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BACKGROUND:

Adult prediction rules for cervical spine injury (CSI) exist; however, pediatric rules do not. Our objectives were to determine test accuracies of retrospectively identified CSI risk factors in a prospective pediatric cohort and compare them to a de novo risk model.

METHODS:

We conducted a 4-center, prospective observational study of children 0 to 17 years old who experienced blunt trauma and underwent emergency medical services scene response, trauma evaluation, and/or cervical imaging. Emergency department providers recorded CSI risk factors. CSIs were classified by reviewing imaging, consultations, and/or telephone follow-up. We calculated bivariable relative risks, multivariable odds ratios, and test characteristics for the retrospective risk model and a de novo model.

RESULTS:

Of 4091 enrolled children, 74 (1.8%) had CSIs. Fourteen factors had bivariable associations with CSIs: diving, axial load, clotheslining, loss of consciousness, neck pain, inability to move neck, altered mental status, signs of basilar skull fracture, torso injury, thoracic injury, intubation, respiratory distress, decreased oxygen saturation, and neurologic deficits. The retrospective model (high-risk motor vehicle crash, diving, predisposing condition, neck pain, decreased neck mobility (report or exam), altered mental status, neurologic deficits, or torso injury) was 90.5% (95% confidence interval: 83.9%–97.2%) sensitive and 45.6% (44.0%–47.1%) specific for CSIs. The de novo model (diving, axial load, neck pain, inability to move neck, altered mental status, intubation, or respiratory distress) was 92.0% (85.7%–98.1%) sensitive and 50.3% (48.7%–51.8%) specific.

CONCLUSIONS:

Our findings support previously identified pediatric CSI risk factors and prospective pediatric CSI prediction rule development.

What’s Known on This Subject:

Pediatric cervical spine injury (CSI) risk factors from a large, multicenter, retrospective case-control study warrant prospective evaluation: predisposing condition, diving, high-risk motor vehicle crash, neck pain, inability to move neck, altered mental status, neurologic deficits, and torso trauma.

What This Study Adds:

In this 4-center prospective observational study of 4091 children with blunt trauma, 14 factors were associated with CSIs. Risk models with these variables accurately predicted CSIs and support conducting a larger study to fully derive a prediction rule.

Pediatric cervical spine injuries (CSIs) are associated with significant morbidity and mortality.1 Cervical plain radiographs and computed tomography (CT) use is prevalent during trauma evaluation.2,4 CSIs, however, are uncommon in children, and the great majority who undergo radiographic screening are injury free.5 Indiscriminate use of radiographic screening for pediatric CSIs is controversial because of concerns that radiation exposure will increase lifetime risk of malignancy.6,14 

Further controversy relates to prehospital use of spinal motion restriction (SMR) devices (cervical collars and rigid longboards). Theoretically, these devices protect from spinal cord injury if unstable injuries are present but are associated with known risks. Most germane during trauma evaluation is that mere presence of these devices leads to increased cervical spine imaging.15 This may be due to increased pain complaints with SMR or physicians deferring neck examinations when devices are present.15,16 

Two large prospective observational studies, National Emergency X-Radiography Utilization Study (NEXUS) and Canadian C-Spine Rule for Radiography, derived adult CSI prediction rules aimed at reducing cervical spine imaging.17,22 These rules were validated in adults and used to safely limit prehospital SMR and cervical imaging during trauma evaluation.23,26 Unfortunately, these studies were not focused on children (NEXUS: 3065 children, 30 with CSIs; Canadian C-spine: no children).5 Researchers have attempted to validate these rules in children with small prospective studies and retrospective analyses; however, results were mixed and sample sizes small.5,27,30 There are no CSI prediction rules specifically derived and validated in a pediatric population.

The Pediatric Emergency Care Applied Research Network (PECARN) conducted a 17-center, 5-year, retrospective case-control study that identified risk factors associated with CSIs in children with blunt trauma (altered mental status, focal neurologic findings, neck pain, torticollis [decreased neck mobility by report or exam], substantial torso injury, conditions predisposing to CSI, diving, and high-risk motor vehicle crash [MVC]).31,32 These factors were 98% sensitive for CSIs within the study cohort and, if used as a prediction rule, would reduce cohort imaging by at least 25%.

Because of risks of SMR and neck irradiation during evaluation of children after blunt trauma, there is a need to derive and validate a CSI prediction rule that guides clinical decision-making. Our primary aim was to determine test accuracies of retrospectively identified PECARN CSI risk factors in a prospective cohort of children. Our secondary aims were to derive a de novo model for predicting CSIs in children after blunt trauma, to compare this with the PECARN model, and to evaluate potential effects on cervical spine imaging rates if these models are used in decision support.

Between March 2014 and November 2016, we conducted a prospective observational study of consecutive children evaluated at 4 tertiary care children’s hospitals. Participating hospitals were academic freestanding children’s hospitals, American College of Surgeons Pediatric Level 1–verified, and PECARN members.

Inclusion criteria consisted of children younger than 18 years who presented to the emergency department (ED) for blunt trauma and were transported from scene of injury by emergency medical services (EMS) in SMR, underwent trauma team evaluation, and/or had cervical spine imaging ordered in the ED. We excluded children whose injury mechanism was solely penetrating trauma, whose legal guardian had a substantial language barrier, who were in state’s custody, or who were transferred from the study site for definitive care.

Data collection methods for this study were previously reported.33 In brief, trained research personnel administered electronic branch-logic questionnaires to treating ED providers to gather observations regarding CSI risk factors before knowledge of cervical spine imaging results, if ordered or if obtained at a transferring hospital, before knowledge of their institutional radiologist’s interpretation. Risk factors included those previously demonstrated to be associated with CSIs, that had biological and/or anatomic plausibility, and with good interrater reliability.16,34,36 These factors included mechanisms of injury and injury biomechanics (high-risk MVC37: passenger compartment intrusion including roof >12 inches at occupant site or >18 inches at any site, partial or complete ejection from vehicle, death of a passenger in the same compartment, and/or vehicle telemetry consistent with high-risk crashes; diving; axial load; or clotheslining: biomechanical force caused by a rope, cable, or similar item exerting traction on the neck while the body is in forward motion), patient history variables (predisposing conditions, loss of consciousness, neck pain, inability to move neck, paresthesia, numbness or weakness), and physical examination findings (altered mental status, intubation, signs of substantial head injury other than altered mental status, signs of basilar skull fracture, posterior midline tenderness to palpation, limited range of neck motion, substantial torso injury, substantial thoracic injury, respiratory distress, decreased oxygen saturation, substantial abdominal injury, substantial pelvic injury, thoracic spine tenderness, lumbar spine tenderness, sacral spine tenderness, focal neurologic deficits [paresthesia, decreased sensation, and weakness]). We defined substantial injuries as life-threatening and warranting surgical intervention or warranting inpatient observation. Respondents could not skip items but could indicate if a risk factor was unknown, unable to be assessed, not assessed, or unknown.

