.0–3.0) 2.0 (2.0–3.0) ,.001 1.0 (1.0–2.0) 1.0 (0.0–1.0) .005

Cardiovascular 2.0 (1.0–2.0) 1.0 (1.0–1.5) .001 2.0 (1.0–3.0) 3.0 (2.0–3.0) .002

Change from previous PEWS, median (IQR) 2.0 (1.0–3.0) 2.0 (1.0–3.0) .959 2.0 (1.0–3.0) 2.0 (1.0–3.0) .458

Acute HHFNC, n (%) 25 (19) 36 (41) ,.001 46 (26) 15 (36) .199

Continuous albuterol, n (%) 11 (8) 8 (9) .845 16 (9) 3 (7) ..999

Nighttime event, n (%) 60 (45) 39 (44) .868 80 (45) 19 (45) .972

IQR, interquartile range; N/A, not applicable.

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creation of a novel illness severity scorebetter equipped to guide clinical decision-making regarding deterioration.

Our study has limitations. First, it isimportant to consider that although the aRRused to compare fever to unplanned ICUtransfers in the multivariable analysis wasmarginally significant, and the upperconfidence limit crossed 1. Second, thestudy population was obtained during thewinter (“respiratory season”), and 56% ofsubjects had an acute respiratory infection.Because a temperature .38.0°C is anexpected part of the natural course ofillness in viral respiratory infections,32 thesepatients may be overrepresented amongour cohort of patients with fever. Third, ourinteraction analyses did not reveal anystatistically significant effect modifications

between the chosen covariates and fever inrelation to our outcomes, but further studywith a larger sample size would allow forbetter assessment of these interactions.Finally, the study population was drawnfrom a single institution in 2014. However,PEWS has not changed at our institutionsince 2014, and care team members’perceptions of the associations betweenPEWS and fever have also remainedconstant. The data were collected forprocess improvement purposes, and resultsdo not represent generalizable knowledge.

CONCLUSIONS

At our institution, patients with fever at thetime of a PEWS elevation may be less likelyto experience an unplanned ICU transferthan patients without fever. We were

underpowered to detect significantdifferences in CDEs and, therefore, do notknow the degree to which this associationrepresents provider behavior versus truedifferences in patient deterioration.Nonetheless, fever is likely 1 of manyclinical variables that can confound theinterpretation of PEWS, limiting its utility asa stand-alone trigger tool for careescalation.

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DOI: 10.1542/hpeds.2018-0187 originally published online February 13, 2019; 2019;9;170Hospital Pediatrics 

Iwanowski and Lisa McLeodJustin Lockwood, Jennifer Reese, Beth Wathen, Jacob Thomas, Mark Brittan, Melissa

Hospitalized Children With Elevated PEWSThe Association Between Fever and Subsequent Deterioration Among

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