Mental Health Diagnoses Risk Among Children and Young Adults With Cerebral Palsy, Chronic Conditions, or Typical Development.

Importance: Mental health (MH) issues in children with cerebral palsy (CP) are poorly understood compared with other pediatric populations. Objective: To examine MH diagnosis code assignment among children and young adults with CP and compare with typically developing (TD) and chronic condition (CC) pediatric populations. Design, Setting, and Participants: This case-control study used International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes to create a CP case set and CC and TD control sets using electronic health record data of children and young adults from a large tertiary care children's hospital in the midwestern United States between 2010 and 2022. Case-control matching was performed to control for demographic factors. Data were analyzed from June to December 2023. Exposures: All MH diagnosis codes were mapped to ICD-10-CM and categorized using Clinical Classifications Software Refined (CCSR). Main Outcomes and Measures: The incidence rates of MH CCSR categories were calculated. Descriptive and comparative statistics were used to evaluate the significance and odds associated with factors. Results: Data from 216 794 individuals (mean [SD] baseline age, 4.3 [5.1] years; 118 562 [55%] male) were analyzed, including 3544 individuals with CP, 142 160 individuals with CC, and 71 080 TD individuals. The CP cohort spread across Gross Motor Function Classification System (GMFCS) levels I (981 individuals [28%]), II (645 individuals [18%]), III (346 individuals [10%]), IV (502 individuals [14%]), and V (618 individuals [17%]). Rates varied significantly for anxiety (824 individuals with CP [23%]; 25 877 individuals with CC [9%]; 6274 individuals with TD [18%]), attention-deficit/hyperactivity disorder (534 individuals with CP [15%]; 22 426 individuals with CC [9%]; 6311 individuals with TD [16%]); conduct or impulse disorder (504 individuals with CP [14%]; 13 209 individuals with CC [5%]; 3715 individuals with TD [9%]), trauma or stress disorders (343 individuals with CP [10%]; 18 229 individuals with CC [8%]; 5329 individuals with TD [13%]), obsessive-compulsive disorder (251 individuals with CP [7%]; 3795 individuals with CC [1%]; 659 individuals with TD [3%]), depression (108 individuals with CP [3%]; 12 224 individuals with CC [5%]; 4007 individuals with TD [9%]), mood disorders (74 individuals with CP [2%]; 4355 individuals with CC [2%]; 1181 individuals with TD [3%]), and suicidal ideation (72 individuals with CP [2%]; 7422 individuals with CC [5%]; 3513 individuals with TD [5%]). There was significant variation in odds of MH diagnoses by GMFCS level (I-II vs III-V: odds ratio [OR], 1.23; 95% CI, 1.09-1.40; P = .001). Among individuals with CP, males were more likely than females to have diagnosis codes for conduct or impulse disorders (OR, 1.41; 95% CI, 1.16-1.73) and attention-deficit/hyperactivity disorder (OR, 1.41 [95% CI, 1.15-1.73]). Black individuals, compared with White individuals, were more likely to have diagnoses for obsessive-compulsive disorder (OR, 1.57 [95% CI, 1.14-2.16]), other mood disorders (OR, 1.85 [95% CI, 1.01-3.38]), and trauma or stress disorders (OR, 1.94 [95% CI, 1.44-2.63]). Odds for trauma or stress disorders were elevated for individuals who identified as other races compared with White individuals (OR, 2.80 [95% CI, 2.03-3.87]). Conclusions and Relevance: In this case-control study of children and young adults with CP and matched comparisons, anxiety and conduct or impulse diagnoses were higher in individuals with CP. The lower diagnosis rates of depression and suicidal ideation may indicate underdiagnosis among individuals with CP. There is likely a need for assessment tools that are more suitable for children with CP.

White matter characteristics in children with cerebral palsy prior to selective dorsal rhizotomy: a multicenter diffusion tensor imaging study.

