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Champlain BASE™ (Building Access to Specialists through eConsultation) is a web-based asynchronous electronic communication service that allows primary-care- practitioners (PCPs) to submit \"elective\" clinical questions to a specialist. For adults, PCPs have reported improved access and timeliness to specialist advice, averted face-to-face specialist referrals in up to 40% of cases and high provider satisfaction. To determine whether the expansion of eConsult to a pediatric setting would result in similar measures of improved healthcare system process and high provider acceptance reported in adults. Prospective observational cohort study. Single Canadian tertiary-care academic pediatric hospital (June 2014-16) servicing 1.2 million people. 1. PCPs already using eConsult. 2.Volunteer pediatric specialists provided services in addition to their regular workload. 3.Pediatric patients (< 18 years-old) referred for none-acute care conditions. Specialty service utilization and access, impact on PCP course-of-action and referral-patterns and survey-based provider satisfaction data were collected. 1064 eConsult requests from 367 PCPs were answered by 23 pediatric specialists representing 14 specialty-services. The top three specialties represented were: General Pediatrics 393 cases (36.9%), Orthopedics 162 (15.2%) and Psychiatry 123 (11.6%). Median specialist response time was 0.9 days (range <1 hour-27 days), most consults (63.2%) required <10minutes to complete and 21/21(100%) specialist survey-respondents reported minimal workload burden. For 515/1064(48.4%) referrals, PCPs received advice for a new or additional course of action; 391/1064(36.7%) referrals resulted in an averted face-to-face specialist visit. In 9 specialties with complete data, the median wait-time was significantly less (p<0.001) for an eConsult (1 day, 95%CI:0.9-1.2) compared with a face-to-face referral (132 days; 95%CI:127-136). The majority (>93.3%) of PCPs rated eConsult as very good/excellent value for both patients and themselves. All specialist survey-respondents indicated eConsult should be a continued service. Similar to adults, eConsult improves PCP access and timeliness to elective pediatric specialist advice and influences their care decisions, while reporting high end-user satisfaction. Further study is warranted to assess impact on resource utilization and clinical outcomes.

In the largest sample studied to date, white matter microstructural trajectories and their relation to persistent symptoms were examined after pediatric mild traumatic brain injury (mTBI). This prospective, longitudinal cohort study recruited children aged 8–16.99 years with mTBI or mild orthopedic injury (OI) from five pediatric emergency departments. Children's pre‐injury and 1‐month post‐injury symptom ratings were used to classify mTBI with or without persistent symptoms. Children completed diffusion‐weighted imaging at post‐acute (2–33 days post‐injury) and chronic (3 or 6 months via random assignment) post‐injury assessments. Mean diffusivity (MD) and fractional anisotropy (FA) were derived for 18 white matter tracts in 560 children (362 mTBI/198 OI), 407 with longitudinal data. Superior longitudinal fasciculus FA was higher in mTBI without persistent symptoms relative to OI, d (95% confidence interval) = 0.31 to 0.37 (0.02, 0.68), across time. In younger children, MD of the anterior thalamic radiations was higher in mTBI with persistent symptoms relative to both mTBI without persistent symptoms, 1.43 (0.59, 2.27), and OI, 1.94 (1.07, 2.81). MD of the arcuate fasciculus, −0.58 (−1.04, −0.11), and superior longitudinal fasciculus, −0.49 (−0.90, −0.09) was lower in mTBI without persistent symptoms relative to OI at 6 months post‐injury. White matter microstructural changes suggesting neuroinflammation and axonal swelling occurred chronically and continued 6 months post injury in children with mTBI, especially in younger children with persistent symptoms, relative to OI. White matter microstructure appears more organized in children without persistent symptoms, consistent with their better clinical outcomes. In the largest sample studied to date, white matter microstructural trajectories and their relation to persistent symptoms were examined after pediatric mild traumatic brain injury (mTBI). White matter microstructural changes suggesting neuroinflammation and axonal swelling continued 6 months post‐injury in children with mTBI, especially in younger children when symptoms are persistent, relative to OI. White matter microstructure appears more organized in children without persistent symptoms, consistent with better clinical outcomes.

