Pediatric Emergency Care Applied Research Network (PECARN)

Pediatric Emergency Care Applied Research Network (PECARN)

see PECARN traumatic brain injury algorithm.

The overuse of CT leads to inefficient care. Therefore, to maximize precision and minimize the overuse of CT, the Pediatric Emergency Care Applied Research Network (PECARN) previously derived clinical prediction rules for identifying children at high risk and very low risk for intra-abdominal trauma undergoing acute intervention and clinically important traumatic brain injury after blunt trauma in large cohorts of children who are injured.

A study aimed to validate the IAI and age-based TBI clinical prediction rules for identifying children at high risk and very low risk for IAIs undergoing acute intervention and clinically important TBIs after blunt trauma.

This was a prospective 6-center observational study of children aged <18 years with the blunt torso or head trauma. Consistent with the original derivation studies, enrolled children underwent a routine history and physical examinations, and the treating clinicians completed case report forms prior to knowledge of CT results (if performed). Medical records were reviewed to determine clinical courses and outcomes for all patients, and for those who were discharged from the emergency department, a follow-up survey via a telephone call or SMS text message was performed to identify any patients with missed IAIs or TBIs. The primary outcomes were IAI undergoing acute intervention (therapeutic laparotomy, angiographic embolization, blood transfusion, or intravenous fluid for ≥2 days for pancreatic or gastrointestinal injuries) and clinically important TBI (death from TBI, neurosurgical procedure, intubation for >24 hours for TBI, or hospital admission of ≥2 nights due to a TBI on CT). Prediction rule accuracy was assessed by measuring rule classification performance, using a standard point and 95% CI estimates of the operational characteristics of each prediction rule (sensitivity, specificity, positive and negative predictive values, and diagnostic likelihood ratios).

The project was funded in 2016, and enrollment was completed on September 1, 2021. Data analyses are expected to be completed by December 2022, and the primary study results are expected to be submitted for publication in 2023.

This study will attempt to validate previously derived clinical prediction rules to accurately identify children at high and very low risk for clinically important intra-abdominal trauma and traumatic brain injury. Assuming successful validation, widespread implementation is then indicated, which will optimize the care of children who are injured by better aligning CT use with need.

International registered report identifier (irrid): RR1-10.2196/43027 1).

Blunt head trauma is common in children and a common reason for presentation to an emergency department. Head CT involves radiation exposure and the risk of fatal radiation-related malignancy increases with younger age at CT 2). The PECARN flow diagram flags assessment features that increase the risk of ci-TBI and weigh them against the risk of radiation exposure. Therefore, it is useful in avoiding unnecessary radiation exposure in younger patients, where it is safe to do so, and identifying those at risk that require further investigation.

In PECARN, altered mental status was defined as GCS 14 or agitation, somnolence, repetitive questioning, or slow response to verbal communication.

Severe mechanisms of injuries including:

motor vehicle crash with patient ejection

death of another passenger, or rollover

pedestrian or bicyclist without helmet struck by a motorized vehicle falls

more than 1.5 m (5 feet) for patients aged 2 years and older

more than 0.9 m (3 feet) for those younger than 2 years

head struck by a high-impact object

The algorithm was created from patients presenting to an emergency department within 24 hours of the trauma and with blunt trauma only.

Excluded criteria included:

penetrating trauma

known brain tumors

pre-existing neurological disorders complicating assessment

neuroimaging at a hospital outside before transfer

and therefore may not apply to patients with these features.

TBI on CT was defined as any of:

intracranial hemorrhage or contusion

cerebral edema

traumatic infarction

diffuse axonal injury

shearing injury

sigmoid sinus thrombosis

midline shift of intracranial contents or signs of brain herniation

diastasis of the skull

pneumocephalus

skull fracture depressed by at least the width of the table of the skull


Kuppermann et al. analyzed 42 412 children (derivation and validation populations: 8502 and 2216 younger than 2 years, and 25 283 and 6411 aged 2 years and older). We obtained CT scans on 14 969 (35.3%); ciTBIs occurred in 376 (0.9%), and 60 (0.1%) underwent neurosurgery. In the validation population, the prediction rule for children younger than 2 years (normal mental status, no scalp hematoma except frontal, no loss of consciousness or loss of consciousness for less than 5 s, non-severe injury mechanism, no palpable skull fracture, and acting normally according to the parents) had a negative predictive value for ciTBI of 1176/1176 (100.0%, 95% CI 99.7-100 0) and sensitivity of 25/25 (100%, 86.3-100.0). 167 (24.1%) of 694 CT-imaged patients younger than 2 years were in this low-risk group. The prediction rule for children aged 2 years and older (normal mental status, no loss of consciousness, no vomiting, non-severe injury mechanism, no signs of basilar skull fracture, and no severe headache) had a negative predictive value of 3798/3800 (99.95%, 99.81-99.99) and sensitivity of 61/63 (96.8%, 89.0-99.6). 446 (20.1%) of 2223 CT-imaged patients aged 2 years and older were in this low-risk group. Neither rule missed neurosurgery in validation populations.