OBJECTIVE: The aims of this study were to 1) assess and quantify white matter (WM) microstructural characteristics derived from diffusion tensor imaging (DTI) in children with cerebral palsy (CP) prior to selective dorsal rhizotomy (SDR), and 2) investigate potential associations between WM diffusion properties and gross motor function and spasticity in children with spastic CP who underwent SDR. METHODS: This study is a multisite study based on DT images acquired prior to SDR as well as postoperative outcome data. DTI data collected from two sites were harmonized using the ComBat approach to minimize intersite scanner difference. The DTI abnormalities between children with spastic CP and controls were analyzed and correlated with the severity of impaired mobility based on the Gross Motor Function Classification System (GMFCS). The improvement in gross motor function and spasticity after SDR surgery was assessed utilizing the Gross Motor Function Measure-66 (GMFM-66), the Modified Tardieu Scale (MTS), and the modified Ashworth scale (MAS). Alterations in these outcome measures were quantified in association with DTI abnormalities. RESULTS: Significant DTI alterations, including lower fractional anisotropy (FA) in the genu of the corpus callosum (gCC) and higher mean diffusivity (MD) in the gCC and posterior limb of the internal capsule (PLIC), were found in children in the SDR group when compared with the age-matched control group (all p < 0.05). Greater DTI alterations (FA in gCC and MD in gCC and PLIC) were associated with lower mobility levels as determined based on GMFCS level (p < 0.05). The pre- to post-SDR improvement in motor function based on GMFM-66 was statistically significant (p = 0.006 and 0.002 at 6-month and 12-month follow-ups, respectively). The SDR efficacy was also identified as improving spasticity in lower-extremity muscle groups assessed with the MTS and MAS. Partial correlation analysis presented a significant association between pre- to post-SDR MTS alteration and DTI abnormalities. CONCLUSIONS: The findings in the present study provided initial quantitative evidence to establish the WM microstructural characteristics in children with spastic CP prior to SDR surgery. The study generated data for the association between baseline DTI characteristics and mobility in children with CP prior to SDR surgery. The study also demonstrated SDR efficacy in improving motor function and spasticity based on the GMFM-66, MTS, and MAS, respectively, in association with DTI data.

Incidence and outcomes of pediatric patients with dual diagnosis of traumatic spinal cord injury and brain injury on an inpatient rehabilitation unit.

BACKGROUND: Traumatic brain injury (TBI) and spinal cord injury (SCI) are diagnoses commonly encountered on the pediatric rehabilitation unit. However, there is limited evidence in the literature addressing the incidence of or rehabilitation outcomes in pediatric patients with a dual diagnosis of TBI and SCI. OBJECTIVE: To determine incidence and functional outcomes of the dual diagnosis population. DESIGN: Retrospective cohort study. SETTING: Inpatient rehabilitation unit within an academic pediatric hospital. PATIENTS: Pediatric patients admitted to a single inpatient rehabilitation unit with a diagnosis of traumatic SCI between 2006 and 2019. Fifty-four patient records were identified and 26 met inclusion criteria. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE: Presence of concomitant TBI in patients with diagnosed SCI. RESULTS: Seven of 26 patients were given a dual diagnosis of TBI and SCI during their initial rehabilitation hospitalization. After review of charts, authors identified 12 additional patients with suspected dual diagnoses based on injury characteristics and symptoms. There were no significant differences in functional outcomes across diagnosis groups. CONCLUSIONS: Incidence of dual diagnosis among pediatric patients with traumatic SCI was initially found to be 27%; the retrospective review indicated that TBI may be underdiagnosed in this patient population, and the dual diagnosis incidence may be as high as 73%. All patients had improved functional outcomes during their rehabilitation stays regardless of presence or absence of TBI.

A big data approach to evaluate receipt of optimal care in childhood cerebral palsy.

