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Background and ObjectivesPathogenic variants in the neuronal sodium channel α1 subunit gene (SCN1A) are the most frequent monogenic cause of epilepsy. Phenotypes comprise a wide clinical spectrum, including severe childhood epilepsy; Dravet syndrome, characterized by drug-resistant seizures, intellectual disability, and high mortality; and the milder genetic epilepsy with febrile seizures plus (GEFS+), characterized by normal cognition. Early recognition of a child's risk for developing Dravet syndrome vs GEFS+ is key for implementing disease-modifying therapies when available before cognitive impairment emerges. Our objective was to develop and validate a prediction model using clinical and genetic biomarkers for early diagnosis of SCN1A-related epilepsies.MethodsWe performed a retrospective multicenter cohort study comprising data from patients with SCN1A-positive Dravet syndrome and patients with GEFS+ consecutively referred for genetic testing (March 2001–June 2020) including age at seizure onset and a newly developed SCN1A genetic score. A training cohort was used to develop multiple prediction models that were validated using 2 independent blinded cohorts. Primary outcome was the discriminative accuracy of the model predicting Dravet syndrome vs other GEFS+ phenotypes.ResultsA total of 1,018 participants were included. The frequency of Dravet syndrome was 616/743 (83%) in the training cohort, 147/203 (72%) in validation cohort 1, and 60/72 (83%) in validation cohort 2. A high SCN1A genetic score (133.4 [SD 78.5] vs 52.0 [SD 57.5]; p < 0.001) and young age at onset (6.0 [SD 3.0] vs 14.8 [SD 11.8] months; p < 0.001) were each associated with Dravet syndrome vs GEFS+. A combined SCN1A genetic score and seizure onset model separated Dravet syndrome from GEFS+ more effectively (area under the curve [AUC] 0.89 [95% CI 0.86–0.92]) and outperformed all other models (AUC 0.79–0.85; p < 0.001). Model performance was replicated in both validation cohorts 1 (AUC 0.94 [95% CI 0.91–0.97]) and 2 (AUC 0.92 [95% CI 0.82–1.00]).DiscussionThe prediction model allows objective estimation at disease onset whether a child will develop Dravet syndrome vs GEFS+, assisting clinicians with prognostic counseling and decisions on early institution of precision therapies (http://scn1a-prediction-model.broadinstitute.org/).Classification of EvidenceThis study provides Class II evidence that a combined SCN1A genetic score and seizure onset model distinguishes Dravet syndrome from other GEFS+ phenotypes.

Background In-brace correction and brace compliance with thoraco-lumbo-sacral orthotic (TLSO) braces are associated with successful treatment of adolescent idiopathic scoliosis (AIS). This paper compares patients who had consistent radiographic documentation of in-brace correction to those who did not. Methods All skeletally immature (Risser 0-2) patients were treated for AIS (25-45°) with full-time TLSO braces that had compliance temperature monitors. All patients wore their braces at least 12 h a day. Brace failure was defined as curve progression to a surgical magnitude (≥ 50°). All patients were followed until brace discontinuation. Results Ninety patients (F 82, M 8) with an average age of 12.1 (10.1-15.0) years, Risser grade 0 (0-2), BMI percentile 48.5 (0.0-98.8), and daily brace wear of 16.5 (12.1-21.6) h/day were treated for 24.3 (8.0-66.6) months. Patients went through 1.7 (1-4) braces on average. Forty-two out of 90 (46.7%) patients had some amount of brace time with an unknown in-brace correction, which, on average, was 66.1% of their total treatment course (11.5-100). On univariate analysis, patients that did not have a repeat in-brace x-ray with major brace adjustments or new brace fabrication tended to be more skeletally immature (Risser 0 and tri-radiate open, p = 0.028), wear more braces throughout their treatment (2.0 vs 1.4, p < 0.001), were treated for a longer period of time (27 vs 22 months, p = 0.022), and failed bracing more often (47.6% vs 22.9%, p = 0.014). Conclusions Patients who did not have new in-brace x-rays with major brace adjustments and/or new brace fabrication were 3.1 (95% CI 1.2-7.6) times more likely to fail bracing than patients who were re-checked with new in-brace x-rays. Trial registration ClinicalTrials.gov—NCT02412137, initial registration date April 2015 Level of evidence III

While evidence exists supporting the potential for aerosol transmission of SARS-CoV-2, the infectious dose by inhalation remains unknown. In the present study, the probability of infection following inhalation of SARS-CoV-2 was dose-dependent in a nonhuman primate model of inhalational COVID-19. The median infectious dose, assessed by seroconversion, was 52 TCID50 (95% CI: 23–363 TCID50), and was significantly lower than the median dose for fever (256 TCID50, 95% CI: 102–603 TCID50), resulting in a group of animals that developed an immune response post-exposure but did not develop fever or other clinical signs of infection. In a subset of these animals, virus was detected in nasopharyngeal and/or oropharyngeal swabs, suggesting that infected animals without signs of disease are able to shed virus and may be infectious, which is consistent with reports of asymptomatic spread in human cases of COVID-19. These results suggest that differences in exposure dose may be a factor influencing disease presentation in humans, and reinforce the importance of public health measures that limit exposure dose, such as social distancing, masking, and increased ventilation. The dose-response data provided by this study are important to inform disease transmission and hazard modeling, and, ultimately, mitigation strategies. Additionally, these data will be useful to inform dose selection in future studies examining the efficacy of therapeutics and vaccines against inhalational COVID-19, and as a baseline in healthy, young adult animals for assessment of the importance of other factors, such as age, comorbidities, and viral variant, on the infectious dose and disease presentation., Author summary SARS-CoV-2 infection and subsequent disease presentation are dependent on exposure dose in a nonhuman primate model of inhalational COVID-19.