Delineating clinical and developmental outcomes in STXBP1-related disorders.

STXBP1-related disorders are among the most common genetic epilepsies and neurodevelopmental disorders. However, the longitudinal epilepsy course and developmental end points, have not yet been described in detail, which is a critical prerequisite for clinical trial readiness. Here, we assessed 1281 cumulative patient-years of seizure and developmental histories in 162 individuals with STXBP1-related disorders and established a natural history framework. STXBP1-related disorders are characterized by a dynamic pattern of seizures in the first year of life and high variability in neurodevelopmental trajectories in early childhood. Epilepsy onset differed across seizure types, with 90% cumulative onset for infantile spasms by 6 months and focal-onset seizures by 27 months of life. Epilepsy histories diverged between variant subgroups in the first 2 years of life, when individuals with protein-truncating variants and deletions in STXBP1 (n = 39) were more likely to have infantile spasms between 5 and 6 months followed by seizure remission, while individuals with missense variants (n = 30) had an increased risk for focal seizures and ongoing seizures after the first year. Developmental outcomes were mapped using milestone acquisition data in addition to standardized assessments including the Gross Motor Function Measure-66 Item Set and the Grasping and Visual-Motor Integration subsets of the Peabody Developmental Motor Scales. Quantification of end points revealed high variability during the first 5 years of life, with emerging stratification between clinical subgroups. An earlier epilepsy onset was associated with lower developmental abilities, most prominently when assessing gross motor development and expressive communication. We found that individuals with neonatal seizures or early infantile seizures followed by seizure offset by 12 months of life had more predictable seizure trajectories in early to late childhood compared to individuals with more severe seizure presentations, including individuals with refractory epilepsy throughout the first year. Characterization of anti-seizure medication response revealed age-dependent response over time, with phenobarbital, levetiracetam, topiramate and adrenocorticotropic hormone effective in reducing seizures in the first year of life, while clobazam and the ketogenic diet were effective in long-term seizure management. Virtual clinical trials using seizure frequency as the primary outcome resulted in wide range of trial success probabilities across the age span, with the highest probability in early childhood between 1 year and 3.5 years. In summary, we delineated epilepsy and developmental trajectories in STXBP1-related disorders using standardized measures, providing a foundation to interpret future therapeutic strategies and inform rational trial design.

Assessing the landscape of STXBP1-related disorders in 534 individuals.

Disease-causing variants in STXBP1 are among the most common genetic causes of neurodevelopmental disorders. However, the phenotypic spectrum in STXBP1-related disorders is wide and clear correlations between variant type and clinical features have not been observed so far. Here, we harmonized clinical data across 534 individuals with STXBP1-related disorders and analysed 19 973 derived phenotypic terms, including phenotypes of 253 individuals previously unreported in the scientific literature. The overall phenotypic landscape in STXBP1-related disorders is characterized by neurodevelopmental abnormalities in 95% and seizures in 89% of individuals, including focal-onset seizures as the most common seizure type (47%). More than 88% of individuals with STXBP1-related disorders have seizure onset in the first year of life, including neonatal seizure onset in 47%. Individuals with protein-truncating variants and deletions in STXBP1 (n = 261) were almost twice as likely to present with West syndrome and were more phenotypically similar than expected by chance. Five genetic hotspots with recurrent variants were identified in more than 10 individuals, including p.Arg406Cys/His (n = 40), p.Arg292Cys/His/Leu/Pro (n = 30), p.Arg551Cys/Gly/His/Leu (n = 24), p.Pro139Leu (n = 12), and p.Arg190Trp (n = 11). None of the recurrent variants were significantly associated with distinct electroclinical syndromes, single phenotypic features, or showed overall clinical similarity, indicating that the baseline variability in STXBP1-related disorders is too high for discrete phenotypic subgroups to emerge. We then reconstructed the seizure history in 62 individuals with STXBP1-related disorders in detail, retrospectively assigning seizure type and seizure frequency monthly across 4433 time intervals, and retrieved 251 anti-seizure medication prescriptions from the electronic medical records. We demonstrate a dynamic pattern of seizure control and complex interplay with response to specific medications particularly in the first year of life when seizures in STXBP1-related disorders are the most prominent. Adrenocorticotropic hormone and phenobarbital were more likely to initially reduce seizure frequency in infantile spasms and focal seizures compared to other treatment options, while the ketogenic diet was most effective in maintaining seizure freedom. In summary, we demonstrate how the multidimensional spectrum of phenotypic features in STXBP1-related disorders can be assessed using a computational phenotype framework to facilitate the development of future precision-medicine approaches.