PURPOSE: Through automated electronic health record (EHR) data extraction and analysis, this project systematically quantified actual care delivery for children with cerebral palsy (CP) and evaluated alignment with current evidence-based recommendations. METHODS: Utilizing EHR data for over 8000 children with CP, we developed an approach to define and quantify receipt of optimal care, and pursued proof-of-concept with two children with unilateral CP, Gross Motor Function Classification System (GMFCS) Level II. Optimal care was codified as a cluster of four components including physical medicine and rehabilitation (PMR) care, spasticity management, physical therapy (PT), and occupational therapy (OT). A Receipt of Care Score (ROCS) quantified the degree of adherence to recommendations and was compared with the Pediatric Outcomes Data Collection Instrument (PODCI) and Pediatric Quality of Life Inventory (PEDS QL). RESULTS: The two children (12 year old female, 13 year old male) had nearly identical PMR and spasticity component scores while PT and OT scores were more divergent. Functional outcomes were higher for the child who had higher adjusted ROCS. CONCLUSIONS: ROCSs demonstrate variation in real-world care delivered over time and differentiate between components of care. ROCSs reflect overall function and quality of life. The ROCS methods developed are novel, robust, and scalable and will be tested in a larger sample.IMPLICATIONS FOR REHABILITATIONOptimal practice, with an emphasis on integrated multidisciplinary care, can be defined and quantified utilizing evidence-based recommendations.Receipt of optimal care for childhood cerebral palsy can be scored using existing electronic health record data.Big Data approaches can contribute to the understanding of current care and inform approaches for improved care.

Developing a length of stay prediction model for newborns, achieving better accuracy with greater usability.

BACKGROUND: One in ten newborn children is born prematurely. The elongated length of stay (LOS) of these children in the Neonatal Intensive Care Unit (NICU) has important implications on hospital occupancy figures, healthcare and management costs, as well as the psychology of parents. In order to allow accurate planning and resource allocation, this study aims to create a generalizable and robust model to predict the NICU LOS of preterm newborns. METHODS: Data were collected from a large tertiary center NICU between 2011 and 2018 and relates to 5,362 newborns. The selected model was externally validated using a data set of 8,768 newborns from another tertiary center NICU. This report compares several models, such as Random Forest (RF), quantile RF, and other feature selection methods, including LASSO and AIC step-forward selection. In addition, a novel step-forward selection based on False Discovery Rate (FDR) for quantile regression is presented and evaluated. RESULTS: A high-orderquantile regression model for predicting preterm newborns' LOS that uses only four features available at birth had more attractive properties than other richer ones. The model achieved a Mean Absolute Error (MAE) of 6.26 days on the internal validation set (average LOS 27.04) and an MAE of 6.04 days on the external validation set (average LOS 29.32). The suggested model surpassed the accuracy obtained by models in the literature. It is shown empirically that the FDR-based selection has better properties than the AIC-based step-forward selection approach. CONCLUSION: This paper demonstrates a process to create a predictive model for NICU LOS in preterm newborns, where each step is reasoned. We obtain a simple and robust model for NICU LOS prediction, which achieves far better results than the current model used for financing NICUs. Utilizing this model, we have created an easy-to-use online web application to ease parents' worries and to assist NICU management: https://tzviel.shinyapps.io/calcuLOS.

Predictors of disease course and long-term outcomes of idiopathic intracranial hypertension in children and adolescents.