CSI was defined as vertebral fractures, ligamentous injury, intraspinal hemorrhage, or spinal cord injury (either on magnetic resonance imaging or spinal cord injury without radiographic association) involving the cervical region (occiput to seventh cervical vertebra, including ligamentous structures attaching the seventh cervical vertebra to first thoracic vertebra). Study personnel determined CSI diagnosis by reviewing cervical spine imaging reports and, if applicable, spine surgeon consultation notes. If imaging report diagnoses conflicted with spine surgeon consultation, we contacted the treating spine surgeon and/or the study’s spine surgeon for clarification. For children who did not undergo ED cervical spine imaging, the medical record was reviewed 21 days later for subsequent imaging. If no subsequent imaging was noted, a follow-up call with the legal guardian was conducted 21 to 28 days after the ED visit to verify absence of CSI.

The analytic cohort was described by using counts and frequencies. We dichotomized observations of CSI risk factors into 2 categories: present versus all other responses. Relative risks (RRs) of CSI with 95% confidence intervals (CIs) were estimated for all candidate risk factors. Risk factors from the PECARN retrospective case-control model were fit to prospective data by multivariable logistic regression and odds ratios (ORs), and 95% CIs were calculated for each risk factor. In a separate analysis, we derived a de novo CSI risk model using only variables with a bivariable lower 95% confidence limit >1 as candidates for inclusion and multiple stepwise logistic regression. Multivariable ORs and 95% CIs were calculated for variables retained in the model.

To assess model performance characteristics, each model was applied to the data as a decision tool where subjects were considered at risk for CSI if they had at least 1 positive value for any model variable. Sensitivity, specificity, negative predictive value, and positive predictive value for CSI were calculated for each model. Observer bias was assessed by repeating this assessment with the subcohort of children presenting directly from scene of injury (ie, excluding those transferred from referring institutions).

Expected overall cervical spine imaging rates were estimated for each model by assuming that any 1 positive variable would result in imaging. Estimates for CT use were calculated by applying each model as a prediction rule to the subpopulation that underwent CT.

All analyses were conducted by using SAS version 9.4 (SAS Institute, Inc, Cary, NC).

This study was approved by all sites’ institutional review boards to be conducted under waiver of written informed consent. Legal guardians of enrolled subjects were provided an informational handout that contained withdrawal instructions.

Supplemental Fig 1 summarizes study enrollment. In total, we screened 11 809 children who experienced blunt trauma, of whom 5764 were eligible and 4144 were enrolled. Characteristics of the 1620 children missed for enrollment were previously described.33 Compared with enrolled children, these children were slightly younger (median age 8.5 vs 9.4 years), more likely white (63% vs 60.8%), and less likely involved in MVCs (22.5% vs 27.3%) and all-terrain vehicle, motorcycle, or scooter crashes (5.1% vs 10.0%). Legal guardians withdrew 53 children.

Table 1 presents total cohort and CSI subpopulation characteristics. Of 4091 children, 74 (1.8%) had CSIs. Cohort mean age was 9.4 years, and mean age of those with CSIs was 10.7 years. A total of 39.3% of the cohort was younger than 8 years and 23 (1.4%) of these children had CSIs. The CSI subpopulation included more boys, white children, and non-Hispanic children. The most common mechanisms of injury for both groups were MVC and sports-related mechanisms. Children with CSIs were more likely to undergo trauma team evaluation and less likely to be discharged. Thirteen children died in the ED, none of whom had documented CSIs.

TABLE 1

Patient Characteristics

CharacteristicsAll Children in the Analytic Cohort, N = 4091Children With CSI in the Analytic Cohort, N = 74
n (%)n (%)
Age, y   
 0–2 824 (20.1) 10 (13.5) 
 3–7 785 (19.2) 13 (17.6) 
 7–15 1927 (47.1) 35 (47.3) 
 16–18 555 (13.6) 16 (21.6) 
Sex, male 2373 (58.0) 48 (64.9) 
Race   
 White 2471 (60.4) 48 (64.9) 
 African American 1290 (31.5) 18 (24.3) 
 Other 312 (7.6) 8 (10.8) 
Ethnicity   
 Non-Hispanic 3829 (93.6) 70 (94.6) 
 Hispanic 129 (3.2) 3 (4.1) 
 Unknown 133 (3.3) 1 (1.4) 
Mechanism of injury   
 MVC 1115 (27.3) 22 (29.7) 
 Fall 1100 (26.9) 18 (24.3) 
 Sports 523 (12.8) 9 (12.2) 
 ATV, motorcycle, or scooter 407 (10.0) 7 (9.5) 
 Hit by car 159 (3.9) 4 (5.4) 
 Diving 17 (0.4) 4 (5.4) 
 Other 363 (8.9) 4 (5.4) 
 Unknown 317 (7.8) 5 (6.8) 
Presenting directly to study site from the scene of injury  3095 (76.7) 43 (58.1) 
Disposition   
 Home 2632 (64.3) 14 (18.9) 
 Admit general inpatient 835 (20.4) 25 (33.8) 
 Admit ICU 318 (7.8) 28 (37.8) 
 Operating room 137 (3.4) 5 (6.8) 
 Death in ED 13 (0.3) 
Diagnosed with CSI 74 (1.8) n/a 
CharacteristicsAll Children in the Analytic Cohort, N = 4091Children With CSI in the Analytic Cohort, N = 74
n (%)n (%)
Age, y   
 0–2 824 (20.1) 10 (13.5) 
 3–7 785 (19.2) 13 (17.6) 
 7–15 1927 (47.1) 35 (47.3) 
 16–18 555 (13.6) 16 (21.6) 
Sex, male 2373 (58.0) 48 (64.9) 
Race   
 White 2471 (60.4) 48 (64.9) 
 African American 1290 (31.5) 18 (24.3) 
 Other 312 (7.6) 8 (10.8) 
Ethnicity   
 Non-Hispanic 3829 (93.6) 70 (94.6) 
 Hispanic 129 (3.2) 3 (4.1) 
 Unknown 133 (3.3) 1 (1.4) 
Mechanism of injury   
 MVC 1115 (27.3) 22 (29.7) 
 Fall 1100 (26.9) 18 (24.3) 
 Sports 523 (12.8) 9 (12.2) 
 ATV, motorcycle, or scooter 407 (10.0) 7 (9.5) 
 Hit by car 159 (3.9) 4 (5.4) 
 Diving 17 (0.4) 4 (5.4) 
 Other 363 (8.9) 4 (5.4) 
 Unknown 317 (7.8) 5 (6.8) 
Presenting directly to study site from the scene of injury  3095 (76.7) 43 (58.1) 
Disposition   
 Home 2632 (64.3) 14 (18.9) 
 Admit general inpatient 835 (20.4) 25 (33.8) 
 Admit ICU 318 (7.8) 28 (37.8) 
 Operating room 137 (3.4) 5 (6.8) 
 Death in ED 13 (0.3) 
Diagnosed with CSI 74 (1.8) n/a 

