Incidence of Type 2 Diabetes in Children With Nonalcoholic Fatty Liver Disease.

BACKGROUND & AIMS: Type 2 diabetes (T2D) is a growing problem in children. Children with NAFLD are at potentially high risk for developing T2D; however, the incidence of T2D in this population is unknown. This study aimed to determine the incidence of T2D in children with NAFLD and identify associated risk factors. METHODS: Children with NAFLD enrolled in the Nonalcoholic Steatohepatitis Clinical Research Network were followed longitudinally. Incidence of T2D was determined by using clinical history and fasting laboratory values. Cumulative incidence curves were developed for time to T2D. A Cox regression multivariable model was constructed using best subsets Akaike's Information Criteria selection. RESULTS: This study included 892 children with NAFLD and with a mean age of 12.8 years (2.7) followed for 3.8 years (2.3) with a total 3234 person-years at risk. The incidence rate of T2D was 3000 new cases per 100,000 person-years at risk. At baseline, 63 children had T2D, and during follow-up, an additional 97 children developed incident T2D, resulting in a period prevalence of 16.8%. Incident T2D was significantly higher in females versus males (hazard ratio [HR], 1.8 [1.0-2.8]), associated with BMI z-score (HR, 1.8 [1.0-3.0]), and more severe liver histology including steatosis grade (HR, 1.3 [1.0-1.7]), and fibrosis stage (HR, 1.3 [1.0-1.5]). CONCLUSIONS: Children with NAFLD are at high risk for existing and incident T2D. In addition to known risk factors for T2D (female and BMI z-score), severity of liver histology at the time of NAFLD diagnosis was independently associated with T2D development. Targeted strategies to prevent T2D in children with NAFLD are needed.

Opportunities for Enhanced Transition of Care Preparation for Adolescents and Emerging Adults With Type 1 Diabetes: Use of the READDY Transition Tool.

There is an ongoing need to determine best practices for effective transition from pediatric to adult care for adolescents and emerging adults (EAs) with type 1 diabetes given the potential for poor health outcomes post-transfer. This study evaluated self-reported confidence ratings as measured by the Readiness of Emerging Adults with Diabetes Diagnosed in Youth (READDY) tool among adolescents and EAs with type 1 diabetes and the association of the confidence ratings with clinical and demographic characteristics, as well as provider documentation of relevant anticipatory guidance topics. The READDY is a diabetes-specific tool used to collect patient-reported confidence in transition preparation topics to target educational interventions. These interventions are divided into four domains: Diabetes Knowledge, Health System Navigation, Insulin Self-Management, and Health Behaviors. A retrospective chart review was conducted of patients 15-24 years of age with type 1 diabetes who completed the READDY survey between January 2017 and January 2018 at a single center. Overall patient-reported confidence levels were high. However, adolescents and EAs endorsed their lowest levels of confidence on items assessing knowledge of alcohol, tobacco, sexual health, and the impact of diabetes on pregnancy (females only), with the percentages of low scores of 20.7, 25.9, 35.9, and 42.9%, respectively. Documentation of provider counseling about screening and prevention of diabetes comorbidities, alcohol use, and tobacco use was associated with scores in the higher range for the corresponding item in the READDY survey. These findings highlight an opportunity to create interventions related to developmentally important topics for adolescents and EAs with type 1 diabetes to enhance successful transition preparation.

High Body Mass Index in Infancy May Predict Severe Obesity in Early Childhood.