These validated prediction rules identified children at very low risk of ciTBIs for whom CT can routinely be obviated 3).


A study applied two different machine learning (ML) models to diagnose mTBI in a paediatric population collected as part of the paediatric emergency care applied research network (PECARN) study between 2004 and 2006. The models were conducted using 15,271 patients under the age of 18 years with mTBI and had a head CT report. In the conventional model, random forest (RF) ranked the features to reduce data dimensionality and the top ranked features were used to train a shallow artificial neural network (ANN) model. In the second model, a deep ANN applied to classify positive and negative mTBI patients using the entirety of the features available. The dataset was divided into two subsets: 80% for training and 20% for testing using five-fold cross-validation. Accuracy, sensitivity, precision, and specificity were calculated by comparing the model’s prediction outcome to the actual diagnosis for each patient. RF ranked ten clinical demographic features and twelve CT-findings; the hybrid RF-ANN model achieved an average specificity of 99.96%, sensitivity of 95.98%, precision of 99.25%, and accuracy of 99.74% in identifying positive mTBI from negative mTBI subjects. The deep ANN proved its ability to carry out the task efficiently with an average specificity of 99.9%, sensitivity of 99.2%, precision of 99.9%, and accuracy of 99.9%. The performance of the two proposed models demonstrated the feasibility of using ANN to diagnose mTBI in a paediatric population. This is the first study to investigate deep ANN in a paediatric cohort with mTBI using clinical and non-imaging data and diagnose mTBI with balanced sensitivity and specificity using shallow and deep ML models. This method, if validated, would have the potential to reduce the burden of TBI evaluation in EDs and aide clinicians in the decision-making process 4).


1)

Ugalde IT, Chaudhari PP, Badawy M, Ishimine P, McCarten-Gibbs KA, Yen K, Atigapramoj NS, Sage A, Nielsen D, Adelson PD, Upperman J, Tancredi D, Kuppermann N, Holmes JF. Validation of Prediction Rules for Computed Tomography Use in Children With Blunt Abdominal or Blunt Head TraumaProtocol for a Prospective Multicenter Observational Cohort Study. JMIR Res Protoc. 2022 Nov 24;11(11):e43027. doi: 10.2196/43027. PMID: 36422920.
2)

Brenner D, Elliston C, Hall E, Berdon W. Estimated risks of radiation-induced fatal cancer from pediatric CT. AJR Am J Roentgenol. 2001 Feb;176(2):289-96.
3)

Kuppermann N, Holmes JF, Dayan PS, Hoyle JD Jr, Atabaki SM, Holubkov R, Nadel FM, Monroe D, Stanley RM, Borgialli DA, Badawy MK, Schunk JE, Quayle KS, Mahajan P, Lichenstein R, Lillis KA, Tunik MG, Jacobs ES, Callahan JM, Gorelick MH, Glass TF, Lee LK, Bachman MC, Cooper A, Powell EC, Gerardi MJ, Melville KA, Muizelaar JP, Wisner DH, Zuspan SJ, Dean JM, Wootton-Gorges SL; 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 Oct 3;374(9696):1160-70. doi: 10.1016/S0140-6736(09)61558-0. Epub 2009 Sep 14. Erratum in: Lancet. 2014 Jan 25;383(9914):308. PMID: 19758692.
4)

Ellethy H, Chandra SS, Nasrallah FA. The detection of mild traumatic brain injury in paediatrics using artificial neural networks. Comput Biol Med. 2021 Aug;135:104614. doi: 10.1016/j.compbiomed.2021.104614. Epub 2021 Jun 30. PMID: 34229143.

Pediatric cerebrovascular disease epidemiology

Pediatric cerebrovascular disease epidemiology

The incidence of pediatric stroke is 1 in 5000, and if hemiplegic cerebral palsy due to vaso-occlusive stroke is included, the number could be as high as 1 in 3000. Additionally, cerebrovascular disease is 1 of the top 10 causes of death in infants younger than 1 year. Finally, 20% to 30% of children with arterial ischemic stroke will have recurrent strokes, even with treatment. Stroke in children differs from stroke in adults. Not only is it rare, but its presentation is subtle—particularly in infants—and even with a focal hemiplegia there is a wide differential diagnosis. Coagulation mechanisms, the arteries, and the neurological systems are all different in children, and each of these plays a large role in stroke. The causes of pediatric stroke do not include atherosclerosis, so a myriad of other risk factors and associations exist and are unique for each age group. The causes of pediatric stroke are poorly understood, and although this is a fertile area of research, clinical trials in the field are lacking. Currently, any treatment guidelines or tools being used to treat children with stroke either come from the field of adult stroke or are based on empirical information.

