Tracking the burden, distribution, and impact of Post-COVID conditions in diverse populations for children, adolescents, and adults (Track PCC): passive and active surveillance protocols.

BACKGROUND: Track PCC includes five geographic surveillance sites to conduct standardized population-based surveillance to estimate and track Post-COVID Conditions (PCC) by age, sex, race/ethnicity, geographic area, severity of initial infection, and risk factors among persons with evidence of SARS-CoV-2 infection (based on the Council of State and Territorial Epidemiologist [CSTE] case definitions for confirmed cases or laboratory-confirmed evidence of infection). METHODS: The study will estimate the incidence, prevalence, including temporal trends, and duration and severity of PCC symptoms, among children, adolescents, and adults. PCCs include a broad range of symptoms and conditions that continue or develop after acute SARS-CoV-2 infection or COVID-19 illness. Surveillance includes both passive and active components for diverse populations in Arizona, Indiana, and Utah as well as the Bronx Borough, NY, and part of Philadelphia County, PA. Passive surveillance will utilize electronic health records and health information exchanges within each site catchment area to longitudinally follow persons with COVID-19 to estimate PCC occurring at least 30 days after acute COVID-19 illness. Active surveillance will utilize self-report of PCCs from detailed surveys of persons ages 7 years and older with evidence of SARS-CoV-2 infection in the past 3 months. Respondents will complete follow-up surveys at 6-, 12- and 18-months post-infection. DISCUSSION: These data can help identify which groups are most affected by PCC, and what health differences among demographic groups exist, as well as indicate potential barriers to care. These additional levels of granularity can inform public health action and help direct needed clinical care for patients.

Transparent deep learning to identify autism spectrum disorders (ASD) in EHR using clinical notes.

OBJECTIVE: Machine learning (ML) is increasingly employed to diagnose medical conditions, with algorithms trained to assign a single label using a black-box approach. We created an ML approach using deep learning that generates outcomes that are transparent and in line with clinical, diagnostic rules. We demonstrate our approach for autism spectrum disorders (ASD), a neurodevelopmental condition with increasing prevalence. METHODS: We use unstructured data from the Centers for Disease Control and Prevention (CDC) surveillance records labeled by a CDC-trained clinician with ASD A1-3 and B1-4 criterion labels per sentence and with ASD cases labels per record using Diagnostic and Statistical Manual of Mental Disorders (DSM5) rules. One rule-based and three deep ML algorithms and six ensembles were compared and evaluated using a test set with 6773 sentences (N = 35 cases) set aside in advance. Criterion and case labeling were evaluated for each ML algorithm and ensemble. Case labeling outcomes were compared also with seven traditional tests. RESULTS: Performance for criterion labeling was highest for the hybrid BiLSTM ML model. The best case labeling was achieved by an ensemble of two BiLSTM ML models using a majority vote. It achieved 100% precision (or PPV), 83% recall (or sensitivity), 100% specificity, 91% accuracy, and 0.91 F-measure. A comparison with existing diagnostic tests shows that our best ensemble was more accurate overall. CONCLUSIONS: Transparent ML is achievable even with small datasets. By focusing on intermediate steps, deep ML can provide transparent decisions. By leveraging data redundancies, ML errors at the intermediate level have a low impact on final outcomes.

Understanding low COVID-19 booster uptake among US adults.