Child neurology telemedicine: Analyzing 14 820 patient encounters during the first year of the COVID-19 pandemic.

AIM: To determine the long-term impact of telemedicine in child neurology care during the COVID-19 pandemic and with the reopening of outpatient clinics. METHOD: We performed an observational cohort study of 34 837 in-person visits and 14 820 telemedicine outpatient visits across 26 399 individuals. We assessed differences in care across visit types, time-period observed, time between follow-ups, patient portal activation rates, and demographic factors. RESULTS: We observed a higher proportion of telemedicine for epilepsy (International Classification of Diseases, 10th Revision G40: odds ratio [OR] 1.4, 95% confidence interval [CI] 1.3-1.5) and a lower proportion for movement disorders (G25: OR 0.7, 95% CI 0.6-0.8; R25: OR 0.7, 95% CI 0.6-0.9) relative to in-person visits. Infants were more likely to be seen in-person after reopening clinics than by telemedicine (OR 1.6, 95% CI 1.5-1.8) as were individuals with neuromuscular disorders (OR 1.6, 95% CI 1.5-1.7). Self-reported racial and ethnic minority populations and those with highest social vulnerability had lower telemedicine participation rates (OR 0.8, 95% CI 0.8-0.8; OR 0.7, 95% CI 0.7-0.8). INTERPRETATION: Telemedicine continued to be utilized even once in-person clinics were available. Pediatric epilepsy care can often be performed using telemedicine while young patients with neuromuscular disorders often require in-person assessment. Prominent barriers for socially vulnerable families and racial and ethnic minorities persist.

A Comparison of Ketamine and Midazolam as First-Line Anesthetic Infusions for Pediatric Status Epilepticus.

BACKGROUND: Pediatric refractory status epilepticus (RSE) often requires management with anesthetic infusions, but few data compare first-line anesthetics. This study aimed to compare the efficacy and adverse effects of midazolam and ketamine infusions as first-line anesthetics for pediatric RSE. METHODS: Retrospective single-center study of consecutive study participants treated with ketamine or midazolam as the first-line anesthetic infusions for RSE at a quaternary care children's hospital from December 1, 2017, until September 15, 2021. RESULTS: We identified 117 study participants (28 neonates), including 79 (68%) who received midazolam and 38 (32%) who received ketamine as the first-line anesthetic infusions. Seizures terminated more often in study participants administered ketamine (61%, 23/38) than midazolam (28%, 22/79; odds ratio [OR] 3.97, 95% confidence interval [CI] 1.76-8.98; P < 0.01). Adverse effects occurred more often in study participants administered midazolam (24%, 20/79) than ketamine (3%, 1/38; OR 12.54, 95% CI 1.61-97.43; P = 0.016). Study participants administered ketamine were younger, ketamine was used more often for children with acute symptomatic seizures, and midazolam was used more often for children with epilepsy. Multivariable logistic regression of seizure termination by first-line anesthetic infusion (ketamine or midazolam) including age at SE onset, SE etiology category, and individual seizure duration at anesthetic infusion initiation indicated seizures were more likely to terminate following ketamine than midazolam (OR 4.00, 95% CI 1.69-9.49; P = 0.002) and adverse effects were more likely following midazolam than ketamine (OR 13.41, 95% CI 1.61-111.04; P = 0.016). Survival to discharge was higher among study participants who received midazolam (82%, 65/79) than ketamine (55%, 21/38; P = 0.002), although treating clinicians did not attribute any deaths to ketamine or midazolam. CONCLUSIONS: Among children and neonates with RSE, ketamine was more often followed by seizure termination and less often associated with adverse effects than midazolam when administered as the first-line anesthetic infusion. Further prospective data are needed to compare first-line anesthetics for RSE.