ATV, all-terrain vehicle; ICU, intensive care unit; n/a, not available.

The bivariable RRs for all risk factors and multivariable ORs for risk factors in the PECARN and de novo models are presented in Table 2. Fourteen factors had significant bivariable associations with CSIs in the study cohort: diving, axial load, clotheslining, loss of consciousness, neck pain, reported inability to move the neck, altered mental status, signs of basilar skull fracture, substantial torso injury, substantial thoracic injury, intubation, respiratory distress, decreased oxygen saturation, and focal neurologic deficits on examination.

TABLE 2

Risk Factors for CSI in Children

Risk FactorsBivariable RR (CI)PECARN Modela OR (CI)De Novo Modelb OR (CI)
Mechanism of injury or biomechanics    
 High-risk MVCc 1.57 (0.64–3.83) 1.58 (0.63–3.97) — 
 Diving 13.69 (5.64–33.27) 17.60 (5.60–55.32) 9.16 (2.41–34.83) 
 Axial load 3.18 (1.74–5.81) — 2.51 (1.22–5.16) 
 Clothesliningd 3.28 (1.07–10.08) — — 
Patient history    
 Predisposing conditions 1.99 (0.29–13.80) 2.02 (0.27–15.10) — 
 Loss of consciousness 2.07 (1.25–3.43) — — 
 Neck pain 1.64 (1.04–2.57) 1.65 (1.04–2.62) 2.87 (1.50–5.48) 
 Inability to move neck 3.61 (1.98–6.60) 3.77 (2.00–7.12) 3.51 (1.72–7.17) 
 Paresthesias 0.56 (0.14–2.25) — — 
 Numbness 0.38 (0.05–2.74) — — 
 Weakness 0.48 (0.07–3.41) — — 
Physical examination    
 Altered mental status 5.37 (3.42–8.44) 5.67 (3.54–9.09) 2.90 (1.37–6.12) 
  Intubated 11.35 (7.02–18.25) — 10.71 (4.43–25.91) 
 Signs of substantial head injury other than altered mental status 0.40 (0.10–1.61) — — 
  Signs of basilar skull fracture 5.52 (2.32–13.13) — — 
 Posterior midline tenderness to palpation 1.47 (0.94–2.32) — — 
 Limited neck range of motion 1.82 (0.89–3.76) 1.85 (0.88–3.90) — 
 Substantial torso injury 2.54 (1.24–5.22) 2.61 (1.24–5.53) — 
 Substantial thoracic injury 5.74 (2.42–13.63) — — 
  Respiratory distress 13.69 (5.64–33.28) — 5.84 (1.56–21.88) 
  Decreased oxygen saturation 15.67 (5.81–42.27) — — 
 Substantial abdominal injury 1.86 (0.69–5.01) — — 
 Substantial pelvic injury No estimatee — — 
 Thoracic spine tenderness 1.11 (0.63–1.94) — — 
 Lumbar spine tenderness 0.42 (0.16–1.16) — — 
 Sacral spine tenderness 0.40 (0.06–2.82) — — 
 Focal neurologic deficits 2.55 (1.05–6.20) 2.62 (1.04–6.63) — 
  Paresthesias No estimatee — — 
  Decreased sensation 2.12 (0.53–8.40) — — 
  Weakness 1.67 (0.42–6.66) — — 
Risk FactorsBivariable RR (CI)PECARN Modela OR (CI)De Novo Modelb OR (CI)
Mechanism of injury or biomechanics    
 High-risk MVCc 1.57 (0.64–3.83) 1.58 (0.63–3.97) — 
 Diving 13.69 (5.64–33.27) 17.60 (5.60–55.32) 9.16 (2.41–34.83) 
 Axial load 3.18 (1.74–5.81) — 2.51 (1.22–5.16) 
 Clothesliningd 3.28 (1.07–10.08) — — 
Patient history    
 Predisposing conditions 1.99 (0.29–13.80) 2.02 (0.27–15.10) — 
 Loss of consciousness 2.07 (1.25–3.43) — — 
 Neck pain 1.64 (1.04–2.57) 1.65 (1.04–2.62) 2.87 (1.50–5.48) 
 Inability to move neck 3.61 (1.98–6.60) 3.77 (2.00–7.12) 3.51 (1.72–7.17) 
 Paresthesias 0.56 (0.14–2.25) — — 
 Numbness 0.38 (0.05–2.74) — — 
 Weakness 0.48 (0.07–3.41) — — 
Physical examination    
 Altered mental status 5.37 (3.42–8.44) 5.67 (3.54–9.09) 2.90 (1.37–6.12) 
  Intubated 11.35 (7.02–18.25) — 10.71 (4.43–25.91) 
 Signs of substantial head injury other than altered mental status 0.40 (0.10–1.61) — — 
  Signs of basilar skull fracture 5.52 (2.32–13.13) — — 
 Posterior midline tenderness to palpation 1.47 (0.94–2.32) — — 
 Limited neck range of motion 1.82 (0.89–3.76) 1.85 (0.88–3.90) — 
 Substantial torso injury 2.54 (1.24–5.22) 2.61 (1.24–5.53) — 
 Substantial thoracic injury 5.74 (2.42–13.63) — — 
  Respiratory distress 13.69 (5.64–33.28) — 5.84 (1.56–21.88) 
  Decreased oxygen saturation 15.67 (5.81–42.27) — — 
 Substantial abdominal injury 1.86 (0.69–5.01) — — 
 Substantial pelvic injury No estimatee — — 
 Thoracic spine tenderness 1.11 (0.63–1.94) — — 
 Lumbar spine tenderness 0.42 (0.16–1.16) — — 
 Sacral spine tenderness 0.40 (0.06–2.82) — — 
 Focal neurologic deficits 2.55 (1.05–6.20) 2.62 (1.04–6.63) — 
  Paresthesias No estimatee — — 
  Decreased sensation 2.12 (0.53–8.40) — — 
  Weakness 1.67 (0.42–6.66) — — 