OBJECTIVE: To characterize growth trajectories of children who develop severe obesity by age 6 years and identify clinical thresholds for detection of high-risk children before the onset of obesity. STUDY DESIGN: Two lean (body mass index [BMI] 5th to ≤75th percentile) and 2 severely obese (BMI ≥99th percentile) groups were selected from populations treated at pediatric referral and primary care clinics. A population-based cohort was used to validate the utility of identified risk thresholds. Repeated-measures mixed modeling and logistic regression were used for analysis. RESULTS: A total of 783 participants of normal weight and 480 participants with severe obesity were included in the initial study. BMI differed significantly between the severely obese and normal-weight cohorts by age 4 months (P < .001), at 1 year before the median age at onset of obesity. A cutoff of the World Health Organization (WHO) 85th percentile for BMI at 6, 12, and 18 months was a strong predictor of severe obesity by age 6 years (sensitivity, 51%-95%; specificity, 95%). This BMI threshold was validated in a second independent cohort (n = 2649), with a sensitivity of 33%-77% and a specificity of 74%-87%. A BMI ≥85th percentile in infancy increases the risk of severe obesity by age 6 years by 2.5-fold and the risk of clinical obesity by age 6 years by 3-fold. CONCLUSIONS: BMI trajectories in children who develop severe obesity by age 6 years differ from those in children who remain at normal weight by age 4-6 months, before the onset of obesity. Infants with a WHO BMI ≥85th percentile are at increased risk for developing severe obesity by age 6 years.

Bilateral cataracts in a 6-yr-old with new onset diabetes: a novel presentation of a known INS gene mutation.

The prevalence of diabetes-related cataracts during childhood is less than 1%. When cataracts occur, it is often in adolescent females with prolonged symptoms and significant hyperglycemia. Cataracts are not a classic feature of monogenic diabetes. We report a case of a 6-yr-old, previously healthy Caucasian male, who presented with bilateral acquired cataracts and was subsequently diagnosed with new onset diabetes. Additional symptoms at presentation included a several year history of polyuria and polydipsia, mild hepatomegaly, and short stature. Pertinent negatives include acanthosis nigricans, lipoatrophy, deafness, muscle weakness, or neuropathy. HbA1c was significantly elevated at diagnosis (>14%, 129.5 mmol/mol) without evidence of ketosis. Autoantibody testing was negative. Features of Mauriac syndrome (short stature, hepatomegaly) as well as acquired cataracts indicated long-standing hyperglycemia with sufficient insulin production to prevent ketone production and development of diabetic ketoacidosis. Whole exome sequencing was conducted and a de novo heterozygous mutation in the INS gene (c.94G>A; p.Gly32Ser) was identified. INS gene mutations are common causes of permanent neonatal diabetes but rare causes of antibody-negative diabetes in children. Importantly, INS gene mutations have not been previously associated with acquired cataracts. Knowledge of a monogenic cause of diabetes allows clinicians to tailor counseling and screening of diabetes-related comorbidities. In summary, this case highlights the need to consider testing for monogenic diabetes, specifically INS gene mutations, in pediatric patients with antibody-negative diabetes, especially if complications of prolonged hyperglycemia are present at diagnosis.

Health markers, depressive symptoms, and community deprivation in a type 2 diabetes multidisciplinary care clinic for youth.

INTRODUCTION: Type 2 diabetes disproportionately affects non-Hispanic/Latino Black and Hispanic/Latino youth. The purpose of this study was to examine whether differences in metabolic risk factors and depressive symptoms exist by race/ethnicity and socioeconomic deprivation and whether these impact clinic attendance and health markers over 1 year in a multidisciplinary type 2 diabetes clinic for youth. METHODS: This study was a retrospective chart review of 54 youth with type 2 diabetes who had both an initial and follow-up visit. Demographic information, metabolic health markers [body mass index (BMI), hemoglobin A1C, liver enzymes, lipid panel, and urine microalbumin], depressive symptoms, and clinic attendance data were obtained from the medical record. Patient address was geocoded to the census tract level to calculate community socioeconomic deprivation. RESULTS: Liver enzymes (ALT and AST) were significantly higher in patients identifying as Hispanic/Latino (ALT M = 97.0 ± 40.6, AST M = 53.6 ± 21.4) and lowest in patients identifying as non-Hispanic/Latino Black (ALT M = 23.1 ± 11.3, F = 10.6 p < .001; AST M = 23.1 ± 11.4, F = 8.1; p < .001) at initial visit. From initial visit to follow-up, there were significant improvements in ALT (F = 13.43, p < .001), AST (F = 6.58, p < .05), and BMIz (F = 18.39, p < .001). Patients identifying as Black or Hispanic showed an increase in depressive symptoms over time, while patients identifying as non-Hispanic White showed a decrease (F = 11.08; p < .05). Unexpectedly, patients living in areas with higher socioeconomic deprivation showed a decrease in hemoglobin A1C over time, while patients living in lower socioeconomic deprivation showed an increase (F = 5.15, p < .05). CONCLUSIONS: Differences exist in metabolic health parameters by race/ethnicity and by socioeconomic deprivation. Multidisciplinary care for youth with type 2 diabetes needs to consider and work to address the systems of inequity experienced by patients that drive disparities in health outcomes.

