Finding the Right Distribution for Highly Skewed Zero-inflated Clinical Data

Discrete, highly skewed distributions with excess numbers of zeros often result in biased estimates and misleading inferences if the zeros are not properly addressed. A clinical example of children with electrophysiologic disorders in which many of the children are treated without surgery is provided. The purpose of the current study was to identify the optimal modeling strategy for highly skewed, zeroinflated data often observed in the clinical setting by: (a) simulating skewed, zero-inflated count data; (b) fitting simulated data with Poisson, Negative Binomial, Zero-Inflated Poisson (ZIP) and Zero-inflated Negative Binomial (ZINB) models; and, (c) applying the aforementioned models to actual, highlyskewed, clinical data of children with an EP disorder. The ZIP model was observed to be the optimal model based on traditional fit statistics as well as estimates of bias, mean-squared error, and coverage. &nbsp

Psychometric properties of the ScreenQ for measuring digital media use in Portuguese young children

Aim: Digital media use is prevalent among children and linked to potential developmental and health risks, but validated measures of children's digital media use are lacking. The aim of this study was to validate the Portuguese version of the ScreenQ with three distinct children's age groups. Methods: Parents of children living in Portugal completed an online survey including the 16-item version of the ScreenQ and items related to home activities and digital media use. A combination of classical and modern theory (Rasch) methods was used for analysis. Results: A total of 549 mothers and 51 fathers of 325 girls and 322 boys from 6 months to 9 years and 11 months old responded to the survey. Point-measure correlations were all positive and endorsement of item values were within acceptable ranges. Cronbach's coefficient α was acceptable for a new measure, and test–retest reliability was high. Statistically significant correlations were found between ScreenQ total scores and relevant demographic, play-related, parenting and digital media use items. Conclusion: The Portuguese version of the ScreenQ exhibited sound psychometric properties, including internal consistency and concurrent validity referenced to external items. Higher ScreenQ scores were correlated with higher digital media multitasking, lower parent–child interaction, and higher concerns regarding child's learning and behaviour

Intermediate outcomes after the Fontan procedure in the current era

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Genetic factors are important determinants of impaired growth after infant cardiac surgery

ObjectivesWe sought to estimate the prevalence and identify the predictors of impaired growth after infant cardiac surgery.MethodsWe performed a secondary analysis of a prospective study of the role of apolipoprotein E gene polymorphisms on neurodevelopment in young children after infant cardiac surgery. Prevalence estimates for growth velocity were derived by using anthropometric measures (weight and head circumference) obtained at birth and at 4 years of age. Genetic evaluation was also performed. Growth measure z scores were calculated by using World Health Organization Child Growth Standards. Growth velocity was evaluated by using 2 different techniques: first by clustering the children into one of 3 growth velocity subgroups based on z scores (impaired growth, difference < −0.5 standard deviation; stable growth, difference of −0.5 to 0.5 standard deviation; and improving growth, difference > 0.5 SD) and second by using continuous difference scores. Statistical analyses were conducted with a combination of proportional odds models for the ordered categories and simple linear regression for the continuous outcomes.ResultsThree hundred nineteen full-term subjects had complete anthropometric measures for weight and head circumference at birth and 4 years. The cohort was 56% male. Genetic examinations were available for 97% (309/319) of the cohort (normal, 74%; definite or suspected genetic abnormality, 26%). Frequency counts for weight categories were as follows: impaired growth, 37%; stable growth, 31%; and improving growth, 32%. Frequency counts for head circumference categories were as follows: impaired growth, 39%; stable growth, 28%; and improving growth, 33%. The presence of a definite or suspected genetic syndrome (P = .04) was found to be a predictor of impaired growth for weight but not for head circumference. When growth z scores were used as continuous outcomes, the apolipoprotein E ε2 allele was found to be predictive of lower z scores for both weight (P = .02) and head circumference (P = .03).ConclusionsImpaired growth for both weight and head circumference is common (both >30%) in this cohort of children after infant cardiac surgery. Both the apolipoprotein E ε2 allele and the presence of a definite or suspected genetic syndrome were associated with impaired weight growth velocity. The apolipoprotein E ε2 allele was also associated with impaired growth velocity for head circumference. Persistent poor growth might have long-term implications for the health and development of children with congenital heart defects

The impact of socio-economic status on health related quality of life for children and adolescents with heart disease

Background: Socioeconomic status (SES) is known to influence children’s health-related quality of life. Many SES indicators assess distinct dimensions of a family’s position rather than measuring the same underlying construct. Many researchers, however, see SES indicators as interchangeable. The primary aim of this study was to determine which measure of SES had the strongest impact on health-related quality of life. Methods: This is a secondary analysis of the Pediatric Cardiac Quality of Life Inventory Validation Study. The SES variables were family income, Hollingshead Index (occupational prestige), and highest parent educational attainment level. Health-related quality of life was measured using the Pediatric Cardiac Quality of Life Inventory. Correlations tested the relationship among the three SES indicators. Regression-based modeling was used to calculate the strength of the association between SES measures and the Pediatric Cardiac Quality of Life Inventory. Results: The correlations among the SES measures were moderately high, with the correlation between the Hollingshead Index and parental education being r = 0.62 (95% CI = 0.56-0.65). There were equally high correlations between family income and the Hollingshead (r = 0.61, 95% CI = 0.57-0.65) and a slightly lower correlation between family income and parental education (r = 0.55, 95% CI = 0.52-0.59). Family income had the highest explanatory value compared to the Hollingshead Index or parental educational attainment, while controlling for sex, race, current cardiac status, and original diagnosis, accounting for 4-5% of the variation in patient and parent Pediatric Cardiac Quality of Life Inventory Total score, respectively, compared to the other SES measures. Conclusion: Family income as an SES measure demonstrated the greatest fidelity with respect to health-related quality of life as measured by the Pediatric Cardiac Quality of Life Inventory across respondent groups and explained more of the variation compared to the Hollingshead Index or highest parental educational attainment