Computational analysis of neurodevelopmental phenotypes: Harmonization empowers clinical discovery.

Making a specific diagnosis in neurodevelopmental disorders is traditionally based on recognizing clinical features of a distinct syndrome, which guides testing of its possible genetic etiologies. Scalable frameworks for genomic diagnostics, however, have struggled to integrate meaningful measurements of clinical phenotypic features. While standardization has enabled generation and interpretation of genomic data for clinical diagnostics at unprecedented scale, making the equivalent breakthrough for clinical data has proven challenging. However, increasingly clinical features are being recorded using controlled dictionaries with machine readable formats such as the Human Phenotype Ontology (HPO), which greatly facilitates their use in the diagnostic space. Improving the tractability of large-scale clinical information will present new opportunities to inform genomic research and diagnostics from a clinical perspective. Here, we describe novel approaches for computational phenotyping to harmonize clinical features, improve data translation through revising domain-specific dictionaries, quantify phenotypic features, and determine clinical relatedness. We demonstrate how these concepts can be applied to longitudinal phenotypic information, which represents a critical element of developmental disorders and pediatric conditions. Finally, we expand our discussion to clinical data derived from electronic medical records, a largely untapped resource of deep clinical information with distinct strengths and weaknesses.

Caregiver assessment of quality of life in individuals with genetic developmental and epileptic encephalopathies.

AIM: To summarize quality of life (QoL) and its determinants, including disease severity, in individuals with developmental and epileptic encephalopathies (DEEs) through a tailored questionnaire. METHOD: A questionnaire containing 89 items addressing demographic characteristics, genetic diagnosis, clinical features, and QoL was distributed to primary caregivers of individuals with DEEs through patient advocacy organizations. Composite scores were generated from the mean values of QoL items, grouped into domain scores. RESULTS: Out of 176 received responses, the most common genetic diagnoses reported were SCN2A (n=42/173, 24%), SLC6A1 (n=28/173, 16%), SCN1A (n=22/173, 13%), and KCNQ2 (n=21/173, 12%). Composite QoL scores centered around a mean score of 61.67 of 100 (SD 17.10). QoL scores were strongly associated with the number of days minimally disrupted by seizures, medication side effects, genetic diagnosis, and community type. The mean QoL scores for individuals with DEEs was significantly lower than for individuals with Rett syndrome, cerebral palsy, autism spectrum disorder, and Down syndrome. INTERPRETATION: QoL in DEEs can be assessed through a standardized instrument. QoL only partially overlaps with objective measurements of disease severity and may represent an independent outcome measure in precision medicine trials.

Visits of concern in child neurology telemedicine.