Glucose control predicts 2-year change in lipid profile in youth with type 1 diabetes.

OBJECTIVE: To test the hypothesis that a change in glycated hemoglobin (A1c) over a follow-up interval of approximately 2 years would be associated with concomitant changes in fasting lipids in individuals with type 1 diabetes (T1D). STUDY DESIGN: All subjects with T1D diagnosed in 2002-2005 in the SEARCH for Diabetes in Youth study with at least 2 study visits ∼12 and ∼24 months after an initial visit were included (age at initial visit, 10.6 ± 4.1 years; 48% female; diabetes duration, 10 ± 7 months; 76% non-Hispanic white; A1c = 7.7% ± 1.4%). Longitudinal mixed models were fit to examine the relationship between change in A1c and change in lipid levels (total cholesterol [TC], high-density lipoprotein-cholesterol [HDL-c], low-density lipoprotein-cholesterol [LDL-c], log triglycerides [TG], and non-HDL-c) with adjustment for possible confounders. RESULTS: Change in A1c over time was significantly associated with changes in TC, HDL-c, LDL-c, TG, and non-HDL-c over the range of A1c values. For example, for a person with an A1c of 10% and then a 2% decrease in A1c 2 years later (to 8%), the model predicted concomitant changes in TC (-0.29 mmol/L, -11.4 mg/dL), HDL-c (0.03 mmol/L, 1.3 mg/dL), LDL-c (-0.23 mmol/L, -9.0 mg/dL), and non-HDL-c (-0.32 mmol/L, -12.4 mg/dL) and an 8.5% decrease in TG (mmol/L). CONCLUSIONS: Improved glucose control over a 2-year follow-up was associated with a more favorable lipid profile but may be insufficient to normalize lipids in dyslipidemic T1D youth needing to decrease lipids to goal.

BMI Metrics Are Poor Predictors of Pediatric Nonalcoholic Fatty Liver Disease Severity.

Background: Alternative BMI metrics are superior to BMI z score (BMIz) in tracking obesity but have not been evaluated in patients with nonalcoholic fatty liver disease (NAFLD). Our objective was to evaluate whether BMI-adjusted z score (BMIaz) or BMI expressed as a percentage of the 95th percentile (%BMIp95) are better predictors of degree of alanine aminotransferase (ALT) elevation, a surrogate for NAFLD severity, compared with BMIz in patients with NAFLD. Methods: A retrospective study of 776 subjects aged 2-18 years with BMIz > 1.0 followed in a NAFLD subspecialty clinic was conducted. Regression analysis was used to determine predictors of elevated ALT. Results: There was no association between BMIz, BMIaz, or %BMIp95 and degree of ALT elevation using linear or logistic regression. Conclusion: These results do not support the use of alternative BMI metrics for evaluating NAFLD severity. Future studies should investigate longitudinal assessments and correlation with histology.

Nonalcoholic Fatty Liver Disease in Young Children with Obesity.

Background: To evaluate the prevalence of suspected nonalcoholic fatty liver disease (NAFLD) in young children with obesity and determine associated risk factors. Methods: Retrospective single-center study of children with obesity, ages 2-6 years. Suspected NAFLD was defined as an alanine aminotransferase (ALT) >30 U/L. Multivariable analyses were performed to determine predictors of elevated ALT. Results: Among 237 children 2-6 years old, 35% had elevated ALT. Multivariable analysis showed that higher BMI z score [odds ratio (OR): 1.5 confidence interval (95% CI: 1.04-1.92)] and higher gamma-glutamyl transferase (GGT) [OR: 21.3 (95% CI: 3.7-121.1)] predicted elevated ALT. Of those with ≥2 ALT levels, 38% (n = 33/86) had a persistently elevated ALT (median ALT >30 U/L). Only 7% of patients with ALT >30 U/L underwent further testing to evaluate for alternative causes of liver disease. Conclusion: Suspected NAFLD is common in young children with obesity and predicted by obesity severity and GGT. Other cardiometabolic markers were equivalent between those with normal vs. elevated ALT, suggesting NAFLD onset may precede development of comorbidities. Earlier screening will enable prompt diagnosis and intervention, which may prevent or delay the onset of cardiometabolic diseases commonly associated with NAFLD in adolescence and adulthood.