BACKGROUND: Vaccinations against SARS-CoV-2 have consistently been shown to reduce the risk of severe COVID-19 disease. However, uptake of boosters has stalled in the United States at less than 20% of the eligible population. The objective of this study was to assess the reasons for not having obtained a bivalent booster within an existing COVID-19 cohort. METHODS: A total of 2196 adult participants from the Arizona CoVHORT, a population-based cohort in the United States established in May 2020, who had received at least one dose of the COVID-19 vaccine, responded to surveys administered between February 13 and March 29, 2023 querying receipt of a bivalent booster and if not, the reasons for not receiving it. Descriptive statistics were employed, including frequencies of responses by participant characteristics, and multivariable logistic regression was used to assess the association between participant characteristics and selected themes for not having received the bivalent booster. RESULTS: The most commonly reported reason for not having been boosted was a prior SARS-CoV-2 infection (39.5%), followed by concern about vaccine side effects (31.5%), believing that the booster would not provide additional protection over the vaccines already received (28.6%), and concern about booster safety (23.4%) or that it would not protect from SARS-CoV-2 infection (23.1%). For themes related to reasons for not having been boosted, those 60 years of age or older were less likely to select items related to knowledge (OR: 0.24; 95% CI: 0.11-0.55) or logistical concerns (OR: 0.09; 95% CI: 0.03-0.30) about the vaccine; while those reporting Hispanic ethnicity were more likely to convey concerns about logistics than those reporting non-Hispanic ethnicity (OR: 2.15; 95% CI: 1.08-4.30). Finally, compared to college graduates, those with some college or technical school were significantly more likely to select items related to the risks and benefits of the bivalent vaccine not being clear as reasons for not having been boosted (OR: 2.41; 95% CI: 1.69-3.43). CONCLUSIONS: Improvement in booster uptake is necessary for optimal public health in the United States. The development of vaccines against SARS-CoV-2 occurred at an unprecedented speed, but vaccine uptake remains among the greatest current public health challenges as updated boosters continue to be developed and made available to the public. Interventions to improve vaccination rates require a variety of approaches.

The International SCN8A Patient Registry: A Scientific Resource to Advance the Understanding and Treatment of a Rare Pediatric Neurodevelopmental Syndrome.

Genetic variants in the SCN8A gene underlie a wide spectrum of neurodevelopmental phenotypes that range from severe epileptic encephalopathy to benign familial infantile epilepsy to neurodevelopmental delays with or without seizures. A host of additional comorbidities also contribute to the phenotypic spectrum. As a result of the recent identification of the genetic etiology and the length of time it often takes to diagnose patients, little data are available on the natural history of these conditions. The International SCN8A Patient Registry was developed in 2015 to fill gaps in understanding the spectrum of the disease and its natural history, as well as the lived experiences of individuals with SCN8A syndrome. Another goal of the registry is to collect longitudinal data from participants on a regular basis. In this article, we describe the construction and structure of the International SCN8A Patient Registry, present the type of information available, and highlight particular analyses that demonstrate how registry data can provide insights into the clinical management of SCN8A syndrome.

Survival From Birth Until Young Adulthood Among Individuals With Congenital Heart Defects: CH STRONG.

BACKGROUND: Limited population-based information is available on long-term survival of US individuals with congenital heart defects (CHDs). Therefore, we assessed patterns in survival from birth until young adulthood (ie, 35 years of age) and associated factors among a population-based sample of US individuals with CHDs. METHODS: Individuals born between 1980 and 1997 with CHDs identified in 3 US birth defect surveillance systems were linked to death records through 2015 to identify those deceased and the year of their death. Kaplan-Meier survival curves, adjusted risk ratios (aRRs) for infant mortality (ie, death during the first year of life), and Cox proportional hazard ratios for survival after the first year of life (aHRs) were used to estimate the probability of survival and associated factors. Standardized mortality ratios compared infant mortality, >1-year mortality, >10-year mortality, and >20-year mortality among individuals with CHDs with general population estimates. RESULTS: Among 11 695 individuals with CHDs, the probability of survival to 35 years of age was 81.4% overall, 86.5% among those without co-occurring noncardiac anomalies, and 92.8% among those who survived the first year of life. Characteristics associated with both infant mortality and reduced survival after the first year of life, respectively, included severe CHDs (aRR=4.08; aHR=3.18), genetic syndromes (aRR=1.83; aHR=3.06) or other noncardiac anomalies (aRR=1.54; aHR=2.53), low birth weight (aRR=1.70; aHR=1.29), and Hispanic (aRR=1.27; aHR=1.42) or non-Hispanic Black (aRR=1.43; aHR=1.80) maternal race and ethnicity. Individuals with CHDs had higher infant mortality (standardized mortality ratio=10.17), >1-year mortality (standardized mortality ratio=3.29), and >10-year and >20-year mortality (both standardized mortality ratios ≈1.5) than the general population; however, after excluding those with noncardiac anomalies, >1-year mortality for those with nonsevere CHDs and >10-year and >20-year mortality for those with any CHD were similar to the general population. CONCLUSIONS: Eight in 10 individuals with CHDs born between1980 and 1997 survived to 35 years of age, with disparities by CHD severity, noncardiac anomalies, birth weight, and maternal race and ethnicity. Among individuals without noncardiac anomalies, those with nonsevere CHDs experienced similar mortality between 1 and 35 years of age as in the general population, and those with any CHD experienced similar mortality between 10 and 35 years of age as in the general population.