AIM: To characterize child neurology telemedicine visits flagged as requiring in-person evaluation during the COVID-19 pandemic. METHOD: We analyzed 7130 audio-video telemedicine visits between March and November 2020. Visits of concern (VOCs) were defined as telemedicine visits where the clinical scenario necessitated in-person follow-up evaluation sooner than if the visit had been conducted in-person. RESULTS: VOCs occurred in 5% (333/7130) of visits for 292 individuals (148 females, 144 males). Providers noted technical challenges more often in VOCs (40%; 133/333) than visits without concern (non-VOCs) (28%; 1922/6797) (p < 0.05). The median age was younger in VOCs (9 years 3 months, interquartile range [IQR] 2 years 0 months-14 years 3 months) than non-VOCs (11 years 3 months, IQR 5 years 10 months-15 years 10 months) (p < 0.05). Median household income was lower for patients with VOCs ($74 K, IQR $55 K-$97 K) compared to non-VOCs ($80 K, IQR $61 K-$100 K) (p < 0.05). Compared with all other race categories, families who self-identified as Black were more likely to have a VOC (odds ratio 1.53, 95% confidence interval 1.21-2.06). Epilepsy and headache represented the highest percentages of VOCs, while neuromuscular disorders and developmental delay had a higher proportion of VOCs than other neurological disorders. INTERPRETATION: These findings suggest that telemedicine is an effective platform for most child neurology visits. Younger children and those with neuromuscular disorders or developmental delays are more likely to require in-person evaluation. WHAT THIS PAPER ADDS: It is possible to successfully flag patients who need in-person assessment. Providers can manage issues arising during telemedicine in 95% of visits. Visits flagged as concerning were likely unrelated to modality of patient care. Provider concern was independent of technical difficulties for most telehealth visits. Younger age may be correlated with need for in-person assessment.

Computational analysis of 10,860 phenotypic annotations in individuals with SCN2A-related disorders.

PURPOSE: Pathogenic variants in SCN2A cause a wide range of neurodevelopmental phenotypes. Reports of genotype-phenotype correlations are often anecdotal, and the available phenotypic data have not been systematically analyzed. METHODS: We extracted phenotypic information from primary descriptions of SCN2A-related disorders in the literature between 2001 and 2019, which we coded in Human Phenotype Ontology (HPO) terms. With higher-level phenotype terms inferred by the HPO structure, we assessed the frequencies of clinical features and investigated the association of these features with variant classes and locations within the NaV1.2 protein. RESULTS: We identified 413 unrelated individuals and derived a total of 10,860 HPO terms with 562 unique terms. Protein-truncating variants were associated with autism and behavioral abnormalities. Missense variants were associated with neonatal onset, epileptic spasms, and seizures, regardless of type. Phenotypic similarity was identified in 8/62 recurrent SCN2A variants. Three independent principal components accounted for 33% of the phenotypic variance, allowing for separation of gain-of-function versus loss-of-function variants with good performance. CONCLUSION: Our work shows that translating clinical features into a computable format using a standardized language allows for quantitative phenotype analysis, mapping the phenotypic landscape of SCN2A-related disorders in unprecedented detail and revealing genotype-phenotype correlations along a multidimensional spectrum.

Assessing seizure burden in pediatric epilepsy using an electronic medical record-based tool through a common data element approach.

OBJECTIVE: Improvement in epilepsy care requires standardized methods to assess disease severity. We report the results of implementing common data elements (CDEs) to document epilepsy history data in the electronic medical record (EMR) after 12 months of clinical use in outpatient encounters. METHODS: Data regarding seizure frequency were collected during routine clinical encounters using a CDE-based form within our EMR. We extracted CDE data from the EMR and developed measurements for seizure severity and seizure improvement scores. Seizure burden and improvement was evaluated by patient demographic and encounter variables for in-person and telemedicine encounters. RESULTS: We assessed a total of 1696 encounters in 1038 individuals with childhood epilepsies between September 6, 2019 and September 11, 2020 contributed by 32 distinct providers. Childhood absence epilepsy (n = 121), Lennox-Gastaut syndrome (n = 86), and Dravet syndrome (n = 42) were the most common epilepsy syndromes. Overall, 43% (737/1696) of individuals had at least monthly seizures, 17% (296/1696) had a least daily seizures, and 18% (311/1696) were seizure-free for >12 months. Quantification of absolute seizure burden and changes in seizure burden over time differed between epilepsy syndromes, including high and persistent seizure burden in patients with Lennox-Gastaut syndrome. Individuals seen via telemedicine or in-person encounters had comparable seizure frequencies. Individuals identifying as Hispanic/Latino, particularly from postal codes with lower median household incomes, were more likely to have ongoing seizures that worsened over time. SIGNIFICANCE: Standardized documentation of clinical data in childhood epilepsies through CDE can be implemented in routine clinical care at scale and enables assessment of disease burden, including characterization of seizure burden over time. Our data provide insights into heterogeneous patterns of seizure control in common pediatric epilepsy syndromes and will inform future initiatives focusing on patient-centered outcomes in childhood epilepsies, including the impact of telemedicine and health care disparities.