Development and Implementation of a Multidisciplinary Clinic Focused on the Care of Adolescents with Youth-Onset Type 2 Diabetes.

Introduction: Diabetes self-management education and lifestyle interventions are the cornerstones of type 2 diabetes (T2D) care; however, the higher risk of comorbidities among youth with T2D requires a comprehensive care model. Traditionally, sub-specialty care relies on a referral model placing the burden on patients/families. In response, we developed a pediatric T2D multidisciplinary clinic (MDC)-A single physical location where patients can access various sub-specialists. The goals of the MDC are to aid with lifestyle modifications and provide referral/access to sub-specialists within the MDC, as determined through screening labs and assessment tools. Methods: We conducted a retrospective chart review of youth seen in the T2D MDC clinic at Cincinnati Children's Hospital from 1/2020 to 12/2021. We evaluated the frequency that youth met with each specialist and completion rates of annual screening labs. Results: The cohort consisted of 227 youth with T2D (mean age 17.6 years, mean BMI 40.9kg/m2, 64% female, 50% Black or African American, 65% public insurance). All patients met with a diabetes provider and 81.2% met with a registered dietitian/certified diabetes education specialist. Exercise physiology met with 51.5% of patients, gastroenterology met with 34.8% of patients, social work met with 44.1% of patients, clinical psychology met with 27.3% of patients, and bariatric surgery met with 9.7% of patients. Percent completion of annual labs were: 98.2% for HbA1c, 84.6% for urine microalbumin, 83.7% for lipids, 90% for liver function, 59.5% for retinopathy, and 45.4% for the Patient Health Questionnaire-9. Conclusion: The majority of patients received diabetes and nutrition education and annual screening labs. Exercise counseling and sub-specialty care remain below 60% in part due to services not being available at every MDC. Our goals are to increase access to subspecialty care within the MDC's and consider additional care delivery methods to provide comprehensive care to youth with T2D.

A metadata framework for computational phenotypes.

With the burgeoning development of computational phenotypes, it is increasingly difficult to identify the right phenotype for the right tasks. This study uses a mixed-methods approach to develop and evaluate a novel metadata framework for retrieval of and reusing computational phenotypes. Twenty active phenotyping researchers from 2 large research networks, Electronic Medical Records and Genomics and Observational Health Data Sciences and Informatics, were recruited to suggest metadata elements. Once consensus was reached on 39 metadata elements, 47 new researchers were surveyed to evaluate the utility of the metadata framework. The survey consisted of 5-Likert multiple-choice questions and open-ended questions. Two more researchers were asked to use the metadata framework to annotate 8 type-2 diabetes mellitus phenotypes. More than 90% of the survey respondents rated metadata elements regarding phenotype definition and validation methods and metrics positively with a score of 4 or 5. Both researchers completed annotation of each phenotype within 60 min. Our thematic analysis of the narrative feedback indicates that the metadata framework was effective in capturing rich and explicit descriptions and enabling the search for phenotypes, compliance with data standards, and comprehensive validation metrics. Current limitations were its complexity for data collection and the entailed human costs.

Blood glucose monitoring and glycemic control in adolescents with type 1 diabetes: meter downloads versus self-report.