This study aimed to identify predictors for unfavorable disease course and clinical and visual outcomes in pediatric patients with idiopathic intracranial hypertension (IIH). Employing a multi-tiered approach, we retrospectively analyzed clinical, ophthalmic, and neuroimaging data from patients diagnosed with IIH between 2003 and 2021. Of the 97 patients included, 56 (58%) were females. The median age was 12 years [Interquartile range (IQR) 9, 14], and the median follow-up time was 39.0 months (IQR 14.8, 90.9). Forty-two (43%) patients had an unfavorable disease course, 28 (29%) had persistence of headache at last follow-up, and 16 (18%) had a poor visual outcome, most of them with mild visual disturbances. Poor visual outcome was more common in females compared to males [16/47 (34%) vs. 0/39, p < 0.001)]. On multivariate regression analysis, female sex and disease recurrence were significantly associated with poor visual outcomes (OR: 18.5, CI:1.3-270, P = 0.03, and OR: 5.1, CI: 1.2-22.5, P = 0.03, respectively). Patients with persistent headaches exhibited lower incidence of papilledema, lower opening pressure, and fewer neuroimaging markers indicating elevated intracranial pressure. CONCLUSIONS: This study provides insights into predictive factors for an unfavorable disease course, persistent headaches, and poor visual outcomes in patients with childhood IIH. Patients with persistent headaches may have a variant of a chronic pain syndrome warranting a different therapeutic approach. WHAT IS KNOWN: • Childhood-onset Idiopathic Intracranial hypertension (IIH) is a heterogenous disease. The knowledge on disease trajectory and long-term outcomes and its predictors is limited. WHAT IS NEW: • A higher opening pressure and factors suggestive of the metabolic syndrome predict an unfavorable disease course whereas female sex and disease recurrence are significantly associated with poor visual outcomes • A third of the patients diagnosed with IIH experience ongoing headaches despite achieving favorable visual outcomes. This subset, characterized by lower disease-severity indicators at onset may represent a distinct subgroup warranting a different therapeutic approach.

Outpatient hospital utilization after single event multi-level surgery in children with cerebral palsy.

PURPOSE: This study aimed to examine outpatient hospital utilization (number of specialties seen and number of visits to each specialty) in the year after single event multi-level surgery (SEMLS) in children with cerebral palsy (CP), and to determine if utilization differs across the medical center in the year after compared to the year before SEMLS. METHODS: This retrospective cross-sectional study used electronic medical record data of outpatient hospital utilization in children with CP who underwent SEMLS. RESULTS: Thirty children with CP (Gross Motor Function Classification System Levels I-V, mean age of 9.9 years) were included. In the year after surgery, a significant difference (p = 0.001) was found for the number of specialties seen, with non-ambulatory children seeing more specialties than ambulatory children. No statistically significant difference was found between the number of outpatient visits to each specialty in the year after SEMLS. Compared to the year before SEMLS, fewer therapy visits occurred in the year after SEMLS (p < 0.001) but significantly more visits to orthopaedics (p = 0.001) and radiology (p = 0.001). CONCLUSION: Children with CP had fewer therapy visits but more orthopaedic and radiology visits the year after SEMLS. Nearly half of the children were non-ambulatory. Examination of care needs in children with CP undergoing SEMLS is justified with consideration of ambulatory status, surgical burden, and post-operative immobilization.

Gross motor function prediction using natural language processing in cerebral palsy.

AIM: To predict ambulatory status and Gross Motor Function Classification System (GMFCS) levels in patients with cerebral palsy (CP) by applying natural language processing (NLP) to electronic health record (EHR) clinical notes. METHOD: Individuals aged 8 to 26 years with a diagnosis of CP in the EHR between January 2009 and November 2020 (~12 years of data) were included in a cross-sectional retrospective cohort of 2483 patients. The cohort was divided into train-test and validation groups. Positive predictive value, sensitivity, specificity, and area under the receiver operating curve (AUC) were calculated for prediction of ambulatory status and GMFCS levels. RESULTS: The median age was 15 years (interquartile range 10-20 years) for the total cohort, with 56% being male and 75% White. The validation group resulted in 70% sensitivity, 88% specificity, 81% positive predictive value, and 0.89 AUC for predicting ambulatory status. NLP applied to the EHR differentiated between GMFCS levels I-II and III (15% sensitivity, 96% specificity, 46% positive predictive value, and 0.71 AUC); and IV and V (81% sensitivity, 51% specificity, 70% positive predictive value, and 0.75 AUC). INTERPRETATION: NLP applied to the EHR demonstrated excellent differentiation between ambulatory and non-ambulatory status, and good differentiation between GMFCS levels I-II and III, and IV and V. Clinical use of NLP may help to individualize functional characterization and management. WHAT THIS PAPER ADDS: Natural language processing (NLP) applied to the electronic health record (EHR) can predict ambulatory status in children with cerebral palsy (CP). NLP provides good prediction of Gross Motor Function Classification System level in children with CP using the EHR. NLP methods described could be integrated in an EHR system to provide real-time information.