A Longitudinal Exploration of CACNA1A -related Hemiplegic Migraine in Children.

Introduction: Since the initial description of CACNA1A- related hemiplegic migraine (HM), the phenotypic spectrum has expanded from mild episodes in neurotypical individuals to potentially life-threatening events frequently seen in individuals with developmental and epileptic encephalopathies. However, the overall longitudinal course throughout childhood remains unknown. Methods: We analyzed HM and seizure history in individuals with CACNA1A -related HM, delineating frequency and severity of events in monthly increments through a standardized approach. Combining these data with medication prescription information, we assessed the response of HM to different agents. Results: Our cohort involved 15 individuals between 3 and 29 years (163 patient years) and included 11 unique and two recurrent variants (p.R1349Q and p.V1393M; both n= 2). The age of first confirmed HM ranged from 14 months to 13 years (average 3 years). 25% of all HM events were severe (lasting >3 days) and 73% of individuals had at least 1 severe occurrence. Spacing of HM events ranged from 1 month to 14 years and changes in HM severity over time of showed increases or decreases of >2 severity levels in 12/122 events. Eight individuals had epilepsy, but severity of epilepsy did not correlate with frequency and severity of HM events. While levetiracetam ( n= 6) and acetazolamide ( n= 5) were the most frequently used medications, they did not show efficacy in HM prevention or HM severity reduction. However, verapamil ( n= 3) showed efficacy in preventing HM episodes (OR 2.68, CI 1.39-5.67). Significance: The longitudinal course of CACNA1A -related HM lacks recognizable patterns for timing and severity of HM events or correlation with seizure patterns. Our data underscores the unpredictability of CACNA1A -related HM, highlighting the need for close surveillance for reoccurring HM events even in individuals with symptom-free periods. Key points: 24% of hemiplegic migraines (HM) in CACNA1A- related disorders are severe, involving cerebral edema and greater than 4 days to recover Timing and severity of HM are unpredictable, with large changes in severity between events, and age of onset ranging from 1-13 yearsEpilepsy occurred in 53% of individuals, with neither the timing nor severity of seizures correlated with HM.

Leveraging electronic medical record-embedded standardised electroencephalogram reporting to develop neonatal seizure prediction models: a retrospective cohort study.

BACKGROUND: Accurate prediction of seizures can help to direct resource-intense continuous electroencephalogram (CEEG) monitoring to neonates at high risk of seizures. We aimed to use data from standardised EEG reports to generate seizure prediction models for vulnerable neonates. METHODS: In this retrospective cohort study, we included neonates who underwent CEEG during the first 30 days of life at the Children's Hospital of Philadelphia (Philadelphia, PA, USA). The hypoxic ischaemic encephalopathy subgroup included only patients with CEEG data during the first 5 days of life, International Classification of Diseases, revision 10, codes for hypoxic ischaemic encephalopathy, and documented therapeutic hypothermia. In January, 2018, we implemented a novel CEEG reporting system within the electronic medical record (EMR) using common data elements that incorporated standardised terminology. All neonatal CEEG data from Jan 10, 2018, to Feb 15, 2022, were extracted from the EMR using age at the time of CEEG. We developed logistic regression, decision tree, and random forest models of neonatal seizure prediction using EEG features on day 1 to predict seizures on future days. FINDINGS: We evaluated 1117 neonates, including 150 neonates with hypoxic ischaemic encephalopathy, with CEEG data reported using standardised templates between Jan 10, 2018, and Feb 15, 2022. Implementation of a consistent EEG reporting system that documents discrete and standardised EEG variables resulted in more than 95% reporting of key EEG features. Several EEG features were highly correlated, and patients could be clustered on the basis of specific features. However, no simple combination of features adequately predicted seizure risk. We therefore applied computational models to complement clinical identification of neonates at high risk of seizures. Random forest models incorporating background features performed with classification accuracies of up to 90% (95% CI 83-94) for all neonates and 97% (88-99) for neonates with hypoxic ischaemic encephalopathy; recall (sensitivity) of up to 97% (91-100) for all neonates and 100% (100-100) for neonates with hypoxic ischaemic encephalopathy; and precision (positive predictive value) of up to 92% (84-96) in the overall cohort and 97% (80-99) in neonates with hypoxic ischaemic encephalopathy. INTERPRETATION: Using data extracted from the standardised EEG report on the first day of CEEG, we predict the presence or absence of neonatal seizures on subsequent days with classification performances of more than 90%. This information, incorporated into routine care, could guide decisions about the necessity of continuing EEG monitoring beyond the first day, thereby improving the allocation of limited CEEG resources. Additionally, this analysis shows the benefits of standardised clinical data collection, which can drive learning health system approaches to personalised CEEG use. FUNDING: Children's Hospital of Philadelphia, the Hartwell Foundation, the National Institute of Neurological Disorders and Stroke, and the Wolfson Foundation.