BACKGROUND: Reported frequencies of blood glucose monitoring (BGM) by both adolescents and their caregivers serve as adherence proxies when meter downloads are not available. Yet, correlates of reported BGM frequencies and their predictive utility are understudied. OBJECTIVE: To identify sociodemographic, psychological, and disease-specific correlates of reported BGM frequencies in adolescents with type 1 diabetes and to explore the predictive utility of BGM indices on glycemic control. SUBJECTS: Study participants included caregivers and adolescents with type 1 diabetes (N=143, 13-18 yr) receiving diabetes treatment at a tertiary care setting. METHODS: At the initial visit, adolescents and caregivers reported on daily BGM frequencies. A sub-sample provided meter downloads. Adolescents also completed a depression inventory. Three months later, adolescents provided blood sampling for A1c assessment. RESULTS: Multivariate general linear modeling identified that older adolescent age and more depressive symptoms were associated with reports of less frequent BGM. Two stepwise multivariate regression models examined the predictive utility of BGM indices (i.e., adolescent-reported BGM, caregiver-reported BGM, meter download) on glycemic control. Caregiver-reported BGM frequency predicted glycemic control in the absence of meter download data (p<0.001). However, when clinical and contextual variables were included, meter download data were the most robust predictor of glycemic control (p<0.0001). CONCLUSIONS: Meter downloads have the most robust association with glycemic control when contextual variables are considered. Caregiver-reported BGM frequencies can serve as reliable substitutes in the absence of meter download, but they may not be as reliable in adolescents with depressive symptoms.

New directions in childhood obesity research: how a comprehensive biorepository will allow better prediction of outcomes.

BACKGROUND: Childhood obesity is associated with the early development of diseases such as type 2 diabetes and cardiovascular disease. Unfortunately, to date, traditional methods of research have failed to identify effective prevention and treatment strategies, and large numbers of children and adolescents continue to be at high risk of developing weight-related disease. AIM: To establish a unique 'biorepository' of data and biological samples from overweight and obese children, in order to investigate the complex 'gene × environment' interactions that govern disease risk. METHODS: The 'Childhood Overweight BioRepository of Australia' collects baseline environmental, clinical and anthropometric data, alongside storage of blood samples for genetic, metabolic and hormonal profiles. Opportunities for longitudinal data collection have also been incorporated into the study design. National and international harmonization of data and sample collection will achieve required statistical power. RESULTS: Ethical approval in the parent site has been obtained and early data indicate a high response rate among eligible participants (71%) with a high level of compliance for comprehensive data collection (range 56% to 97% for individual study components). Multi-site ethical approval is now underway. CONCLUSIONS: In time, it is anticipated that this comprehensive approach to data collection will allow early identification of individuals most susceptible to disease, as well as facilitating refinement of prevention and treatment programs.

Stability of adolescent body mass index during three years of follow-up.

OBJECTIVE: A 4-year longitudinal study was conducted to determine the prevalence of overweight, detect shifts in body mass index (BMI) distribution, and determine which adolescents were at risk for pathologic weight gain. STUDY DESIGN: BMI was analyzed in 1746 adolescents in years 1 (2001-2002) through 4 (2004-2005) of a school-based study. Changes in BMI-Z according to baseline BMI category were examined with general linear modeling. RESULTS: In year 1, the prevalence of at risk for overweight (BMI = 85th-95th percentile) and overweight (BMI > or = 95th percentile) was 19.1% and 18.1%, respectively. Between years 1 and 4, the cohort exhibited no increase in the prevalence of at risk for overweight (19.1% versus 17.2%) or overweight (18.2% versus 18.8%; P > .5). The mean BMI Z-score (BMI-Z) for the cohort was identical in years 1 and 4 (0.66 +/- 1.0 Z-score units). Although the overall cohort exhibited stability in BMI-Z, individuals at the lowest categories of BMI-Z (year 1 BMI Z-score < 0) exhibited significant increases in BMI Z-score by year 4 (P < .01), with lean girls gaining more than lean boys (P for difference < .007). CONCLUSION: The study cohort exhibited stability in adiposity during 3 years of follow-up. However, lean adolescents, particularly girls, experienced significant increases in BMI-Z, beyond that expected for age- and sex-related growth.

Approach to management of malignant hyperthermia-like syndrome in pediatric diabetes mellitus.