Young adults with congenital heart disease heading to college: Are college health centers and providers prepared?

BACKGROUND: An estimated 1.4 million adults in the United States have congenital heart disease (CHD). As this population grows and many pursue postsecondary education, these adults' health care needs and concerns should be at the forefront for providers, particularly nurse practitioners, at college health centers. PURPOSE: To understand how college health centers and providers identify and manage the care of students with chronic conditions to further support their health care transition, with a focus on students with CHD. METHODOLOGY: Qualitative key informant interviews were performed with providers at five college health centers to understand the processes in place and the challenges health care providers on college campuses face when caring for students with CHD. RESULTS: Most of the college health centers did not have formalized processes in place to care for these students. Although many felt that they had the capabilities in their health centers to manage these students' maintenance/preventive care needs, fewer felt comfortable with their urgent or emergent care needs. The onus was often on students or parents/guardians to initiate these transitions. CONCLUSIONS: This study highlights some challenges to providing care to students with chronic conditions like CHD. More collaborative relationships with specialists may be critical to ensuring that all the care needs of chronic disease students are met on college campuses. IMPLICATIONS: Nurse practitioners, who often staff these clinics, are well positioned to support this transition onto campuses and lead the development of processes to identify these students, ease care management transitions, and ensure easy provider communication that allow students with chronic diseases to thrive on campus.

Cardiology Care and Loss to Follow-Up Among Adults With Congenital Heart Defects in CH STRONG.

Many of the estimated 1.4 million adults with congenital heart defects (CHDs) in the United States are lost to follow-up (LTF) despite recommendations for ongoing cardiology care. Using 2016 to 2019 CH STRONG (Congenital Heart Survey To Recognize Outcomes, Needs, and well-beinG) data, we describe cardiac care among community-based adults with CHD, born in 1980 to 1997, identified through state birth defects registries. Our estimates of LTF were standardized to the CH STRONG eligible population and likely more generalizable to adults with CHD than clinic-based data. Half of our sample were LTF and more than 45% had not received cardiology care in over 5 years. Of those who received care, only 1 in 3 saw an adult CHD physician at their last encounter. Not knowing they needed to see a cardiologist, being told they no longer needed cardiology care, and feeling "well" were the top reasons for LTF, and only half of respondents report doctors discussing the need for cardiac follow-up.

DMD Gene and Dystrophinopathy Phenotypes Associated With Mutations: A Systematic Review for Clinicians.

ABSTRACT: The diagnosis of Duchenne and Becker muscular dystrophy (DBMD) is made by genetic testing in approximately 95% of cases. Although specific mutations can be associated with skeletal muscle phenotype, pulmonary and cardiac comorbidities (leading causes of death in Duchenne) have not been associated with Duchenne muscular dystrophy mutation type or location and vary within families. Therefore, identifying predictors for phenotype severity beyond frameshift prediction is important clinically. We performed a systematic review assessing research related to genotype-phenotype correlations in DBMD. While there are severity differences across the spectrum and within mild and severe forms of DBMD, few protective or exacerbating mutations within the dystrophin gene were reported. Except for intellectual disability, clinical test results reporting genotypic information are insufficient for clinical prediction of severity and comorbidities and the predictive validity is too low to be useful when advising families. Including expanded information coupled with proposed severity predictions in clinical genetic reports for DBMD is critical for improving anticipatory guidance.

Statewide county-level autism spectrum disorder prevalence estimates-seven U.S. states, 2018.