Prognostic value of neutrophil-to-lymphocyte ratio in COVID-19 compared with Influenza and respiratory syncytial virus infection.

A high neutrophil to lymphocyte ratio (NLR) is considered an unfavorable prognostic factor in various diseases, including COVID-19. The prognostic value of NLR in other respiratory viral infections, such as Influenza, has not hitherto been extensively studied. We aimed to compare the prognostic value of NLR in COVID-19, Influenza and Respiratory Syncytial Virus infection (RSV). A retrospective cohort of COVID-19, Influenza and RSV patients admitted to the Tel Aviv Medical Center from January 2010 to October 2020 was analyzed. Laboratory, demographic, and clinical parameters were collected. Two way analyses of variance (ANOVA) was used to compare the association between NLR values and poor outcomes among the three groups. ROC curve analyses for each virus was applied to test the discrimination ability of NLR. 722 COVID-19, 2213 influenza and 482 RSV patients were included. Above the age of 50, NLR at admission was significantly lower among COVID-19 patients (P < 0.001). NLR was associated with poor clinical outcome only in the COVID-19 group. ROC curve analysis was performed; the area under curve of poor outcomes for COVID-19 was 0.68, compared with 0.57 and 0.58 for Influenza and RSV respectively. In the COVID-19 group, multivariate logistic regression identified a high NLR (defined as a value above 6.82) to be a prognostic factor for poor clinical outcome, after adjusting for age, sex and Charlson comorbidity score (odds ratio of 2.9, P < 0.001). NLR at admission is lower and has more prognostic value in COVID-19 patients, when compared to Influenza and RSV.

Disordered Eating Behaviors in Young Individuals With Idiopathic Intracranial Hypertension.

BACKGROUND: The objective of this study was to assess the prevalence of disordered eating behaviors (DEBs) in young individuals with idiopathic intracranial hypertension (IIH) and to identify predictors of DEBs in this population. METHODS: Individuals with IIH aged eight to 25 years and their matched controls responded to a self-rating survey comprised of the Eating Attitude Test-26 for assessing the presence of DEBs and the Depression, Anxiety and Stress Scale. RESULTS: Fifty-three subjects with IIH and 106 healthy controls were included. DEBs were significantly more prevalent in individuals with IIH (P < 0.001). Individuals with IIH and DEBs were more likely to have longer periods of treatment [odds ratio: 1.07, 95% CI: 1.02-1.41), P = 0.008] and to have lost a significant amount of weight during the course of treatment [odds ratio: 9.06 (95% CI: 1.30-62.9), P = 0.026]. Depression, anxiety, and stress were more prevalent in the IIH group than in the controls (P = 0.004) and were associated with DEBs in these individuals (P = 0.01). CONCLUSIONS: There is an increased prevalence of DEBs among young individuals with IIH, which persists even after disease resolution, and is associated with higher reported rates of depression, anxiety, and stress. Medical caregivers should have heightened awareness to DEBs in individuals with IIH with the aim of early identification and intervention.

An interactive single cell web portal identifies gene and cell networks in COVID-19 host responses.