—, not applicable.

a

Model including only those variables identified in the PECARN retrospective case-control study.

b

Model created by using stepwise variable selection.

c

Intrusion, including roof; >12 inches occupant site, >18 inches any site; ejection (partial or complete) from automobile; death in same passenger compartment; vehicle telemetry data consistent with a high-risk crash.

d

Biomechanical force caused by a rope, cable, or similar item exerting traction on the neck while the body is in forward motion.

e

No children with CSIs within the cohort had the finding.

Most PECARN model risk factors maintained independent associations with CSIs in the multivariable analysis (diving, neck pain, reported inability to move neck, altered mental status, substantial torso trauma, and focal neurologic deficits); however, 3 variables did not (high-risk MVC, predisposing conditions, and limited neck range of motion on exam). The de novo model for CSI risk included 7 variables: diving mechanism, axial load, neck pain, reported inability to move neck, altered mental status, respiratory distress, and intubation.

In Table 3, we report test accuracies for each model. Compared with the PECARN model, the de novo model had marginally better sensitivity and specificity (90.5% and 45.6% vs 91.9% and 50.3%, respectively) and negative and positive predictive values (99.6% and 3.0% vs 99.7% and 3.3%, respectively). When the analysis was repeated for the 3138 children who presented directly to the study sites, including 43 with CSIs, the results were similar. The sensitivity and specificity of the PECARN model in this subcohort were 93.0% (95% CI 85.4%–100%) and 42.1% (95% CI 40.3%–43.8%), respectively. The sensitivity and specificity for the de novo model in the subcohort were 95.3% (95% CI 89.1%–100%) and 45.9% (95% CI 44.1%–47.7%), respectively.

TABLE 3

Model Performance

PECARN Modela (N = 4091)De Novo Modelb (N = 4091)
Any 1 Risk FactorNo Risk FactorscValue (95% CI)Any 1 Risk FactorNo Risk FactorscValue (95% CI)
CSI present 67 — 68 — 
CSI absent 2186 1831 — 1998 2019 — 
Sensitivity — — 90.54% (83.87%–97.21%) — — 91.89% (85.7%–98.11%) 
Specificity — — 45.58% (44.04%–47.12%) — — 50.26% (48.72%–51.81%) 
Positive predictive value — — 2.97% (2.27%–3.68%) — — 3.29% (2.52%–4.06%) 
Negative predictive value — — 99.62% (99.34%–99.90%) — — 99.71% (99.47%–99.94%) 
Positive likelihood ratio — — 1.66 (1.54–1.80) — — 1.85 (1.71–1.99) 
Negative likelihood ratio — — 0.21 (0.10–0.42) — — 0.16 (0.07–0.35) 
PECARN Modela (N = 4091)De Novo Modelb (N = 4091)
Any 1 Risk FactorNo Risk FactorscValue (95% CI)Any 1 Risk FactorNo Risk FactorscValue (95% CI)
CSI present 67 — 68 — 
CSI absent 2186 1831 — 1998 2019 — 
Sensitivity — — 90.54% (83.87%–97.21%) — — 91.89% (85.7%–98.11%) 
Specificity — — 45.58% (44.04%–47.12%) — — 50.26% (48.72%–51.81%) 
Positive predictive value — — 2.97% (2.27%–3.68%) — — 3.29% (2.52%–4.06%) 
Negative predictive value — — 99.62% (99.34%–99.90%) — — 99.71% (99.47%–99.94%) 
Positive likelihood ratio — — 1.66 (1.54–1.80) — — 1.85 (1.71–1.99) 
Negative likelihood ratio — — 0.21 (0.10–0.42) — — 0.16 (0.07–0.35) 

—, not applicable.

a

Model including only those variables identified in the PECARN retrospective case-control study.

b

Model created by using stepwise variable selection.

c

A risk factor was considered absent if the ED provider classified the risk factor as not present, unable to be assessed, not assessed, or unknown.

In Table 4, we present extrapolated imaging rates if these CSI risk models guided decision-making. Overall imaging rates would decrease by more than a third, from an observed rate of 78.2% to 55.1% or 50.5%, in the PECARN and de novo models, respectively. CT scan use would decrease by more than half, from 15.8% to 7.5% or 7.1%. However, both models would have missed children with CSIs; 7 with the PECARN model and 6 with the de novo model.

TABLE 4

Rates of Cervical Spine Imaging During ED Evaluation and Hospital Admission

InterventionReported by ED Provider at Time of Initial EvaluationObserved on Medical Record ReviewPECARN ModelaDe Novo Modelb
Any imaging 2723 of 4091 (66.6%) 3201 of 4091 (78.2%) 2253 of 4091 (55.1%)c 2066 of 4091 (50.5%)c 
CT scan 437 of 4091 (10.7%) 648 of 4091 (15.8%) 306 of 4091 (7.5%)d 289 of 4091 (7.1%)d 
InterventionReported by ED Provider at Time of Initial EvaluationObserved on Medical Record ReviewPECARN ModelaDe Novo Modelb
Any imaging 2723 of 4091 (66.6%) 3201 of 4091 (78.2%) 2253 of 4091 (55.1%)c 2066 of 4091 (50.5%)c 
CT scan 437 of 4091 (10.7%) 648 of 4091 (15.8%) 306 of 4091 (7.5%)d 289 of 4091 (7.1%)d 
a

Model including only those variables identified in the PECARN retrospective case-control study.

b

Model created by using stepwise forward variable selection.

c

Estimated by applying model to entire cohort, with the presence of any risk factor indicating need for imaging, and all no indicating imaging unneeded.

d

Estimated by applying the model to those that had the CT in the cohort, with the presence of any risk factor indicating need for the CT and absence of all risk factors indicating CT unneeded.