BACKGROUND: Hyperglycemic hyperosmolar nonketotic syndrome (HHNS) is usually associated with type 2 diabetes mellitus and is rare in children. However, a fatal malignant hyperthermia-like syndrome (MHLS) with rhabdomyolysis associated with new-onset diabetes mellitus and HHNS in adolescents has been described. DESIGN/METHODS: Case series. RESULTS: A 16-yr-old obese male (case A) and a 10-yr-old mid-pubertal nonobese female (case B) presented within a 6-month period with emesis, altered mental status, blood glucose >1600 mg/dL, and laboratory evidence of rhabdomyolysis. Case A developed fever after initiation of insulin therapy, along with refractory hypotension and multiorgan failure. He died 14 hrs after admission. Case B developed fever before insulin therapy, was treated with dantrolene, and made a full recovery. Metabolic workup showed evidence of short-chain acyl-CoA dehydrogenase (SCAD) deficiency. CONCLUSIONS: We report two cases of malignant hyperthermia-like syndrome associated with HHNS in adolescents. Their respective fluid management and clinical courses are described. Dantrolene therapy should be initiated immediately after this syndrome is recognized. We believe it is unlikely insulin is the sole trigger for MHLS. Case B is unique in that there was evidence of SCAD deficiency, a metabolic defect that we propose could lead to MHLS. We recommend that all patients with HHNS and MHLS be evaluated for an underlying metabolic disorder.

Comparing Two Waist-to-Height Ratio Measurements with Cardiometabolic Risk Factors among Youth with Diabetes.

BACKGROUND: Waist circumference (WC) is commonly measured by either the World Health Organization (WHO) or National Health and Nutrition Examination Survey (NHANES) protocol. OBJECTIVE: Compare the associations of WHO vs. NHANES WC-to-height ratio (WHtR) protocols with cardiometabolic risk factors (CMRFs) in a sample of youth with diabetes. METHODS: For youth (10-19 years old with type 1 [N=3082] or type 2 [N=533] diabetes) in the SEARCH for Diabetes in Youth Study, measurements were obtained of WC (by two protocols), weight, height, fasting lipids (total cholesterol, triglycerides, HDL cholesterol, Non-HDL cholesterol) and blood pressures. Associations of CMRFs with WHO and NHANES WHtR were modeled stratified by body mass index (BMI) percentiles for age/sex: lower BMI (<85th BMI percentile; N=2071) vs. higher BMI (≥85th percentile; N=1594). RESULTS: Among lower-BMI participants, both NHANES and WHO WHtR were associated (p<0.005) with all CMRFs except blood pressure. Among higher-BMI participants, both NHANES and WHO WHtR were associated (p<0.05) with all CMRFs. WHO WHtR was more strongly associated (p<0.05) than NHANES WHtR with triglycerides, non-HDL cholesterol, and systolic blood pressure in lower-BMI participants. Among high-BMI participants, WHO WHtR was more strongly associated (p<0.05) than NHANES WHtR with triglycerides and systolic blood pressure. CONCLUSION: Among youth with diabetes, WHtR calculated from either WC protocol captures cardiometabolic risk. The WHO WC protocol may be preferable to NHANES WC.

Prevalence of Prediabetes and Type 2 Diabetes in Children With Nonalcoholic Fatty Liver Disease.