Numerous studies have provided single-cell transcriptome profiles of host responses to SARS-CoV-2 infection. Critically lacking however is a data mine that allows users to compare and explore cell profiles to gain insights and develop new hypotheses. To accomplish this, we harmonized datasets from COVID-19 and other control condition blood, bronchoalveolar lavage, and tissue samples, and derived a compendium of gene signature modules per cell type, subtype, clinical condition, and compartment. We demonstrate approaches to interacting with, exploring, and functional evaluating these modules via a new interactive web portal ToppCell (http://toppcell.cchmc.org/). As examples, we develop three hypotheses: (1) alternatively-differentiated monocyte-derived macrophages form a multicelllar signaling cascade that drives T cell recruitment and activation; (2) COVID-19-generated platelet subtypes exhibit dramatically altered potential to adhere, coagulate, and thrombose; and (3) extrafollicular B maturation is driven by a multilineage cell activation network that expresses an ensemble of genes strongly associated with risk for developing post-viral autoimmunity.

Implicating Gene and Cell Networks Responsible for Differential COVID-19 Host Responses via an Interactive Single Cell Web Portal.

Numerous studies have provided single-cell transcriptome profiles of host responses to SARS-CoV-2 infection. Critically lacking however is a datamine that allows users to compare and explore cell profiles to gain insights and develop new hypotheses. To accomplish this, we harmonized datasets from COVID-19 and other control condition blood, bronchoalveolar lavage, and tissue samples, and derived a compendium of gene signature modules per cell type, subtype, clinical condition, and compartment. We demonstrate approaches to probe these via a new interactive web portal (http://toppcell.cchmc.org/COVID-19). As examples, we develop three hypotheses: (1) a multicellular signaling cascade among alternatively differentiated monocyte-derived macrophages whose tasks include T cell recruitment and activation; (2) novel platelet subtypes with drastically modulated expression of genes responsible for adhesion, coagulation and thrombosis; and (3) a multilineage cell activator network able to drive extrafollicular B maturation via an ensemble of genes strongly associated with risk for developing post-viral autoimmunity.

Cross-platform validation of neurotransmitter release impairments in schizophrenia patient-derived NRXN1-mutant neurons.

Heterozygous NRXN1 deletions constitute the most prevalent currently known single-gene mutation associated with schizophrenia, and additionally predispose to multiple other neurodevelopmental disorders. Engineered heterozygous NRXN1 deletions impaired neurotransmitter release in human neurons, suggesting a synaptic pathophysiological mechanism. Utilizing this observation for drug discovery, however, requires confidence in its robustness and validity. Here, we describe a multicenter effort to test the generality of this pivotal observation, using independent analyses at two laboratories of patient-derived and newly engineered human neurons with heterozygous NRXN1 deletions. Using neurons transdifferentiated from induced pluripotent stem cells that were derived from schizophrenia patients carrying heterozygous NRXN1 deletions, we observed the same synaptic impairment as in engineered NRXN1-deficient neurons. This impairment manifested as a large decrease in spontaneous synaptic events, in evoked synaptic responses, and in synaptic paired-pulse depression. Nrxn1-deficient mouse neurons generated from embryonic stem cells by the same method as human neurons did not exhibit impaired neurotransmitter release, suggesting a human-specific phenotype. Human NRXN1 deletions produced a reproducible increase in the levels of CASK, an intracellular NRXN1-binding protein, and were associated with characteristic gene-expression changes. Thus, heterozygous NRXN1 deletions robustly impair synaptic function in human neurons regardless of genetic background, enabling future drug discovery efforts.

Describing the Delivery of Evidence-Based Physical Therapy Intervention to Individuals With Cerebral Palsy.