Delineating clinical and developmental outcomes in STXBP1-related disorders.

STXBP1-related disorders are among the most common genetic epilepsies and neurodevelopmental disorders. However, the longitudinal epilepsy course and developmental endpoints have not yet been described in detail, which is a critical prerequisite for clinical trial readiness. Here, we assessed 1,281 cumulative patient-years of seizure and developmental histories in 162 individuals with STXBP1-related disorders and established a natural history framework. STXBP1-related disorders are characterized by a dynamic pattern of seizures in the first year of life and high variability in neurodevelopmental trajectories in early childhood. Epilepsy onset differed across seizure types, with 90% cumulative onset for infantile spasms by 6 months and focal-onset seizures by 27 months of life. Epilepsy histories diverged between variant subgroups in the first 2 years of life, when individuals with protein-truncating variants and deletions in STXBP1 (n=39) were more likely to have infantile spasms between 5 and 6 months followed by seizure remission, while individuals with missense variants (n=30) had an increased risk for focal seizures and ongoing seizures after the first year. Developmental outcomes were mapped using milestone acquisition data in addition to standardized assessments including the Gross Motor Function Measure-66 Item Set and the Grasping and Visual-Motor Integration subsets of the Peabody Developmental Motor Scales. Quantification of endpoints revealed high variability during the first five years of life, with emerging stratification between clinical subgroups, most prominently between individuals with and without infantile spasms. We found that individuals with neonatal seizures or early infantile seizures followed by seizure offset by 12 months of life had more predictable seizure trajectories in early to late childhood than compared to individuals with more severe seizure presentations, including individuals with refractory epilepsy throughout the first year. Characterization of anti-seizure medication response revealed age-dependent response over time, with phenobarbital, levetiracetam, topiramate, and adrenocorticotropic hormone effective in reducing seizures in the first year of life, while clobazam and the ketogenic diet were effective in long-term seizure management. Virtual clinical trials using seizure frequency as the primary outcome resulted in wide range of trial success probabilities across the age span, with the highest probability in early childhood between 1 year and 3.5 years. In summary, we delineated epilepsy and developmental trajectories in STXBP1-related disorders using standardized measures, providing a foundation to interpret future therapeutic strategies and inform rational trial design.

Multicenter Study of the Impact of COVID-19 Shelter-In-Place on Tertiary Hospital-based Care for Pediatric Neurologic Disease.