In Table 5, we present characteristics of the 7 children with CSIs missed by ED providers’ assessments of PECARN risk factors. On retrospective chart review, all but 1 child had PECARN risk factors: altered mental status (3), neck pain (3), and focal neurologic deficit (1). The child that lacked a PECARN risk factor reported back pain and severe upper thoracic tenderness and had a C7 burst fracture. None of the missed children required surgical intervention; however, 1 required a brace and another required a rigid cervical collar.

TABLE 5

Characteristics of Children With CSI Whose ED Provider Did Not Report One of the Risk Factors From the PECARN Model

AgeMechanism of Injury on Chart ReviewChief Complaint on Chart ReviewExamination Findings on Chart ReviewPECARN Risk Factors on Chart ReviewDiagnosisTreatment
5.7 y Fall from second story (10 ft) Back pain Diffuse thoracic spine tenderness None C7 burst fracture; T2–T4 compression fractures Brace 
15.3 y ATV crash Arrived from OSH with concern for CSI None Neck pain C1 lateral mass contusion and bilateral C1–C2 alar ligament injury Unknowna 
6.1 yb Fall (10 ft) Loss of consciousness; axial load Signs of substantial head injury other than altered mental status Neck pain C1–C2 epidural hemorrhage; no fracture or ligamentous disruption None 
7 wk Fall from bed reported, suspected NAT Loss of consciousness Repeat episodes of unresponsiveness and limp tone Altered mental status C1–C4 subdural hemorrhage; no fracture or ligamentous disruption None 
6 mo NAT Arrived from OSH with concern for substantial head injury Irritable; signs of substantial head injury; palpable skull fracture Altered mental status C7–T2 compression deformities with associated C7–T1 ligamentous injury None 
8.3 y MVC >55 MPH Arrived by EMS with concern for substantial head injury GCS 14 at scene; persistent somnolence and confusion; tenderness to neck palpation; sixth nerve palsy Altered mental status; focal neurologic deficit C2 ventral subdural hematoma None 
3.8 y Fall from bench hitting head on a table Transferred with concern for CSI; complained of neck pain and holding neck Occipital laceration; tenderness to palpation of the posterior midline neck Neck pain C1 posterior synchondrosis fracture Rigid cervical collar 
AgeMechanism of Injury on Chart ReviewChief Complaint on Chart ReviewExamination Findings on Chart ReviewPECARN Risk Factors on Chart ReviewDiagnosisTreatment
5.7 y Fall from second story (10 ft) Back pain Diffuse thoracic spine tenderness None C7 burst fracture; T2–T4 compression fractures Brace 
15.3 y ATV crash Arrived from OSH with concern for CSI None Neck pain C1 lateral mass contusion and bilateral C1–C2 alar ligament injury Unknowna 
6.1 yb Fall (10 ft) Loss of consciousness; axial load Signs of substantial head injury other than altered mental status Neck pain C1–C2 epidural hemorrhage; no fracture or ligamentous disruption None 
7 wk Fall from bed reported, suspected NAT Loss of consciousness Repeat episodes of unresponsiveness and limp tone Altered mental status C1–C4 subdural hemorrhage; no fracture or ligamentous disruption None 
6 mo NAT Arrived from OSH with concern for substantial head injury Irritable; signs of substantial head injury; palpable skull fracture Altered mental status C7–T2 compression deformities with associated C7–T1 ligamentous injury None 
8.3 y MVC >55 MPH Arrived by EMS with concern for substantial head injury GCS 14 at scene; persistent somnolence and confusion; tenderness to neck palpation; sixth nerve palsy Altered mental status; focal neurologic deficit C2 ventral subdural hematoma None 
3.8 y Fall from bench hitting head on a table Transferred with concern for CSI; complained of neck pain and holding neck Occipital laceration; tenderness to palpation of the posterior midline neck Neck pain C1 posterior synchondrosis fracture Rigid cervical collar 

ATV, all-terrain vehicle; GCS, Glasgow Coma Scale; MPH, miles per hour; NAT, non-accidental trauma; OSH, outside hospital.

a

Medical record review lacks information regarding treatment rendered.

b

Subject not missed by de novo model due to axial load biomechanics noted by ED provider.

We included children transferred from other hospitals with imaging. Knowledge of imaging results may have influenced ED providers’ reported risk factor observations. This potential bias was mitigated by efforts to capture ED providers’ observations before radiologists overread outside imaging. Including children transferred from outlying hospitals was important to ensure that the study population was representative of the entire injured population. Importantly, a subanalysis that included only children presenting directly to the study sites yielded similar prediction model sensitivity and specificity estimates. The analyses were underpowered to provide narrow CIs around ORs and RRs point estimates for uncommon risk factors and therefore lacks sufficient power to fully assess model performance characteristics.

In this 4-center prospective observational study of children experiencing blunt trauma, we identified 14 factors that were associated with CSI in bivariable analyses: diving, axial load, clotheslining, loss of consciousness, neck pain, reported inability to move neck, altered mental status, intubation, basilar skull fracture, substantial torso injury, substantial thoracic injury, respiratory distress, decreased oxygen saturation, and focal neurologic deficits. We also demonstrated by multivariable analyses that both the PECARN model (high-risk MVC, diving mechanism, conditions predisposing for CSI, neck pain, reported inability to move neck, altered mental status, limited neck range of motion on exam, substantial torso injury, and focal neurologic deficits) and a de novo model (diving mechanism, axial load biomechanics, neck pain, reported inability to move neck, altered mental status, intubation and respiratory distress) have reasonable test accuracy and the potential to limit imaging if used in clinical decision-making. Collectively, these results support the feasibility of deriving a CSI prediction rule for children.

In this study, we confirm the important association between CSI and head injury. Signs of substantial head injury (basilar skull fracture), signs of traumatic brain injury (altered mental status), respiratory failure and intubation, and head-first impact (diving mechanism and axial load biomechanics) held significant independent associations with CSI. Adult CSI prediction rules for cervical imaging after blunt trauma are contingent on normal mental status for clinical clearance. One argument for this practice is that a patient’s examination is unreliable when mentation is altered. Another compelling argument is that head-first impact predisposes to CSI and that mental status is a good marker for the severity of the head-first, axial load impact and therefore is also a good marker for CSI risk. Future development of a robust pediatric CSI prediction rule should be focused on stratification based on mental status because it may be meaningful in determining which children to triage to CT scan. If the CSI risk based on altered mental status is sufficiently high, this risk would outweigh the risk of CT-related ionizing radiation exposure.