PURPOSE: To characterize by evidence grades and examine variation in type of physical therapy intervention delivered in routine clinical care in individuals with cerebral palsy (CP). METHODS: Retrospective data collection from the electronic record over 1 year at a tertiary care pediatric outpatient therapy division. RESULTS: Four hundred sixty-five individuals with CP received 28 344 interventions during 4335 treatment visits. Sixty-six percent of interventions were evidence-based interventions (EBIs). Significant variation was demonstrated across Gross Motor Function Classification System levels, with children classified as level V receiving the least and level III the most. The most frequent EBIs delivered were caregiver education, motor control, functional strengthening, ankle-foot orthoses, treadmill training, and fit of adaptive equipment. CONCLUSIONS: Further work is needed to determine whether amount of EBI is related to better outcomes. Combining this information with other aspects of dose (intensity, time, and frequency) may elucidate the contribution of each with outcomes.

Electronic health record and patterns of care for children with cerebral palsy.

AIM: To characterize the patterns of care of children with cerebral palsy (CP) in a tertiary healthcare system. METHOD: Electronic health record data from 2009 to 2019 were extracted for children with CP. Machine learning hierarchical clustering was used to identify clusters of care. The ratio of in-person to care coordination visits was calculated for each specialty. RESULTS: The sample included 6369 children with CP (55.7% males, 44.3% females, 76.2% white, 94.7% non-Hispanic; with a mean age of 8y 2mo [SD 5y 10mo; range 0-21y; median 7y 1mo]) at the time of diagnosis. A total of 3.7 million in-person visits and care coordination notes were identified across 34 specialties. The duration of care averaged 5 years 5 months with five specialty interactions and 21.8 in-person visits per year per child. Seven clusters of care were identified, including: musculoskeletal and function; neurological; high-frequency/urgent care services; procedures; comorbid diagnoses; development and behavioral; and primary care. Network analysis showed shared membership among several clusters. INTERPRETATION: Coordination of care is a central element for children with CP. Medical informatics, machine learning, and big data approaches provide unique insights into care delivery to inform approaches to improve outcomes for children with CP. What this paper adds Seven primary clusters of care were identified: musculoskeletal and function; neurological; high-frequency/urgent care services; procedures; comorbid diagnoses; development and behavioral; and primary care. The in-person to care coordination visit ratio was 1:5 overall for healthcare encounters. Most interactions with care teams occur outside of in-person visits. The ratio of in-person to care coordination activities differ by specialty.

Patient monitoring as a predictor of blood culture results in a tertiary neonatal intensive care unit.

We present a mesoergonomic approach to the early detection of neonatal sepsis, analyzing clinical data for 4999 patients from a neo-natal intensive care unit to predict positive culture results. The Apgar score at birth predicted positive results. For neonates with poor and intermediate Apgar scores, culture results for monitored infants were more likely to be positive than those for unmonitored infants. Thus, the medical staff tended to monitor infants who eventually had a greater chance for positive test results. A cost-effectiveness analysis indicated that for infants with high Apgar scores, the physician should decide whether to obtain a blood culture, based on the patient's characteristics. For infants with lower Apgar scores, it may be advisable to obtain a blood culture whenever one decides to monitor a neonate. The study demonstrates that staff decisions regarding a patient can serve as input for further clinical decision-making.

Early prediction of encephalopathic transformation in children with benign epilepsy with centro-temporal spikes.

BACKGROUND: Most children with Benign epilepsy with centro-temporal spikes (BECTS) undergo remission during late adolescence and do not require treatment. In a small group of patients, the condition may evolve to encephalopathic syndromes including epileptic encephalopathy with continuous spike-and-wave during sleep (ECSWS), or Landau-Kleffner Syndrome (LKS). Development of prediction models for early identification of at-risk children is of utmost importance. AIM: To develop a predictive model of encephalopathic transformation using data-driven approaches, reveal complex interactions to identify potential risk factors. METHODS: Data were collected from a cohort of 91 patients diagnosed with BECTS treated between the years 2005-2017 at a pediatric neurology institute. Data on the initial presentation was collected based on a novel BECTS ontology and used to discover potential risk factors and to build a predictive model. Statistical and machine learning methods were compared. RESULTS: A subgroup of 18 children had encephalopathic transformation. The least absolute shrinkage and selection operator (LASSO) regression Model with Elastic Net was able to successfully detect children with ECSWS or LKS. Sensitivity and specificity were 0.83 and 0.44. The most notable risk factors were fronto-temporal and temporo-parietal localization of epileptic foci, semiology of seizure involving dysarthria or somatosensory auras. CONCLUSION: Novel prediction model for early identification of patients with BECTS at risk for ECSWS or LKS. This model can be used as a screening tool and assist physicians to consider special management for children predicted at high-risk. Clinical application of machine learning methods opens new frontiers of personalized patient care and treatment.