PURPOSE: Autism spectrum disorder (ASD) prevalence information is necessary for identifying community needs such as addressing disparities in identification and services. METHODS: Seven Autism and Developmental Disabilities Monitoring (ADDM) Network sites participated in a pilot project to link statewide health and education data to generate statewide and county-level prevalence estimates for a broader age range for their states for the first time. RESULTS: Statewide prevalence of ASD for ages 3-21 years in 2018 ranged from 1.5% in Tennessee and Wisconsin to 2.3% in Arizona. The median county-level prevalence of ASD was 1.4% of residents ages 3-21 years. More boys than girls had ASD at all sites, and prevalence was lower among non-Hispanic Black, Hispanic, Asian/Pacific Islander, and American Indian/Alaska Native residents compared to non-Hispanic White residents at most sites. ASD prevalence estimates for children aged 8 years were similar to 2018 ADDM Network estimates that used record review to provide more in-depth information, but showed greater variation for children aged 4 years. CONCLUSIONS: Linkage of statewide data sets provides less detailed but actionable local information when more resource-intensive methods are not possible.

Differentiation of Pediatric-Onset Duchenne and Becker Muscular Dystrophy Subphenotypes Using Data from the Muscular Dystrophy Surveillance Tracking and Research Network (MD STARnet).

Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) phenotypes are used to describe disease progression in affected individuals. However, considerable heterogeneity has been observed across and within these two phenotypes, suggesting a spectrum of severity rather than distinct conditions. Characterizing the phenotypes and subphenotypes aids researchers in the design of clinical studies and clinicians in providing anticipatory guidance to affected individuals and their families. Using data from the Muscular Dystrophy Surveillance, Tracking, and Research Network (MD STARnet), we used K-means cluster analysis to group phenotypically similar males with pediatric-onset dystrophinopathy. We identified four dystrophinopathy clusters: Classical BMD, Classical DMD, late ambulatory DMD, and severe DMD. The clusters that we identified align with both 'classical' and 'non-classical' dystrophinopathy described in the literature. Individuals with dystrophinopathies have heterogenous clinical presentations that cluster into phenotypically similar groups. Use of clinically-derived phenotyping may provide a clearer understanding of disease trajectories, reduce variability in study results, and prevent exclusion of certain cohorts from analysis. Findings from studying subphenotypes may ultimately improve our ability to predict disease progression.

Early Identification of Autism Spectrum Disorder Among Children Aged 4 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2018.

PROBLEM/CONDITION: Autism spectrum disorder (ASD). PERIOD COVERED: 2018. DESCRIPTION OF SYSTEM: The Autism and Developmental Disabilities Monitoring Network is an active surveillance program that estimates ASD prevalence and monitors timing of ASD identification among children aged 4 and 8 years. This report focuses on children aged 4 years in 2018, who were born in 2014 and had a parent or guardian who lived in the surveillance area in one of 11 sites (Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin) at any time during 2018. Children were classified as having ASD if they ever received 1) an ASD diagnostic statement (diagnosis) in an evaluation, 2) a special education classification of ASD (eligibility), or 3) an ASD International Classification of Diseases (ICD) code. Suspected ASD also was tracked among children aged 4 years. Children who did not meet the case definition for ASD were classified as having suspected ASD if their records contained a qualified professional's statement indicating a suspicion of ASD. RESULTS: For 2018, the overall ASD prevalence was 17.0 per 1,000 (one in 59) children aged 4 years. Prevalence varied from 9.1 per 1,000 in Utah to 41.6 per 1,000 in California. At every site, prevalence was higher among boys than girls, with an overall male-to-female prevalence ratio of 3.4. Prevalence of ASD among children aged 4 years was lower among non-Hispanic White (White) children (12.9 per 1,000) than among non-Hispanic Black (Black) children (16.6 per 1,000), Hispanic children (21.1 per 1,000), and Asian/Pacific Islander (A/PI) children (22.7 per 1,000). Among children aged 4 years with ASD and information on intellectual ability, 52% met the surveillance case definition of co-occurring intellectual disability (intelligence quotient ≤70 or an examiner's statement of intellectual disability documented in an evaluation). Of children aged 4 years with ASD, 72% had a first evaluation at age ≤36 months. Stratified by census-tract-level median household income (MHI) tertile, a lower percentage of children with ASD and intellectual disability was evaluated by age 36 months in the low MHI tertile (72%) than in the high MHI tertile (84%). Cumulative incidence of ASD diagnosis or eligibility received by age 48 months was 1.5 times as high among children aged 4 years (13.6 per 1,000 children born in 2014) as among those aged 8 years (8.9 per 1,000 children born in 2010). Across MHI tertiles, higher cumulative incidence of ASD diagnosis or eligibility received by age 48 months was associated with lower MHI. Suspected ASD prevalence was 2.6 per 1,000 children aged 4 years, meaning for every six children with ASD, one child had suspected ASD. The combined prevalence of ASD and suspected ASD (19.7 per 1,000 children aged 4 years) was lower than ASD prevalence among children aged 8 years (23.0 per 1,000 children aged 8 years). INTERPRETATION: Groups with historically lower prevalence of ASD (non-White and lower MHI) had higher prevalence and cumulative incidence of ASD among children aged 4 years in 2018, suggesting progress in identification among these groups. However, a lower percentage of children with ASD and intellectual disability in the low MHI tertile were evaluated by age 36 months than in the high MHI group, indicating disparity in timely evaluation. Children aged 4 years had a higher cumulative incidence of diagnosis or eligibility by age 48 months compared with children aged 8 years, indicating improvement in early identification of ASD. The overall prevalence for children aged 4 years was less than children aged 8 years, even when prevalence of children suspected of having ASD by age 4 years is included. This finding suggests that many children identified after age 4 years do not have suspected ASD documented by age 48 months. PUBLIC HEALTH ACTION: Children born in 2014 were more likely to be identified with ASD by age 48 months than children born in 2010, indicating increased early identification. However, ASD identification among children aged 4 years varied by site, suggesting opportunities to examine developmental screening and diagnostic practices that promote earlier identification. Children aged 4 years also were more likely to have co-occurring intellectual disability than children aged 8 years, suggesting that improvement in the early identification and evaluation of developmental concerns outside of cognitive impairments is still needed. Improving early identification of ASD could lead to earlier receipt of evidence-based interventions and potentially improve developmental outcomes.

Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2018.

PROBLEM/CONDITION: Autism spectrum disorder (ASD). PERIOD COVERED: 2018. DESCRIPTION OF SYSTEM: The Autism and Developmental Disabilities Monitoring (ADDM) Network conducts active surveillance of ASD. This report focuses on the prevalence and characteristics of ASD among children aged 8 years in 2018 whose parents or guardians lived in 11 ADDM Network sites in the United States (Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin). To ascertain ASD among children aged 8 years, ADDM Network staff review and abstract developmental evaluations and records from community medical and educational service providers. In 2018, children met the case definition if their records documented 1) an ASD diagnostic statement in an evaluation (diagnosis), 2) a special education classification of ASD (eligibility), or 3) an ASD International Classification of Diseases (ICD) code. RESULTS: For 2018, across all 11 ADDM sites, ASD prevalence per 1,000 children aged 8 years ranged from 16.5 in Missouri to 38.9 in California. The overall ASD prevalence was 23.0 per 1,000 (one in 44) children aged 8 years, and ASD was 4.2 times as prevalent among boys as among girls. Overall ASD prevalence was similar across racial and ethnic groups, except American Indian/Alaska Native children had higher ASD prevalence than non-Hispanic White (White) children (29.0 versus 21.2 per 1,000 children aged 8 years). At multiple sites, Hispanic children had lower ASD prevalence than White children (Arizona, Arkansas, Georgia, and Utah), and non-Hispanic Black (Black) children (Georgia and Minnesota). The associations between ASD prevalence and neighborhood-level median household income varied by site. Among the 5,058 children who met the ASD case definition, 75.8% had a diagnostic statement of ASD in an evaluation, 18.8% had an ASD special education classification or eligibility and no ASD diagnostic statement, and 5.4% had an ASD ICD code only. ASD prevalence per 1,000 children aged 8 years that was based exclusively on documented ASD diagnostic statements was 17.4 overall (range: 11.2 in Maryland to 29.9 in California). The median age of earliest known ASD diagnosis ranged from 36 months in California to 63 months in Minnesota. Among the 3,007 children with ASD and data on cognitive ability, 35.2% were classified as having an intelligence quotient (IQ) score ≤70. The percentages of children with ASD with IQ scores ≤70 were 49.8%, 33.1%, and 29.7% among Black, Hispanic, and White children, respectively. Overall, children with ASD and IQ scores ≤70 had earlier median ages of ASD diagnosis than children with ASD and IQ scores >70 (44 versus 53 months). INTERPRETATION: In 2018, one in 44 children aged 8 years was estimated to have ASD, and prevalence and median age of identification varied widely across sites. Whereas overall ASD prevalence was similar by race and ethnicity, at certain sites Hispanic children were less likely to be identified as having ASD than White or Black children. The higher proportion of Black children compared with White and Hispanic children classified as having intellectual disability was consistent with previous findings. PUBLIC HEALTH ACTION: The variability in ASD prevalence and community ASD identification practices among children with different racial, ethnic, and geographical characteristics highlights the importance of research into the causes of that variability and strategies to provide equitable access to developmental evaluations and services. These findings also underscore the need for enhanced infrastructure for diagnostic, treatment, and support services to meet the needs of all children.