The risk factors identified in this study differ from the adult literature with respect to neck findings. The NEXUS and the Canadian C-spine rules rely on the neck examination, both include posterior midline neck tenderness, and the Canadian C-spine rule also includes lack of normal neck range of motion on examination.17,18,22 Both the PECARN retrospective case-control study of CSI in children and the current study found self-report of neck pain and difficulty moving the neck to be predictive as opposed to being restricted to the examination findings of posterior midline neck tenderness and limited range of motion.32 One possible reason for this difference is that SMR alters physical examination in the ED. Researchers previously demonstrated increased neck and spine tenderness after supine positioning in a cervical collar on a rigid longboard.15,38,40 Another possibility is that ED providers defer aspects of the neck examination for children who arrive in a cervical collar, rendering self-report the only means for assessing these findings. Within this study cohort, ED providers did not assess children transported from the scene of injury by EMS for posterior midline cervical tenderness in 12.3% and neck range of motion in 41.2%.16 

Aside from limited range of neck motion on examination, 2 additional PECARN model risk factors did not maintain their associations with CSI in this study: predisposing conditions and high-risk MVC mechanism.32 Both of these risk factors are included in the Canadian C-spine Rule.22 Predisposing conditions in this cohort had low prevalence, occurring in <1% of children. The main aim of this study was to establish the infrastructure for conducting a larger cohort study and is therefore underpowered for rare findings and those with weaker but significant associations. High-risk MVCs, however, were prevalent within the cohort. Although high-risk MVC did not maintain a significant association with CSI, it may be important in prediction rule derivation when there is a sufficient sample size to pair high-risk mechanisms with physical examination findings to determine CSI risk.

The PECARN model had sufficiently accurate performance characteristics in this cohort that use of the model for clinical decision support would significantly reduce cervical spine imaging, although 7 CSIs would have been missed. De novo modeling revealed that there are opportunities to improve the PECARN model. Both models were similar in that axial load biomechanics, mental status assessment, and neck complaints were important factors associated with CSI. However, the de novo model included respiratory distress and intubation, which could reflect substantial head, chest, or spinal cord injury. This compares to focal neurologic deficits and substantial torso injury in the PECARN model. With larger sample sizes, it is likely that all factors that are signs of severe traumatic brain injury and spinal cord injury would be identified as significant in prediction rule derivation.

Clinical prediction rule use has come under scrutiny by some authors using the argument that physician judgement is rarely assessed in studies for comparison; in those studies where it was assessed, prediction rules seldom improve on it.41 In a separate analysis of this cohort, however, we demonstrated ED provider gestalt for identifying children with CSIs is poor.16 Twenty percent of the children with CSIs in that analysis were rated by providers as having <1% risk for CSI. This is consistent with investigations of head injury in children after blunt trauma.42,43 Furthermore, PECARN developed a decision support tool for imaging children after blunt head trauma.44,46 Implementation of the PECARN head injury rule has repeatedly demonstrated reduction in CT use during the evaluation of children after blunt head trauma.46,50 Developing and implementing clinical prediction rules to aid in identifying children at nonnegligible risk for CSIs after blunt trauma is likely to empower clinical decision-making and appropriate imaging use.

In this prospective cohort of children with blunt trauma, we confirmed that there are risk factors with good test accuracy in identifying CSIs. We also demonstrated that incorporating these risk factors into a clinical prediction rule has the potential to substantially reduce cervical spine imaging during trauma evaluation of children. A future, adequately powered prospective observational study aimed at using these risk factors to construct a definitive pediatric CSI prediction rule is warranted.

Dr J.C. Leonard conceptualized and designed the study, designed the data collection instruments, coordinated and supervised data collection, collaborated on data analyses, and drafted the manuscript; Drs Browne, Ahmad, Schwartz, J.R. Leonard, and Lerner designed the data collection instruments and coordinated and supervised data collection; Dr Wallendorf designed the data collection instruments, managed the data, and conducted the analyses; Dr Kuppermann conceptualized and designed the study, designed the data collection instruments, collaborated on data analyses, and drafted the manuscript; and all authors critically reviewed the manuscript for important intellectual content and approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: Dr J.C. Leonard was supported by Eunice Kennedy Shriver National Institute of Child Health and Human Development grant R21HD076108-02. Funded by the National Institutes of Health (NIH).

We thank the EMS and ED providers, as well as the research staff, whose efforts made this study possible.