IMPORTANCE: Nonalcoholic fatty liver disease (NAFLD) is a major chronic liver disease in children in the United States and is associated with insulin resistance. In adults, NAFLD is also associated with type 2 diabetes. To our knowledge, the prevalence of type 2 diabetes in children with NAFLD is unknown. OBJECTIVE: To determine the prevalence of type 2 diabetes and prediabetes in children with NAFLD and assess type 2 diabetes and prediabetes as risk factors for nonalcoholic steatohepatitis (NASH). DESIGN, SETTING, AND PARTICIPANTS: This was a multicenter, cross-sectional study at 12 pediatric clinical centers across the United States participating in the National Institute of Diabetes and Digestive and Kidney Diseases NASH Clinical Research Network. Children younger than 18 years with biopsy-confirmed NAFLD enrolled in the NASH Clinical Research Network. MAIN OUTCOMES AND MEASURES: The presence of type 2 diabetes and prediabetes as determined by American Diabetes Association screening criteria using clinical history and fasting laboratory values. RESULTS: There were 675 children with NAFLD included in the study with a mean age of 12.6 years and mean body mass index (calculated as weight in kilograms divided by height in meters squared) of 32.5. Most of the children were boys (480 of 675) and Hispanic (445 of 675).The estimated prevalence of prediabetes was 23.4% (95% CI, 20.2%-26.6%), and the estimated prevalence of type 2 diabetes was 6.5% (95% CI, 4.6%-8.4%). Girls with NAFLD had 1.6 (95% CI, 1.04-2.40) times greater odds of having prediabetes and 5.0 (95% CI, 2.49-9.98) times greater odds of having type 2 diabetes than boys with NAFLD. The prevalence of NASH was higher in those with type 2 diabetes (43.2%) compared with prediabetes (34.2%) or normal glucose (22%) (P < .001). The odds of having NASH were significantly higher in those with prediabetes (OR, 1.9; 95% CI, 1.21-2.9) or type 2 diabetes (OR, 3.1; 95% CI, 1.5-6.2) compared with those with normal glucose. CONCLUSIONS AND RELEVANCE: In this study, nearly 30% of children with NAFLD also had type 2 diabetes or prediabetes. These children had greater odds of having NASH and thus were at greater long-term risk for adverse hepatic outcomes.

Suboptimal Clinical Documentation in Young Children with Severe Obesity at Tertiary Care Centers.

Background and Objectives. The prevalence of severe obesity in children has doubled in the past decade. The objective of this study is to identify the clinical documentation of obesity in young children with a BMI ≥ 99th percentile at two large tertiary care pediatric hospitals. Methods. We used a standardized algorithm utilizing data from electronic health records to identify children with severe early onset obesity (BMI ≥ 99th percentile at age <6 years). We extracted descriptive terms and ICD-9 codes to evaluate documentation of obesity at Boston Children's Hospital and Cincinnati Children's Hospital and Medical Center between 2007 and 2014. Results. A total of 9887 visit records of 2588 children with severe early onset obesity were identified. Based on predefined criteria for documentation of obesity, 21.5% of children (13.5% of visits) had positive documentation, which varied by institution. Documentation in children first seen under 2 years of age was lower than in older children (15% versus 26%). Documentation was significantly higher in girls (29% versus 17%, p < 0.001), African American children (27% versus 19% in whites, p < 0.001), and the obesity focused specialty clinics (70% versus 15% in primary care and 9% in other subspecialty clinics, p < 0.001). Conclusions. There is significant opportunity for improvement in documentation of obesity in young children, even years after the 2007 AAP guidelines for management of obesity.

Developing an Algorithm to Detect Early Childhood Obesity in Two Tertiary Pediatric Medical Centers.

OBJECTIVE: The objective of this study is to develop an algorithm to accurately identify children with severe early onset childhood obesity (ages 1-5.99 years) using structured and unstructured data from the electronic health record (EHR). INTRODUCTION: Childhood obesity increases risk factors for cardiovascular morbidity and vascular disease. Accurate definition of a high precision phenotype through a standardize tool is critical to the success of large-scale genomic studies and validating rare monogenic variants causing severe early onset obesity. DATA AND METHODS: Rule based and machine learning based algorithms were developed using structured and unstructured data from two EHR databases from Boston Children's Hospital (BCH) and Cincinnati Children's Hospital and Medical Center (CCHMC). Exclusion criteria including medications or comorbid diagnoses were defined. Machine learning algorithms were developed using cross-site training and testing in addition to experimenting with natural language processing features. RESULTS: Precision was emphasized for a high fidelity cohort. The rule-based algorithm performed the best overall, 0.895 (CCHMC) and 0.770 (BCH). The best feature set for machine learning employed Unified Medical Language System (UMLS) concept unique identifiers (CUIs), ICD-9 codes, and RxNorm codes. CONCLUSIONS: Detecting severe early childhood obesity is essential for the intervention potential in children at the highest long-term risk of developing comorbidities related to obesity and excluding patients with underlying pathological and non-syndromic causes of obesity assists in developing a high-precision cohort for genetic study. Further such phenotyping efforts inform future practical application in health care environments utilizing clinical decision support.