EHR-based Case Identification of Pediatric Long COVID: A Report from the RECOVER EHR Cohort.

Objective: Long COVID, marked by persistent, recurring, or new symptoms post-COVID-19 infection, impacts children's well-being yet lacks a unified clinical definition. This study evaluates the performance of an empirically derived Long COVID case identification algorithm, or computable phenotype, with manual chart review in a pediatric sample. This approach aims to facilitate large-scale research efforts to understand this condition better. Methods: The algorithm, composed of diagnostic codes empirically associated with Long COVID, was applied to a cohort of pediatric patients with SARS-CoV-2 infection in the RECOVER PCORnet EHR database. The algorithm classified 31,781 patients with conclusive, probable, or possible Long COVID and 307,686 patients without evidence of Long COVID. A chart review was performed on a subset of patients (n=651) to determine the overlap between the two methods. Instances of discordance were reviewed to understand the reasons for differences. Results: The sample comprised 651 pediatric patients (339 females, M age = 10.10 years) across 16 hospital systems. Results showed moderate overlap between phenotype and chart review Long COVID identification (accuracy = 0.62, PPV = 0.49, NPV = 0.75); however, there were also numerous cases of disagreement. No notable differences were found when the analyses were stratified by age at infection or era of infection. Further examination of the discordant cases revealed that the most common cause of disagreement was the clinician reviewers' tendency to attribute Long COVID-like symptoms to prior medical conditions. The performance of the phenotype improved when prior medical conditions were considered (accuracy = 0.71, PPV = 0.65, NPV = 0.74). Conclusions: Although there was moderate overlap between the two methods, the discrepancies between the two sources are likely attributed to the lack of consensus on a Long COVID clinical definition. It is essential to consider the strengths and limitations of each method when developing Long COVID classification algorithms.

Multi-institutional Assessment of Otitis Media Epidemiology Using Real-world Data.

OBJECTIVES: To determine rates and risk factors of pediatric otitis media (OM) using real-world electronic health record (PEDSnet) data from January 2009 through May 2021. STUDY DESIGN: Retrospective cohort study. SETTING: Seven pediatric academic health systems that participate in PEDSnet. METHODS: Children <6 months-old at time of first outpatient, Emergency Department, or inpatient visit were included and followed longitudinally. A time-to-event analysis was performed using a Cox proportional hazards model to estimate hazard ratios for OM incidence based on sociodemographic factors and specific health conditions. RESULTS: The PEDSnet cohort included 910,265 children, 54.3% male, mean age (months) 1.3 [standard deviation (SD) 1.6] and mean follow up (years) 4.3 (SD 3.2). By age 3 years, 39.6% of children had evidence of one OM episode. OM rates decreased following pneumococcal-13 vaccination (PCV-13) and the COVID-19 pandemic. Along with young age, non-Hispanic Black/African American or Hispanic race/ethnicity, public insurance, higher family income, and male sex had higher incidence rates. Health conditions that increased OM risk included cleft palate [adjusted hazard ratio (aHR) 4.0 [95% confidence interval (CI) 3.9-4.2], primary ciliary dyskinesia [aHR 2.5 (95% CI 1.8-3.5)], trisomy 21 [aHR 2.0 (95% CI 1.9-2.1)], atopic dermatitis [aHR 1.4 (95% CI 1.4-1.4)], and gastroesophageal reflux [aHR1.5 (95% CI 1.5-1.5)]. CONCLUSIONS: Approximately 20% of children by age 1 and 40% of children by age 3 years will have experienced an OM episode. OM rates decreased after PCV-13 and COVID-19. Children with abnormal ciliary function or craniofacial conditions, specifically cleft palate, carry the highest risk of OM.

Leveraging Serologic Testing to Identify Children at Risk For Post-Acute Sequelae of SARS-CoV-2 Infection: An Electronic Health Record-Based Cohort Study from the RECOVER Program.

Using an electronic health record-based algorithm, we identified children with Coronavirus disease 2019 (COVID-19) based exclusively on serologic testing between March 2020 and April 2022. Compared with the 131 537 polymerase chain reaction-positive children, the 2714 serology-positive children were more likely to be inpatients (24% vs 2%), to have a chronic condition (37% vs 24%), and to have a diagnosis of multisystem inflammatory syndrome in children (23% vs <1%). Identification of children who could have been asymptomatic or paucisymptomatic and not tested is critical to define the burden of post-acute sequelae of severe acute respiratory syndrome coronavirus 2 infection in children.

Skeletal Outcomes in Children and Young Adults with Glomerular Disease.

BACKGROUND: Children with glomerular disease have unique risk factors for compromised bone health. Studies addressing skeletal complications in this population are lacking. METHODS: This retrospective cohort study utilized data from PEDSnet, a national network of pediatric health systems with standardized electronic health record data for more than 6.5 million patients from 2009 to 2021. Incidence rates (per 10,000 person-years) of fracture, slipped capital femoral epiphysis (SCFE), and avascular necrosis/osteonecrosis (AVN) in 4598 children and young adults with glomerular disease were compared with those among 553,624 general pediatric patients using Poisson regression analysis. The glomerular disease cohort was identified using a published computable phenotype. Inclusion criteria for the general pediatric cohort were two or more primary care visits 1 year or more apart between 1 and 21 years of age, one visit or more every 18 months if followed >3 years, and no chronic progressive conditions defined by the Pediatric Medical Complexity Algorithm. Fracture, SCFE, and AVN were identified using SNOMED-CT diagnosis codes; fracture required an associated x-ray or splinting/casting procedure within 48 hours. RESULTS: We found a higher risk of fracture for the glomerular disease cohort compared with the general pediatric cohort in girls only (incidence rate ratio [IRR], 1.6; 95% CI, 1.3 to 1.9). Hip/femur and vertebral fracture risk were increased in the glomerular disease cohort: adjusted IRR was 2.2 (95% CI, 1.3 to 3.7) and 5 (95% CI, 3.2 to 7.6), respectively. For SCFE, the adjusted IRR was 3.4 (95% CI, 1.9 to 5.9). For AVN, the adjusted IRR was 56.2 (95% CI, 40.7 to 77.5). CONCLUSIONS: Children and young adults with glomerular disease have significantly higher burden of skeletal complications than the general pediatric population.