     
  • CI

    confidence interval

  •  
  • CSI

    cervical spine injury

  •  
  • CT

    computed tomography

  •  
  • ED

    emergency department

  •  
  • EMS

    emergency medical services

  •  
  • MVC

    motor vehicle crash

  •  
  • NEXUS

    National Emergency X-Radiography Utilization Study

  •  
  • OR

    odds ratio

  •  
  • PECARN

    Pediatric Emergency Care Applied Research Network

  •  
  • RR

    relative risk

  •  
  • SMR

    spinal motion restriction

1
Leonard
JR
,
Jaffe
DM
,
Kuppermann
N
,
Olsen
CS
,
Leonard
JC
;
Pediatric Emergency Care Applied Research Network (PECARN) Cervical Spine Study Group
.
Cervical spine injury patterns in children.
Pediatrics
.
2014
;
133
(
5
). Available at: www.pediatrics.org/cgi/content/full/133/5/e1179
[PubMed]
2
Adelgais
KM
,
Grossman
DC
,
Langer
SG
,
Mann
FA
.
Use of helical computed tomography for imaging the pediatric cervical spine.
Acad Emerg Med
.
2004
;
11
(
3
):
228
236
[PubMed]
3
Broder
J
,
Fordham
LA
,
Warshauer
DM
.
Increasing utilization of computed tomography in the pediatric emergency department, 2000-2006.
Emerg Radiol
.
2007
;
14
(
4
):
227
232
[PubMed]
4
Mannix
R
,
Nigrovic
LE
,
Schutzman
SA
, et al
.
Factors associated with the use of cervical spine computed tomography imaging in pediatric trauma patients.
Acad Emerg Med
.
2011
;
18
(
9
):
905
911
[PubMed]
5
Viccellio
P
,
Simon
H
,
Pressman
BD
,
Shah
MN
,
Mower
WR
,
Hoffman
JR
;
NEXUS Group
.
A prospective multicenter study of cervical spine injury in children.
Pediatrics
.
2001
;
108
(
2
). Available at: www.pediatrics.org/cgi/content/full/108/2/e20
[PubMed]
6
Pearce
MS
,
Salotti
JA
,
Little
MP
, et al
.
Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study.
Lancet
.
2012
;
380
(
9840
):
499
505
[PubMed]
7
Brenner
D
,
Elliston
C
,
Hall
E
,
Berdon
W
.
Estimated risks of radiation-induced fatal cancer from pediatric CT.
AJR Am J Roentgenol
.
2001
;
176
(
2
):
289
296
[PubMed]
8
Brenner
DJ
.
Estimating cancer risks from pediatric CT: going from the qualitative to the quantitative.
Pediatr Radiol
.
2002
;
32
(
4
):
228
221; discussion 242–224
9
Berrington de González
A
,
Mahesh
M
,
Kim
KP
, et al
.
Projected cancer risks from computed tomographic scans performed in the United States in 2007.
Arch Intern Med
.
2009
;
169
(
22
):
2071
2077
[PubMed]
10
Adams
MJ
,
Shore
RE
,
Dozier
A
, et al
.
Thyroid cancer risk 40+ years after irradiation for an enlarged thymus: an update of the Hempelmann cohort.
Radiat Res
.
2010
;
174
(
6
):
753
762
[PubMed]
11
Bhatti
P
,
Veiga
LH
,
Ronckers
CM
, et al
.
Risk of second primary thyroid cancer after radiotherapy for a childhood cancer in a large cohort study: an update from the childhood cancer survivor study.
Radiat Res
.
2010
;
174
(
6
):
741
752
[PubMed]
12
Mathews
JD
,
Forsythe
AV
,
Brady
Z
, et al
.
Cancer risk in 680,000 people exposed to computed tomography scans in childhood or adolescence: data linkage study of 11 million Australians.
BMJ
.
2013
;
346
:
f2360
[PubMed]
13
Muchow
RD
,
Egan
KR
,
Peppler
WW
,
Anderson
PA
.
Theoretical increase of thyroid cancer induction from cervical spine multidetector computed tomography in pediatric trauma patients.
J Trauma Acute Care Surg
.
2012
;
72
(
2
):
403
409
[PubMed]
14
Ron
E
,
Lubin
JH
,
Shore
RE
, et al
.
Thyroid cancer after exposure to external radiation: a pooled analysis of seven studies.
Radiat Res
.
1995
;
141
(
3
):
259
277
[PubMed]
15
Leonard
JC
,
Mao
J
,
Jaffe
DM
.
Potential adverse effects of spinal immobilization in children.
Prehosp Emerg Care
.
2012
;
16
(
4
):
513
518
16
Browne
LR
,
Schwartz
H
,
Ahmad
FA
, et al
.
Interobserver agreement in pediatric cervical spine injury assessment between prehospital and emergency department providers.
Acad Emerg Med
.
2017
;
24
(
12
):
1501
1510
[PubMed]
17
Hoffman
JR
,
Mower
WR
,
Wolfson
AB
,
Todd
KH
,
Zucker
MI
;
National Emergency X-Radiography Utilization Study Group
.
Validity of a set of clinical criteria to rule out injury to the cervical spine in patients with blunt trauma.
N Engl J Med
.
2000
;
343
(
2
):
94
99
[PubMed]
18
Hoffman
JR
,
Schriger
DL
,
Mower
W
,
Luo
JS
,
Zucker
M
.
Low-risk criteria for cervical-spine radiography in blunt trauma: a prospective study.
Ann Emerg Med
.
1992
;
21
(
12
):
1454
1460
[PubMed]
19
Mahadevan
S
,
Mower
WR
,
Hoffman
JR
,
Peeples
N
,
Goldberg
W
,
Sonner
R
.
Interrater reliability of cervical spine injury criteria in patients with blunt trauma.
Ann Emerg Med
.
1998
;
31
(
2
):
197
201
[PubMed]
20
Touger
M
,
Gennis
P
,
Nathanson
N
, et al
.
Validity of a decision rule to reduce cervical spine radiography in elderly patients with blunt trauma.
Ann Emerg Med
.
2002
;
40
(
3
):
287
293
[PubMed]
21
Stiell
IG
,
Clement
CM
,
McKnight
RD
, et al
.
The Canadian C-spine rule versus the NEXUS low-risk criteria in patients with trauma.
N Engl J Med
.
2003
;
349
(
26
):
2510
2518
[PubMed]
22
Stiell
IG
,
Wells
GA
,
Vandemheen
KL
, et al
.
The Canadian C-spine rule for radiography in alert and stable trauma patients.
JAMA
.
2001
;
286
(
15
):
1841
1848
[PubMed]
23
Stiell
IG
,
Clement
CM
,
Grimshaw
J
, et al
.
Implementation of the Canadian C-Spine rule: prospective 12 centre cluster randomised trial.
BMJ
.
2009
;
339
:
b4146
[PubMed]
24
Domeier
RM
,
Swor
RA
,
Evans
RW
, et al
.
Multicenter prospective validation of prehospital clinical spinal clearance criteria.
J Trauma
.
2002
;
53
(
4
):
744
750
[PubMed]
25
Muhr
D
,
Seabrook
DL
,
Wittwer
LK
.
Paramedic use of a spinal injury clearance algorithm reduces spinal immobilization in the out-of-hospital setting.
Prehosp Emerg Care
.
1999
;
3
(
1
):
1
6
26
Sahni
R
,
Menegazzi
JJ
,
Mosesso
VN
 Jr
.
Paramedic evaluation of clinical indicators of cervical spinal injury.
Prehosp Emerg Care
.
1997
;
1
(
1
):
16
18
27