Objective: To describe changes in hospital-based care for children with neurologic diagnoses during the initial 6 weeks following regional Coronavirus 2019 Shelter-in-Place orders. Methods: This retrospective cross-sectional study of 7 US and Canadian pediatric tertiary care institutions included emergency and inpatient encounters with a neurologic primary discharge diagnosis code in the initial 6 weeks of Shelter-in-Place (COVID-SiP), compared to the same period during the prior 3 years (Pre-COVID). Patient demographics, encounter length, and neuroimaging and electroencephalography use were extracted from the medical record. Results: 27,900 encounters over 4 years were included. Compared to Pre-COVID, there was a 54% reduction in encounters during Shelter-in-Place. COVID-SiP patients were younger (median 5 years vs 7 years). The incidence of encounters for migraine fell by 72%, and encounters for acute diagnoses of status epilepticus, infantile spasms, and traumatic brain injury dropped by 53%, 55%, and 56%, respectively. There was an increase in hospital length of stay, relative utilization of intensive care, and diagnostic testing (long-term electroencephalography, brain MRI, and head CT (all P<.01)). Conclusion: During the initial 6 weeks of SiP, there was a significant decrease in neurologic hospital-based encounters. Those admitted required a high level of care. Hospital-based neurologic services are needed to care for acutely ill patients. Precise factors causing these shifts are unknown and raise concern for changes in care seeking of patients with serious neurologic conditions. Impacts of potentially delayed diagnosis or treatment require further investigation.

Ketamine for Management of Neonatal and Pediatric Refractory Status Epilepticus.

BACKGROUND AND OBJECTIVES: Few data are available regarding the use of anesthetic infusions for refractory status epilepticus (RSE) in children and neonates, and ketamine use is increasing despite limited data. We aimed to describe the impact of ketamine for RSE in children and neonates. METHODS: Retrospective single-center cohort study of consecutive patients admitted to the intensive care units of a quaternary care children's hospital treated with ketamine infusion for RSE. RESULTS: Sixty-nine patients were treated with a ketamine infusion for RSE. The median age at onset of RSE was 0.7 years (interquartile range 0.15-7.2), and the cohort included 13 (19%) neonates. Three patients (4%) had adverse events requiring intervention during or within 12 hours of ketamine administration, including hypertension in 2 patients and delirium in 1 patient. Ketamine infusion was followed by seizure termination in 32 patients (46%), seizure reduction in 19 patients (28%), and no change in 18 patients (26%). DISCUSSION: Ketamine administration was associated with few adverse events, and seizures often terminated or improved after ketamine administration. Further data are needed comparing first-line and subsequent anesthetic medications for treatment of pediatric and neonatal RSE. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence on the therapeutic utility of ketamine for treatment of RSE in children and neonates.

Phenotypic homogeneity in childhood epilepsies evolves in gene-specific patterns across 3251 patient-years of clinical data.

While genetic studies of epilepsies can be performed in thousands of individuals, phenotyping remains a manual, non-scalable task. A particular challenge is capturing the evolution of complex phenotypes with age. Here, we present a novel approach, applying phenotypic similarity analysis to a total of 3251 patient-years of longitudinal electronic medical record data from a previously reported cohort of 658 individuals with genetic epilepsies. After mapping clinical data to the Human Phenotype Ontology, we determined the phenotypic similarity of individuals sharing each genetic etiology within each 3-month age interval from birth up to a maximum age of 25 years. 140 of 600 (23%) of all 27 genes and 3-month age intervals with sufficient data for calculation of phenotypic similarity were significantly higher than expect by chance. 11 of 27 genetic etiologies had significant overall phenotypic similarity trajectories. These do not simply reflect strong statistical associations with single phenotypic features but appear to emerge from complex clinical constellations of features that may not be strongly associated individually. As an attempt to reconstruct the cognitive framework of syndrome recognition in clinical practice, longitudinal phenotypic similarity analysis extends the traditional phenotyping approach by utilizing data from electronic medical records at a scale that is far beyond the capabilities of manual phenotyping. Delineation of how the phenotypic homogeneity of genetic epilepsies varies with age could improve the phenotypic classification of these disorders, the accuracy of prognostic counseling, and by providing historical control data, the design and interpretation of precision clinical trials in rare diseases.