Genetic Testing in Pediatric Left Ventricular Noncompaction

Background: Left ventricular noncompaction (LVNC) can occur in isolation or can co-occur with a cardiomyopathy phenotype or cardiovascular malformation. The yield of cardiomyopathy gene panel testing in infants, children, and adolescents with a diagnosis of LVNC is unknown. By characterizing a pediatric population with LVNC, we sought to determine the yield of cardiomyopathy gene panel testing, distinguish the yield of testing for LVNC with or without co-occurring cardiac findings, and define additional factors influencing genetic testing yield. Methods and results: One hundred twenty-eight individuals diagnosed with LVNC at ≤21 years of age were identified, including 59% with idiopathic pathogenesis, 32% with familial disease, and 9% with a syndromic or metabolic diagnosis. Overall, 75 individuals had either cardiomyopathy gene panel (n=65) or known variant testing (n=10). The yield of cardiomyopathy gene panel testing was 9%. The severity of LVNC by imaging criteria was not associated with positive genetic testing, co-occurring cardiac features, pathogenesis, family history, or myocardial dysfunction. Individuals with isolated LVNC were significantly less likely to have a positive genetic testing result compared with those with LVNC and co-occurring cardiomyopathy (0% versus 12%, respectively; P<0.01). Conclusions: Genetic testing should be considered in individuals with cardiomyopathy co-occurring with LVNC. These data do not suggest an indication for cardiomyopathy gene panel testing in individuals with isolated LVNC in the absence of a family history of cardiomyopathy

The Telehealth Enhancement of Adherence to Medication (TEAM) in pediatric IBD trial: Design and methodology

Medication nonadherence is a significant health care issue requiring regular behavioral treatment. Lack of sufficient health care resources and patient/family time commitment for weekly treatment are primary barriers to receiving appropriate self-management support. We describe the methodology of the Telehealth Enhancement of Adherence to Medication (TEAM) trial for medication nonadherence in pediatric inflammatory bowel disease (IBD). For this trial, participants 11–18 years of age will be recruited from seven pediatric hospitals and will complete an initial 4-week run in to assess adherence to a daily medication. Those who take less than 90% of their prescribed medication will be randomized. A total of 194 patients with IBD will be randomized to either a telehealth behavioral treatment (TBT) arm or education only (EO) arm. All treatment will be delivered via telehealth video conferencing. Patients will be assessed at baseline, post-treatment, 3-, 6-, and 12-months. We anticipate that participants in the TBT arm will demonstrate a statistically significant improvement at post-treatment and 3-, 6-, and 12-month follow-up compared to participants in the EO arm for both medication adherence and secondary outcomes (i.e., disease severity, patient quality of life, and health care utilization). If efficacious, the TEAM intervention could be disseminated broadly and reduce health care access barriers so that patients could receive much needed self-management intervention

Impact of Surgical Complexity on Health‐Related Quality of Life in Congenital Heart Disease Surgical Survivors

Background: Surgical complexity and related morbidities may affect long‐term patient quality of life (QOL). Aristotle Basic Complexity (ABC) score and Risk Adjustment in Congenital Heart Surgery (RACHS‐1) category stratify the complexity of pediatric cardiac operations. The purpose of this study was to examine the relationship between surgical complexity and QOL and to investigate other demographic and clinical variables that might explain variation in QOL in pediatric cardiac surgical survivors. Methods and Results: Pediatric Cardiac Quality of Life (PCQLI) study participants who had undergone cardiac surgery were included. The PCQLI database provided sample characteristics and QOL scores. Surgical complexity was defined by the highest ABC raw score or RACHS‐1 category. Relationships among surgical complexity and demographic, clinical, and QOL variables were assessed using ordinary least squares regression. A total of 1416 patient–parent pairs were included. Although higher ABC scores and RACHS‐1 categories were associated with lower QOL scores (P<0.005), correlation with QOL scores was poor to fair (r=−0.10 to −0.29) for all groups. Ordinary least squares regression showed weak association with R 2=0.06 to R 2=0.28. After accounting for single‐ventricle anatomy, number of doctor visits, and time since last hospitalization, surgical complexity scores added no additional explanation to the variance in QOL scores. Conclusions: ABC scores and RACHS‐1 categories are useful tools for morbidity and mortality predictions prior to cardiac surgery and quality of care initiatives but are minimally helpful in predicting a child's or adolescent's long‐term QOL scores. Further studies are warranted to determine other predictors of QOL variation

From clinical data management to clinical data science: Time for a new educational model

Abstract The purpose of this article is to propose and provide a blueprint for a graduate‐level curriculum in clinical data science, devoted to the measurement, acquisition, care, treatment, and inferencing of clinical research data. The curriculum presented here contains a series of five required core courses, five required research courses, and a list of potential electives. The coursework draws from but does not duplicate content from the foundational areas of biostatistics, clinical medicine, biomedical informatics, and regulatory affairs, and may be reproduced by any institution interested in and capable of offering such a program. This new curriculum in “clinical” data science will prepare students for work in academic, industry, and government research settings as well as offer a unifying knowledge base for the profession