Maxwell
MJ
,
Jardine
AD
.
Paediatric cervical spine injury but NEXUS negative.
Emerg Med J
.
2007
;
24
(
9
):
676
[PubMed]
28
Rachesky
I
,
Boyce
WT
,
Duncan
B
,
Bjelland
J
,
Sibley
B
.
Clinical prediction of cervical spine injuries in children. Radiographic abnormalities.
Am J Dis Child
.
1987
;
141
(
2
):
199
201
[PubMed]
29
Binns
H
,
Jaffe
DM
,
Radkowski
MA
,
Barthel
MJ
,
Engelhard
HH
 III
.
An eight-variable clinical assessment model for the prediction of cervical spine injury in children.
Am J Dis Child
.
1987
;
141
(
12
):
1249
1250
[PubMed]
30
Jaffe
DM
,
Binns
H
,
Radkowski
MA
,
Barthel
MJ
,
Engelhard
HH
 III
.
Developing a clinical algorithm for early management of cervical spine injury in child trauma victims.
Ann Emerg Med
.
1987
;
16
(
3
):
270
276
[PubMed]
31
Leonard
JC
,
Jaffe
DM
,
Olsen
CS
,
Kuppermann
N
.
Age-related differences in factors associated with cervical spine injuries in children.
Acad Emerg Med
.
2015
;
22
(
4
):
441
446
[PubMed]
32
Leonard
JC
,
Kuppermann
N
,
Olsen
C
, et al;
Pediatric Emergency Care Applied Research Network
.
Factors associated with cervical spine injury in children after blunt trauma.
Ann Emerg Med
.
2011
;
58
(
2
):
145
155
[PubMed]
33
Ahmad
FA
,
Schwartz
H
,
Browne
LR
, et al
.
Methods for collecting paired observations from emergency medical services and emergency department providers for pediatric cervical spine injury risk factors.
Acad Emerg Med
.
2017
;
24
(
4
):
432
441
[PubMed]
34
Olsen
CS
,
Kuppermann
N
,
Jaffe
DM
, et al;
Pediatric Emergency Care Applied Research Network (PECARN) Cervical Spine Injury Study Group
.
Interobserver agreement in retrospective chart reviews for factors associated with cervical spine injuries in children.
Acad Emerg Med
.
2015
;
22
(
4
):
487
491
[PubMed]
35
Gorelick
MH
,
Atabaki
SM
,
Hoyle
J
, et al;
Pediatric Emergency Care Applied Research Network
.
Interobserver agreement in assessment of clinical variables in children with blunt head trauma.
Acad Emerg Med
.
2008
;
15
(
9
):
812
818
[PubMed]
36
Yen
K
,
Kuppermann
N
,
Lillis
K
, et al;
Intra-Abdominal Injury Study Group for the Pediatric Emergency Care Applied Research Network (PECARN)
.
Interobserver agreement in the clinical assessment of children with blunt abdominal trauma.
Acad Emerg Med
.
2013
;
20
(
5
):
426
432
[PubMed]
37
Sasser
SM
,
Hunt
RC
,
Faul
M
, et al;
Centers for Disease Control and Prevention (CDC)
.
Guidelines for field triage of injured patients: recommendations of the National Expert Panel on Field Triage, 2011.
MMWR Recomm Rep
.
2012
;
61
(
RR-1
):
1
20
38
Chan
D
,
Goldberg
R
,
Tascone
A
,
Harmon
S
,
Chan
L
.
The effect of spinal immobilization on healthy volunteers.
Ann Emerg Med
.
1994
;
23
(
1
):
48
51
[PubMed]
39
Cordell
WH
,
Hollingsworth
JC
,
Olinger
ML
,
Stroman
SJ
,
Nelson
DR
.
Pain and tissue-interface pressures during spine-board immobilization.
Ann Emerg Med
.
1995
;
26
(
1
):
31
36
[PubMed]
40
Cross
DA
,
Baskerville
J
.
Comparison of perceived pain with different immobilization techniques.
Prehosp Emerg Care
.
2001
;
5
(
3
):
270
274
41
Schriger
DL
,
Elder
JW
,
Cooper
RJ
.
Structured clinical decision aids are seldom compared with subjective physician judgment, and are seldom superior.
Ann Emerg Med
.
2017
;
70
(
3
):
338
344.e3
42
Palchak
MJ
,
Holmes
JF
,
Kuppermann
N
.
Clinician judgment versus a decision rule for identifying children at risk of traumatic brain injury on computed tomography after blunt head trauma.
Pediatr Emerg Care
.
2009
;
25
(
2
):
61
65
[PubMed]
43
Atabaki
SM
,
Hoyle
JD
 Jr
,
Schunk
JE
, et al
.
Comparison of prediction rules and clinician suspicion for identifying children with clinically important brain injuries after blunt head trauma.
Acad Emerg Med
.
2016
;
23
(
5
):
566
575
[PubMed]
44
Kuppermann
N
,
Holmes
JF
,
Dayan
PS
, et al;
Pediatric Emergency Care Applied Research Network (PECARN)
.
Identification of children at very low risk of clinically-important brain injuries after head trauma: a prospective cohort study.
Lancet
.
2009
;
374
(
9696
):
1160
1170
[PubMed]
45
Tham
E
,
Swietlik
M
,
Deakyne
S
, et al;
Pediatric Emergency Care Applied Research Network (PECARN)
.
Clinical decision support for a multicenter trial of pediatric head trauma: development, implementation, and lessons learned.
Appl Clin Inform
.
2016
;
7
(
2
):
534
542
[PubMed]
46
Dayan
PS
,
Ballard
DW
,
Tham
E
, et al;
Pediatric Emergency Care Applied Research Network (PECARN)
;
Clinical Research on Emergency Services and Treatment (CREST) Network
;
and Partners Healthcare
;
Traumatic Brain Injury-Knowledge Translation Study Group
.
Use of traumatic brain injury prediction rules with clinical decision support.
Pediatrics
.
2017
;
139
(
4
):
e20162709
[PubMed]
47
Jennings
RM
,
Burtner
JJ
,
Pellicer
JF
, et al
.
Reducing head CT use for children with head injuries in a community emergency department.
Pediatrics
.
2017
;
139
(
4
):
e20161349
[PubMed]
48
Lorton
F
,
Poullaouec
C
,
Legallais
E
, et al
.
Validation of the PECARN clinical decision rule for children with minor head trauma: a French multicenter prospective study.
Scand J Trauma Resusc Emerg Med
.
2016
;
24
:
98
[PubMed]
49
Nigrovic
LE
,
Stack
AM
,
Mannix
RC
, et al
.
Quality improvement effort to reduce cranial CTs for children with minor blunt head trauma.
Pediatrics
.
2015
;
136
(
1
). Available at: www.pediatrics.org/cgi/content/full/136/1/e227
[PubMed]
50
Schonfeld
D
,
Bressan
S
,
Da Dalt
L
,
Henien
MN
,
Winnett
JA
,
Nigrovic
LE
.
Pediatric Emergency Care Applied Research Network head injury clinical prediction rules are reliable in practice.
Arch Dis Child
.
2014
;
99
(
5
):
427
431
[PubMed]

Competing Interests

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

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

Supplementary data