Disability Among Young Adults With Congenital Heart Defects: Congenital Heart Survey to Recognize Outcomes, Needs, and Well-Being 2016-2019.

Background Disabilities have implications for health, well-being, and health care, yet limited information is available on the percentage of adults with congenital heart defects (CHD) living with disabilities. We evaluated the prevalence of disability and associated characteristics among the 2016-2019 CH STRONG (Congenital Heart Survey to Recognize Outcomes, Needs, and Well-Being) population-based sample of 19- to 38-year-olds with CHD from 3 US locations. Methods and Results Prevalence of disability types (hearing, vision, cognition, mobility, self-care, living independently) were compared with similarly aged adults from the general population as estimated by the American Community Survey and standardized to the CH STRONG eligible population to reduce nonresponse bias and confounding. Health-related quality of life (HRQOL) was measured via Patient-Reported Outcomes Measurement Information System Global Health Scale T-scores standardized to US 18- to 34-year-olds. Separate multivariable regression models assessed associations between disability and HRQOL. Of 1478 participants, 40% reported disabilities, with cognition most prevalent (29%). Of those reporting disability, 45% ever received disability benefits and 46% were unemployed. Prevalence of disability types were 5 to 8 times higher in adults with CHD than the general population. Those with ≥1 disability had greater odds of being female, and of having non-Hispanic Black maternal race and ethnicity, severe CHD, recent cardiac care, and noncardiac congenital anomalies. On average, adults with CHD and cognition, mobility, and self-care disabilities had impaired mental HRQOL and those with any disability type had impaired physical HRQOL. Conclusions Two of 5 adults with CHD may have disabilities, which are associated with impaired HRQOL. These results may inform healthcare needs and services for this growing population.

Advance Care Directives Among a Population-Based Sample of Young Adults with Congenital Heart Defects, CH STRONG, 2016-2019.

Little is known about advance care planning among young adults with congenital heart defects (CHD). Congenital Heart Survey to Recognize Outcomes, Needs, and well-beinG (CH STRONG) participants were born with CHD between 1980 and 1997, identified using active, population-based birth defects surveillance systems in Arkansas, Arizona and Atlanta, and Georgia, and surveyed during 2016-2019. We estimated the percent having an advance care directive standardized to the site, year of birth, sex, maternal race, and CHD severity of the 9312 CH STRONG-eligible individuals. We calculated adjusted odds ratios (aOR) and 95% confidence intervals (CI) for characteristics associated with having advance care directives. Of 1541 respondents, 34.1% had severe CHD, 54.1% were female, and 69.6% were non-Hispanic white. After standardization, 7.3% had an advance care directive (range: 2.5% among non-Hispanic blacks to 17.4% among individuals with "poor" perceived health). Individuals with severe CHD (10.5%, aOR = 1.6, 95% CI: 1.1-2.3), with public insurance (13.1%, aOR = 1.7, 95% CI: 1.1-2.7), with non-cardiac congenital anomalies (11.1%, aOR = 1.9, 95% CI: 1.3-2.7), and who were hospitalized in the past year (13.3%, aOR = 1.8, 95% CI: 1.1-2.8) were more likely than their counterparts to have advance care directives. Individuals aged 19-24 years (6.6%, aOR = 0.4, 95% CI: 0.3-0.7) and 25-30 years (7.6%, aOR = 0.5, 95% CI: 0.3-0.8), compared to 31-38 years (14.3%), and non-Hispanic blacks (2.5%), compared to non-Hispanic whites (9.5%, aOR = 0.2, 95% CI: 0.1-0.6), were less likely to have advance care directives. Few young adults with CHD had advance care directives. Disparities in advance care planning may exist.