IntroductionPaediatric mild traumatic brain injury (mTBI) is a public health burden. Clinicians urgently need evidence-based guidance to manage mTBI, but gold standards for diagnosing and predicting the outcomes of mTBI are lacking. The objective of the Advancing Concussion Assessment in Pediatrics (A-CAP) study is to assess a broad pool of neurobiological and psychosocial markers to examine associations with postinjury outcomes in a large sample of children with either mTBI or orthopaedic injury (OI), with the goal of improving the diagnosis and prognostication of outcomes of paediatric mTBI.Methods and analysisA-CAP is a prospective, longitudinal cohort study of children aged 8.00–16.99 years with either mTBI or OI, recruited during acute emergency department (ED) visits at five sites from the Pediatric Emergency Research Canada network. Injury information is collected in the ED; follow-up assessments at 10 days and 3 and 6 months postinjury measure a variety of neurobiological and psychosocial markers, covariates/confounders and outcomes. Weekly postconcussive symptom ratings are obtained electronically. Recruitment began in September 2016 and will occur for approximately 24 months. Analyses will test the major hypotheses that neurobiological and psychosocial markers can: (1) differentiate mTBI from OI and (2) predict outcomes of mTBI. Models initially will focus within domains (eg, genes, imaging biomarkers, psychosocial markers), followed by multivariable modelling across domains. The planned sample size (700 mTBI, 300 OI) provides adequate statistical power and allows for internal cross-validation of some analyses.Ethics and disseminationThe ethics boards at all participating institutions have approved the study and all participants and their parents will provide informed consent or assent. Dissemination will follow an integrated knowledge translation plan, with study findings presented at scientific conferences and in multiple manuscripts in peer-reviewed journals.

Concussion is commonly characterized by a cascade of neurometabolic changes following injury. Magnetic Resonance Spectroscopy (MRS) can be used to quantify neurometabolites non-invasively. Longitudinal changes in neurometabolites have rarely been studied in pediatric concussion, and fewer studies consider symptoms. This study examines longitudinal changes of neurometabolites in pediatric concussion and associations between neurometabolites and symptom burden. Participants who presented with concussion or orthopedic injury (OI, comparison group) were recruited. The first timepoint for MRS data collection was at a mean of 12 days post-injury (n = 545). Participants were then randomized to 3 (n = 243) or 6 (n = 215) months for MRS follow-up. Parents completed symptom questionnaires to quantify somatic and cognitive symptoms at multiple timepoints following injury. There were no significant changes in neurometabolites over time in the concussion group and neurometabolite trajectories did not differ between asymptomatic concussion, symptomatic concussion, and OI groups. Cross-sectionally, Choline was significantly lower in those with persistent somatic symptoms compared to OI controls at 3 months post-injury. Lower Choline was also significantly associated with higher somatic symptoms. Although overall neurometabolites do not change over time, choline differences that appear at 3 months and is related to somatic symptoms.

IntroductionPaediatric mild traumatic brain injury (mTBI) is a public health burden. Clinicians urgently need evidence-based guidance to manage mTBI, but gold standards for diagnosing and predicting the outcomes of mTBI are lacking. The objective of the Advancing Concussion Assessment in Pediatrics (A-CAP) study is to assess a broad pool of neurobiological and psychosocial markers to examine associations with postinjury outcomes in a large sample of children with either mTBI or orthopaedic injury (OI), with the goal of improving the diagnosis and prognostication of outcomes of paediatric mTBI.Methods and analysisA-CAP is a prospective, longitudinal cohort study of children aged 8.00–16.99 years with either mTBI or OI, recruited during acute emergency department (ED) visits at five sites from the Pediatric Emergency Research Canada network. Injury information is collected in the ED; follow-up assessments at 10 days and 3 and 6 months postinjury measure a variety of neurobiological and psychosocial markers, covariates/confounders and outcomes. Weekly postconcussive symptom ratings are obtained electronically. Recruitment began in September 2016 and will occur for approximately 24 months. Analyses will test the major hypotheses that neurobiological and psychosocial markers can: (1) differentiate mTBI from OI and (2) predict outcomes of mTBI. Models initially will focus within domains (eg, genes, imaging biomarkers, psychosocial markers), followed by multivariable modelling across domains. The planned sample size (700 mTBI, 300 OI) provides adequate statistical power and allows for internal cross-validation of some analyses.Ethics and disseminationThe ethics boards at all participating institutions have approved the study and all participants and their parents will provide informed consent or assent. Dissemination will follow an integrated knowledge translation plan, with study findings presented at scientific conferences and in multiple manuscripts in peer-reviewed journals.