Novel Alzheimer's disease subtypes identified using a data and knowledge driven strategy.

The population of adults with Alzheimer's disease (AD) varies in needs and outcomes. The heterogeneity of current AD diagnostic subgroups impedes the use of data analytics in clinical trial design and translation of findings into improved care. The purpose of this project was to define more clinically-homogeneous groups of AD patients and link clinical characteristics with biological markers. We used an innovative big data analysis strategy, the 3C strategy, that incorporates medical knowledge into the data analysis process. A large set of preprocessed AD Neuroimaging Initiative (ADNI) data was analyzed with 3C. The data analysis yielded 6 new disease subtypes, which differ from the assigned diagnosis types and present different patterns of clinical measures and potential biomarkers. Two of the subtypes, "Anosognosia dementia" and "Insightful dementia", differentiate between severe participants based on clinical characteristics and biomarkers. The "Uncompensated mild cognitive impairment (MCI)" subtype, demonstrates clinical, demographic and imaging differences from the "Affective MCI" subtype. Differences were also observed between the "Worried Well" and "Healthy" clusters. The use of data-driven analysis yielded sub-phenotypic clinical clusters that go beyond current diagnoses and are associated with biomarkers. Such homogenous sub-groups can potentially form the basis for enhancement of brain medicine research.

Development of Ontology for Self-limited Epilepsy with Centrotemporal Spikes and Application of Data Mining Algorithms to Identify New Subtypes.

BACKGROUND: Benign rolandic epilepsy or benign childhood epilepsy with centrotemporal spikes (BCECTS) is a common childhood epileptic syndrome. The syndrome resolves in adolescence, but 1-7% of patients have an atypical presentation, some of which require aggressive medical treatment. Early treatment may prevent complications and neurocognitive deterioration. Variants include Landau-Kleffner syndrome (LKS) and electrical status epilepticus during sleep (ESES). OBJECTIVES: To determine data driven identification of risk factors and characterization of new subtypes of BCECTS based on anontology. To use data mining analysis and correlation between the identified groups and known clinical variants. METHODS: We conducted a retrospective cohort study comprised of 104 patients with a diagnosis of BCECTS and a minimum of 2 years of follow-up, between the years 2005 and 2017. The medical records were obtained from the epilepsy service unit of the pediatric neurology department at Dana-Dwek Hospital, Tel Aviv Sourasky Medical Center. We developed a BCECTS ontology and performed data preprocessing and analysis using the R Project for Statistical Computing (https://www.r-project.org/) and machine learning tools to identify risk factors and characterize subgroups. RESULTS: The ontology created a uniform and understandable infrastructure for research. With the ontology, a more precise characterization of clinical symptoms and EEG activity of BCECTS was possible. Risk factors for the development of severe atypical presentations were identified: electroencephalography (EEG) with spike wave (P < 0.05), EEG without evidence of left lateralization (P < 0.05), and EEG localization (centrotemporal, frontal, or frontotemporal) (P < 0.01). CONCLUSIONS: Future use of the ontology infrastructure for expanding characterization for multicenter studies as well as future studies of the disease are needed. Identifying subgroups and adapting them to known clinical variants will enable identification of risk factors, improve prediction of disease progression, and facilitate adaptation of more accurate therapy. Early identification and frequent follow-up may have a significant impact on the prognosis of the atypical variants.