Exercise Performance in Adolescents With Fontan Physiology (from the Pediatric Heart Network Fontan Public Data Set).

In the pediatric population, exercise capacity differs between females and males and the gap widens through adolescence. However, specific age- and sex-based changes in adolescents with congenital heart disease and Fontan palliation have not been reported. The purpose of the current study is to identify age- and sex-specific changes in exercise performance at peak and ventilatory anaerobic threshold (AT) for adolescents with Fontan physiology. Retrospective review of the Pediatric Heart Network Fontan cross sectional study (Fontan 1) public use dataset. Comparisons were made for peak and AT exercise parameters for females and males at 2-year age intervals. In addition, normative values were generated by sex and age at 2-year intervals. χ2 test was used for comparison for categorical variables. Changes in exercise parameters between age groups by sex were compared by ANOVA with post-hoc analysis. Exercise testing was performed in 411 patients. AT was reached in 317 subjects (40% female), of whom, 166 (43% female) reached peak exercise. Peak oxygen consumption decreased 32% through adolescence in females and did not have the typical increase through adolescence for males. Oxygen consumption at AT also decreased with age in both sexes. In conclusion, age- and sex-based exercise performance for adolescents with Fontan physiology are predictably low, but there are additional significant decreases through adolescence for this population, especially in females. We have established normative exercise values for several parameters for this population which will better identify at risk patients and allow for earlier intervention.

Comorbidities Among Young Adults with Congenital Heart Defects: Results from the Congenital Heart Survey To Recognize Outcomes, Needs, and well-beinG - Arizona, Arkansas, and Metropolitan Atlanta, 2016-2019.

An estimated 1.4 million adults in the United States live with congenital heart defects (CHDs), yet their health outcomes are not well understood (1). Using self-reported, cross-sectional data from 1,482 respondents in the 2016-2019 Congenital Heart Survey To Recognize Outcomes, Needs, and well-beinG (CH STRONG) (2), CDC and academic partners estimated the prevalence of comorbidities among adults with CHDs aged 20-38 years born in Arizona (AZ), Arkansas (AR), and metropolitan Atlanta, Georgia (GA) compared with the general population (aged 20-38 years) from the National Health and Nutrition Examination Survey (NHANES) during 2015-2018 (3) and the AZ, AR, and GA Behavioral Risk Factor Surveillance Systems (BRFSS) during 2016-2018 (4). Adults with CHDs were more likely than those in the general population to report cardiovascular comorbidities, such as a history of congestive heart failure (4.3% versus 0.2%) and stroke (1.4% versus 0.3%), particularly those with severe CHDs (2). Adults with CHDs were more likely to report current depressive symptoms (15.1% versus 8.5%), but less likely to report previous diagnoses of depression (14.2% versus 22.6%), asthma (12.7% versus 16.9%), or rheumatologic disease (3.2% versus 8.0%). Prevalence of noncardiovascular comorbidities was similar between adults whose CHD was considered severe and those with nonsevere CHDs. Public health practitioners and clinicians can encourage young adults with CHDs to seek appropriate medical care to help them live as healthy a life as possible.

Characterization of individuals with selected muscular dystrophies from the expanded pilot of the Muscular Dystrophy Surveillance, Tracking and Research Network (MD STARnet) in the United States.