Importance Headache is the most common symptom after pediatric concussion. Objectives To examine whether posttraumatic headache phenotype is associated with symptom burden and quality of life 3 months after concussion. Design, Setting, and Participants This was a secondary analysis of the Advancing Concussion Assessment in Pediatrics (A-CAP) prospective cohort study, conducted September 2016 to July 2019 at 5 Pediatric Emergency Research Canada (PERC) network emergency departments. Children aged 8.0-16.99 years presenting with acute (<48 hours) concussion or orthopedic injury (OI) were included. Data were analyzed from April to December 2022. Exposure Posttraumatic headache was classified as migraine or nonmigraine headache, or no headache, using modified International Classification of Headache Disorders, 3rd edition, diagnostic criteria based on self-reported symptoms collected within 10 days of injury. Main Outcomes and Measures Self-reported postconcussion symptoms and quality-of-life were measured at 3 months after concussion using the validated Health and Behavior Inventory (HBI) and Pediatric Quality of Life Inventory–Version 4.0 (PedsQL-4.0). An initial multiple imputation approach was used to minimize potential biases due to missing data. Multivariable linear regression evaluated the association between headache phenotype and outcomes compared with the Predicting and Preventing Postconcussive Problems in Pediatrics (5P) clinical risk score and other covariates and confounders. Reliable change analyses examined clinical significance of findings. Results Of 967 enrolled children, 928 (median [IQR] age, 12.2 [10.5 to 14.3] years; 383 [41.3%] female) were included in analyses. HBI total score (adjusted) was significantly higher for children with migraine than children without headache (estimated mean difference [EMD], 3.36; 95% CI, 1.13 to 5.60) and children with OI (EMD, 3.10; 95% CI, 0.75 to 6.62), but not children with nonmigraine headache (EMD, 1.93; 95% CI, −0.33 to 4.19). Children with migraine were more likely to report reliable increases in total symptoms (odds ratio [OR], 2.13; 95% CI, 1.02 to 4.45) and somatic symptoms (OR, 2.70; 95% CI, 1.29 to 5.68) than those without headache. PedsQL-4.0 subscale scores were significantly lower for children with migraine than those without headache only for physical functioning (EMD, −4.67; 95% CI, −7.86 to −1.48). Conclusions and Relevance In this cohort study of children with concussion or OI, those with posttraumatic migraine symptoms after concussion had higher symptom burden and lower quality of life 3 months after injury than those with nonmigraine headache. Children without posttraumatic headache reported the lowest symptom burden and highest quality of life, comparable with children with OI. Further research is warranted to determine effective treatment strategies that consider headache phenotype.

Thinly collimated multidetector CT (MDCT) with coronal and sagittal reformats have recently been reported to visualize the inguinal ligament and associated structures with a higher accuracy than in thickly collimated axial images.3 MDCT findings distinguishing between femoral and inguinal hernias have also been described.4,5 A comprehensive, easily applied approach to the differential diagnosis of groin hernias is required. Inguinal anatomy The inguinal region comprises the inguinal canal and the femoral triangle.6 Inguinal canal The inguinal canal extends between the deep inguinal ring (defect in the transversalis fascia) and superficial inguinal ring (triangular defect in the medial portion of the external oblique aponeurosis).

Polymicrogyria (PMG) is a disorder of cortical organization mainly seen in children, which can be associated with seizures, developmental delay and motor weakness. PMG is typically diagnosed on magnetic resonance imaging (MRI) but some cases can be challenging to detect even for experienced radiologists. In this study, we create an open pediatric MRI dataset (PPMR) with PMG and controls from the Children's Hospital of Eastern Ontario (CHEO), Ottawa, Canada. The differences between PMG MRIs and control MRIs are subtle and the true distribution of the features of the disease is unknown. This makes automatic detection of cases of potential PMG in MRI difficult. We propose an anomaly detection method based on a novel center-based deep contrastive metric learning loss function (cDCM) which enables the automatic detection of cases of potential PMG. Additionally, based on our proposed loss function, we customize a deep learning model structure that integrates dilated convolution, squeeze-and-excitation blocks and feature fusion for our PPMR dataset. Despite working with a small and imbalanced dataset our method achieves 92.01% recall at 55.04% precision. This will facilitate a computer aided tool for radiologists to select potential PMG MRIs. To the best of our knowledge, this research is the first to apply machine learning techniques to identify PMG from MRI only.