More than 95% of children with ischemic stroke have an underlying thrombus occluding an artery or a vein, and our understanding of clot pathogenesis in children is increasing. Whereas in adults, platelet clots predominantly form secondary to atherosclerosis, in children and infants there is likely a higher fibrin composition, which may require a different treatment strategy. Although anticoagulation is typically used, it is not known whether anticoagulation is more effective than aspirin. There are also major clinical challenges, the most significant of which is that the diagnosis is not made and the stroke is missed entirely or that the diagnosis is severely delayed and by the time the diagnosis is made, the infarct is much larger 1).


In 1978 A 10-year review of the Mayo Clinic experience with childhood cerebrovascular disease unrelated to birth, intracranial infection, or trauma identified 69 patients (38 with ischemic stroke, and 31 with subarachnoid or intracerebral hemorrhage). Although children with cerebral infarction had better survival, they experienced more residual disability than children with cerebral hemorrhage. The medical records-linkage system for Rochester, Minnesota residents made it possible for the first time to study cerebrovascular disease in a well-defined childhood population. Records from all medical facilities serving this population (average of 15,834 resident children) showed four strokes over 10 years (average annual incidence rate of 2.52 cases per 100,000 per year) 2).


In 2018 a study reported the period prevalence, incidence, and risk factors of pediatric stroke in Taiwan.

All Taiwan inhabitants aged 1 month to 18 years registered in the National Health Insurance Research Database between 2010 and 2011 were enrolled in this study. Factors including age, sex, location, and household income levels were collected. Incidence, period prevalence, mortality rate, and the possible risks were completely evaluated. Outcomes and results: Hemorrhagic stroke has a significantly higher mortality rate than ischemic stroke (27.6% vs. 10.2%, P<0.05). Risk factors or underlying diseases for stroke were identified in 77.8% of the patients and 16.2% had more than one risk factor. The most common risk factors were vascular diseases (26.3%), infection (14.0%), and cardiac disorders (9.1%).

Infants younger than 2 years, boys, and children in lower socioeconomic status have a significantly higher risk of stroke. Hemorrhagic stroke has a significantly higher mortality rate than ischemic stroke. More than half of the children with stroke had underlying diseases and the causes of hemorrhagic stroke are significantly different from ischemic stroke 3).


In 2019 Surmava et al. sought to evaluate in -Ontario, the incidence and characteristics of pediatric stroke and TIA including care gaps and the predictive value of International Classification of Diseases (ICD) codes.

A retrospective chart review was conducted at 147 Ontario pediatric and adult acute care hospitals. Pediatric stroke and TIA cases (age < 18 years) were identified using ICD-10 code searches in the 2010/11 Canadian Institute for Health Information’s Discharge Abstract Database (CIHI-DAD) and National Ambulatory Care Reporting System (NACRS) databases in the Ontario Stroke Audit.

Among 478 potential pediatric strokes and TIA cases identified in the CIHI-DAD and NACRS databases, 163 were confirmed as cases of stroke and TIA during the 1-year study period. The Ontario stroke and TIA incidence rate was 5.9 per 100,000 children (3.3 ischemic, 1.8 hemorrhagic, and 0.8 TIA). The mean age was 6.4 years (16% neonate). Nearly half were not imaged within 24 h of arrival in emergency and only 56% were given antithrombotic treatment. At discharge, 83 out of 121 (69%) required health care services post-discharge. Overall positive predictive value (PPV) of ICD-10 stroke and TIA codes was 31% (range 5-74%) and yield ranged from 2.4 to 29% for acute stroke or TIA event; code I63 achieved maximal PPV and yield.

This population-based study yielded a higher incidence rate than prior North-American studies. Important care gaps exist including delayed diagnosis, lack of expert care, and departure from published treatment guidelines. Variability in ICD PPV and yield underlines the need for prospective data collection and for improving the pediatric stroke and TIA coding processes 4).


It is believed that the incidence in the Hospital Universitario “Dr. Jose Eleuterio Gonzalez,” Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo Leon, Mexico is higher than it appears.

A study by Garza-Alatorre et al. aimed to assess the incidence and characteristics of pediatric stroke in this university hospital. Likewise, this study seeks to evaluate if a longer symptoms-to-diagnosis time is associated with mortality in patients with ischemic stroke.

Methods: A retrospective study including children with stroke admitted to the UANL University Hospital from January 2013 to December 2016.