INTRODUCTION: Data on muscular dystrophies (MDs), a heterogeneous group of heritable diseases hallmarked by progressive muscle deterioration, are scarce. OBJECTIVE: We describe cross-sectional sociodemographic and clinical characteristics of individuals with congenital, distal, Emery-Dreifuss, facioscapulohumeral, limb-girdle, myotonic, or oculopharyngeal MD. METHODS: The study was conducted in four sites (Arizona, Colorado, Iowa, and 12 western New York counties) as a pilot expansion of the Muscular Dystrophy Surveillance, Tracking and Research Network, funded by the Centers for Disease Control and Prevention. MDs were detected in healthcare facilities and administrative data sources using International Classification of Disease codes. Our sample contains 1,723 individuals with a MD diagnosis and a healthcare encounter between January 1, 2007 and December 31, 2011. RESULTS AND CONCLUSIONS: Individuals were mostly non-Hispanic and white. Median ages ranged from 9.2 to 66.0 years. Most (98%) had health insurance. The proportion of individuals who were disabled or unable to work increased with age (range: 8.6-46.4%). People with limb-girdle MD aged ≥18 years were more likely to be nonambulatory (range: 24.5-44.7%). The percentages of individuals with documented clinical interventions during the surveillance period were low. The most common cause of death was respiratory causes (46.3-57.1%); an ICD-10 code for MD (G71.1 or G71.0) was reported for nearly one-half. Our findings show wide variability in sociodemographic and clinical characteristics across MDs.

Effect of comorbid neuropsychiatric disorders on children and adolescents undergoing surgery for moderate and severe congenital heart disease.

BACKGROUND: Children and adolescents with congenital heart disease (CHD) are at an increased risk of neuropsychiatric disorders (NPDs). The purpose of this study is to determine how a comorbid NPD affects hospital outcomes and costs for CHD patients undergoing cardiac surgery. METHODS: Retrospective review of the 2000-2012 Healthcare Cost and Utilization Project Kids' Inpatient Databases for admissions 10 to 21 years old with an ICD-9 code for moderate or severe CHD and a procedure code for cardiopulmonary bypass as a marker for cardiac surgery; admissions with syndromes that could be associated with NPD were excluded. Demographics, hospital outcomes, and charges were compared between admissions with and without NPD ICD-9 codes using analysis of variance, independent samples Kruskal-Wallis, and χ2 , as appropriate. RESULTS: There were 4768 admissions with CHD and cardiac surgery: 4285 (90%) with no NPD, 93 (2%) with cognitive deficits, 390 (8%) with mood/behavior deficits. Patients with NPD had a longer length of stay and higher mean charges (P < .001 for both). Patients with mood/behavior deficits were older and patients with cognitive deficits were more likely female (P < .001 for both). CONCLUSIONS: Children and adolescents with moderate or severe CHD and NPD who undergo cardiac surgery incur longer hospital stays and higher charges. Recognizing and addressing the underlying NPDs may be important to improve postoperative progression for children and adolescents with CHD hospitalized for cardiac surgery.

Anxiety reduction after pre-procedure meetings in patients with CHD.

BACKGROUND: Cardiac catheterisations for CHD produce anxiety for patients and families. Current strategies to mitigate anxiety and explain complex anatomy include pre-procedure meetings and educational tools (cardiac diagrams, echocardiograms, imaging, and angiography). More recently, three-dimensionally printed patient-specific models can be added to the armamentarium. The purpose of this study was to evaluate the efficacy of pre-procedure meetings and of different educational tools to reduce patient and parent anxiety before a catheterisation. METHODS: Prospective study of patients ≥18 and parents of patients <18 scheduled for clinically indicated catheterisations. Patients completed online surveys before and after meeting with the interventional cardiologist, who was blinded to study participation. Both the pre- and post-meeting surveys measured anxiety using the State-Trait Anxiety Inventory. In addition, the post-meeting survey evaluated the subjective value (from 1 to 4) of individual educational tools: physician discussion, cardiac diagrams, echocardiograms, prior imaging, angiograms and three-dimensionally printed cardiac models. Data were compared using paired t-tests. RESULTS: Twenty-three patients consented to participate, 16 had complete data for evaluation. Mean State-Trait Anxiety Inventory scores were abnormally elevated at baseline and decreased into the normal range after the pre-procedure meeting (39.8 versus 31, p = 0.008). Physician discussion, angiograms, and three-dimensional models were reported to be most effective at increasing understanding and reducing anxiety. CONCLUSION: In this pilot study, we have found that pre-catheterisation meetings produce a measurable decrease in patient and family anxiety before a procedure. Discussions of the procedure, angiograms, and three-dimensionally printed cardiac models were the most effective educational tools.