Background: Clinical decision support (CDS) may improve the postneuroimaging management of children with mild traumatic brain injuries (mTBI) and intracranial injuries. While the CHIIDA score has been proposed for this purpose, a more sensitive risk model may have broader use. Consequently, this study's objectives were to: (1) develop a new risk model with improved sensitivity compared to the CHIIDA model and (2) externally validate the new model and CHIIDA model in a multicenter data set. Methods:We analyzed children ≤18 years old with mTBI and intracranial injuries included in the PECARN head injury data set (2004)(2005)(2006). We used binary recursive partitioning to predict the composite outcome of neurosurgical intervention,

Please list the following information on your separate title page in Word .DOC format in the order listed below and upload as a Title Page file at submission 1. Manuscript Title (50 word maximum) Components of Endocannabinoid Signaling System are Expressed in the Perinatal Mouse Cerebellum and Required for its Normal Development 2. Abbreviated Title (50 character maximum) Endocannabinoids Shape Cerebellar Development 3. List all Author Names and Affiliations in order as they would appear in the published article

OBJECTIVEThe purpose of this study is to determine if the preoperative Pediatric Quality of Life Inventory (PedsQL) score is predictive of short- and intermediate-term PedsQL outcomes following Chiari decompression surgery. The utility of preoperative patient-reported outcomes (PROs) in predicting pain, opioid consumption, and long-term PROs has been demonstrated in adult spine surgery. To the best of the authors’ knowledge, however, there is currently no widely accepted tool to predict short-, intermediate-, or long-term outcomes after pediatric Chiari decompression surgery.METHODSA prospectively maintained database was retrospectively reviewed. Patients who had undergone first-time decompression for symptomatic Chiari malformation were identified and grouped according to their preoperative PedsQL scores: mild disability (score 80–100), moderate disability (score 60–79), and severe disability (score < 60). PedsQL scores at the 6-week, 3-month, and/or 6-month follow-ups were collected. Preoperative PedsQL subgroups were tested for an association with demographic and perioperative characteristics using one-way ANOVA or chi-square analysis. Preoperative PedsQL subgroups were tested for an association with improvements in short- and intermediate-term PedsQL scores using one-way ANOVA and a paired Wilcoxon signed-rank test controlling for statistically different demographic characteristics when appropriate.RESULTSA total of 87 patients were included in this analysis. According to their preoperative PedsQL scores, 28% of patients had mild disability, 40% had moderate disability, and 32% had severe disability. There was a significant difference in the prevalence of comorbidities (p = 0.009) and the presenting symptoms of headaches (p = 0.032) and myelopathy (p = 0.047) among the subgroups; however, in terms of other demographic or operative factors, there was no significant difference. Patients with greater preoperative disability demonstrated statistically significantly lower PedsQL scores at all postoperative time points, except in terms of the parent-reported PedsQL at 6 months after surgery (p = 0.195). Patients with severe disability demonstrated statistically significantly greater improvements (compared to preoperative scores) in PedsQL scores at all time points after surgery, except in terms of the 6-week and 6-month PROs and the 6-month parent-reported outcomes (p = 0.068, 0.483, and 0.076, respectively).CONCLUSIONSPatients with severe disability, as assessed by the PedsQL, had lower absolute PedsQL scores at all time points after surgery but greater improvement in short- and intermediate-term PROs. The authors conclude that the PedsQL is an efficient and accurate tool that can quickly assess patient disability in the preoperative period and predict both short- and intermediate-term surgical outcomes.

Author Contributions: JKG conceived of the study, obtained grant funding, designed the study, conducted data acquisition, analyzed the data with YY, and wrote the initial draft of the paper. DDL conceived of the study, designed the study, helped obtain grant funding, supervised data collection protocols, guided the data analysis plan, interpreted the data, and provided overall study Accepted ArticleThis article is protected by copyright. All rights reserved supervision. NK and REF conceived of the study, designed the study, helped obtain grant funding, guided the data analysis plan, and provided study supervision. LA, CN, EJ, EB, SV, and CS designed the study, supervised data collection protocols, and conducted/directly supervised data acquisition.RA conducted data acquisition. MH, GJ, ATH, AB, and SB conducted data acquisition. YY analyzed the data with JKG. MO and CC helped design the study and analysis plan. CS and NRS contributed substantially to the interpretation of the data.