Results: A total of 41 patients and 46 stroke episodes were admitted. About 45.7% had an ischemic stroke and 54.3% had a hemorrhagic stroke. Mortality of 24.4% and morbidity of 60.9% were recorded. Regarding ischemic and hemorrhagic stroke, and increased symptoms-to-diagnosis time and a higher mortality were obtained with a relative risk of 2.667 (95% confidence interval [CI]: 1.09-6.524, p = 0.013) and 8.0 (95% CI: 2.18-29.24, p = < 0.0001), respectively. A continuous increase in the incidence rate, ranging from 4.57 to 13.21 per 1,000 admissions comparing the first period (2013) versus the last period (2016), p = 0.02, was found in our center.

Pediatric stroke is a rare disease; however, its incidence shows a continuous increase. More awareness toward pediatric stroke is needed 5).


1)

Bowers KJ, Deveber GA, Ferriero DM, Roach ES, Vexler ZS, Maria BL. Cerebrovascular disease in children: recent advances in diagnosis and management. J Child Neurol. 2011 Sep;26(9):1074-100. doi: 10.1177/0883073811413585. Epub 2011 Jul 21. PMID: 21778188; PMCID: PMC5289387.
2)

Schoenberg BS, Mellinger JF, Schoenberg DG. Cerebrovascular disease in infants and children: a study of incidence, clinical features, and survival. Neurology. 1978 Aug;28(8):763-8. doi: 10.1212/wnl.28.8.763. PMID: 567292.
3)

Chiang KL, Cheng CY. Epidemiology, risk factors and characteristics of pediatric stroke: a nationwide population-based study. QJM. 2018 Jul 1;111(7):445-454. doi: 10.1093/qjmed/hcy066. PMID: 29648667.
4)

Surmava AM, Maclagan LC, Khan F, Kapral MK, Hall RE, deVeber G. Incidence and Current Treatment Gaps in Pediatric Stroke and TIA: An Ontario-Wide Population-Based Study. Neuroepidemiology. 2019;52(3-4):119-127. doi: 10.1159/000493140. Epub 2019 Jan 17. PMID: 30654369.
5)

Garza-Alatorre G, Carrion-Garcia AL, Falcon-Delgado A, Garza-Davila EC, Martinez-Ponce de Leon AR, Botello-Hernandez E. Characteristics of Pediatric Stroke and Association of Delayed Diagnosis with Mortality in a Mexican Tertiary Care Hospital. Neuropediatrics. 2021 Jul 14. doi: 10.1055/s-0041-1731802. Epub ahead of print. PMID: 34261144.

Pediatric traumatic brain injury guidelines

Pediatric traumatic brain injury guidelines

see Guidelines for the Management of Pediatric Severe Traumatic Brain Injury, Third Edition

In a systematic review and guideline appraisal for pediatric clinical practice guidelines (CPGs) concerning the acute management of Pediatric Traumatic Brain Injury. Targeted guideline creation specific to the pediatric population has the potential to improve the quality of acute TBI clinical practice guidelines (CPGs).

Furthermore, it is crucial to address the applicability of a guideline to translate the CPG from a published manuscript into clinically relevant local practice tools and for resource limited practice settings 1).

Guidelines for Diagnosing and Managing Pediatric Concussion

Guidelines.


Thromboprophylaxis in Traumatic brain injury:

Low-molecular-weight heparin (LMWH) prophylaxis in pediatric traumatic brain injury appears to be more effective than unfractionated heparin (UH) in preventing venous thromboembolism (VTE). Large, multicenter prospective studies are warranted to confirm the superiority of LMWH over UH in pediatric patients with traumatic brain injury. Moreover, outcomes of VTE prophylaxis in the very young remain understudied; therefore, dedicated studies to evaluate this population are needed 2).


1)

Appenteng R, Nelp T, Abdelgadir J, Weledji N, Haglund M, Smith E, Obiga O, Sakita FM, Miguel EA, Vissoci CM, Rice H, Vissoci JRN, Staton C. A systematic review and quality analysis of pediatric traumatic brain injury clinical practice guidelines. PLoS One. 2018 Aug 2;13(8):e0201550. doi: 10.1371/journal.pone.0201550. eCollection 2018. PubMed PMID: 30071052; PubMed Central PMCID: PMC6072093.
2)

van Erp IA, Gaitanidis A, El Moheb M, Kaafarani HMA, Saillant N, Duhaime AC, Mendoza AE. Low-molecular-weight heparin versus unfractionated heparin in pediatric traumatic brain injury. J Neurosurg Pediatr. 2021 Feb 12:1-6. doi: 10.3171/2020.9.PEDS20615. Epub ahead of print. PMID: 33578391.
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