Hepatic abnormalities in youth with Turner syndrome.

BACKGROUND & AIMS: Liver disease in children with Turner Syndrome (TS) is poorly understood relative to associated growth, cardiac and reproductive complications. This study sought to better characterize hepatic abnormalities in a large national cohort of youth with TS. METHODS: Using electronic health record data from PEDSnet institutions, 2145 females with TS were matched to 8580 females without TS on eight demographic variables. Outcomes included liver enzymes (AST and ALT) stratified as normal, 1-2 times above the upper limit of normal (ULN), 2-3 times ULN and >3 times ULN, as well as specific liver disease diagnoses. RESULTS: Fifty-eight percent of youth with TS had elevated liver enzymes. Patients with TS had higher odds of enzymes 1-2 times ULN (OR: 1.7, 95% CI: 1.4-1.9), 2-3 times ULN (OR: 2.7, 95% CI: 1.7-3.3) and >3 times ULN (OR: 1.7, 95% CI: 1.3-2.2). They also had higher odds of any liver diagnosis (OR: 2.4, 95% CI: 1.7-3.3), fatty liver disease (OR: 1.9, 95% CI: 1.1-3.2), hepatitis (OR: 3.7, 95% CI: 1.9-7.1), cirrhosis/fibrosis (OR: 5.8, 95% CI: 1.3-25.0) and liver tumour/malignancy (OR: 4.8, 95% CI: 1.4-17.0). In a multinomial model, age, BMI and presence of cardiovascular disease or diabetes significantly increased the odds of elevated liver enzymes in girls with TS. CONCLUSIONS: Youth with TS have higher odds for elevated liver enzymes and clinically significant liver disease compared with matched controls. These results emphasize the need for clinical screening and additional research into the aetiology and treatment of liver disease in TS. LAY SUMMARY: Turner Syndrome, a chromosomal condition in which females are missing the second sex chromosome, is often associated with short stature, infertility and cardiac complications. Liver abnormalities are less well described in the literature. In this study, nearly 60% of youth with TS have elevated liver enzymes. Furthermore, patients with TS had a diagnosis of liver disease more often than patients without TS. Our results support the importance of early and consistent liver function screening and of additional research to define mechanisms that disrupt liver function in paediatric TS females.

Population-based Assessment of Cardiometabolic-related Diagnoses in Youth With Klinefelter Syndrome: A PEDSnet Study.

CONTEXT: Diabetes and cardiovascular diseases are common among men with Klinefelter syndrome (KS) and contribute to high morbidity and mortality. OBJECTIVE: To determine if cardiometabolic-related diagnoses are more prevalent among youth with KS than matched controls in a large population-based cohort. METHODS: Secondary data analysis of electronic health records from 6 pediatric institutions in the United States (PEDSnet). Patients included all youth with KS in the database (n = 1080) and 4497 youth without KS matched for sex, age (mean 13 years at last encounter), year of birth, race, ethnicity, insurance, site, and duration of care (mean 7 years). The main outcome measures were prevalence of 5 cardiometabolic-related outcomes: overweight/obesity, dyslipidemia, dysglycemia, hypertension, and liver dysfunction. RESULTS: The odds of overweight/obesity (OR 1.6; 95% CI 1.4-1.8), dyslipidemia (3.0; 2.2-3.9), and liver dysfunction (2.0; 1.6-2.5) were all higher in KS than in controls. Adjusting for covariates (obesity, testosterone treatment, and antipsychotic use) attenuated the effect of KS on these outcomes; however, boys with KS still had 45% greater odds of overweight/obesity (95% CI 1.2-1.7) and 70% greater odds of liver dysfunction (95% CI 1.3-2.2) than controls, and both dyslipidemia (1.6; 1.1-2.4) and dysglycemia (1.8; 1.1-3.2) were higher in KS but of borderline statistical significance when accounting for multiple comparisons. The odds of hypertension were not different between groups. CONCLUSION: This large, population-based cohort of youth with KS had a higher odds of most cardiometabolic-related diagnoses than matched controls.

Measuring BMI change among children and adolescents.

BACKGROUND: Weight control programs for children monitor BMI changes using BMI z-scores that adjust BMI for the sex and age of the child. It is, however, uncertain if BMIz is the best metric for assessing BMI change. OBJECTIVE: To identify which of 6 BMI metrics is optimal for assessing change. We considered a metric to be optimal if its short-term variability was consistent across the entire BMI distribution. SUBJECTS: 285 643 2- to 17-year-olds with BMI measured 3 times over a 10- to 14-month period. METHODS: We summarized each metric's variability using the within-child standard deviation. RESULTS: Most metrics' initial or mean value correlated with short-term variability (|r| ~ 0.3 to 0.5). The metric for which the within-child variability was largely independent (r = 0.13) of the metric's initial or mean value was the percentage of the 50th expressed on a log scale. However, changes in this metric between the first and last visits were highly (r ≥ 0.97) correlated with changes in %95th and %50th. CONCLUSIONS: Log %50 was the metric for which the short-term variability was largely independent of a child's BMI. Changes in log %50th, %95th, and %50th are strongly correlated.

Using a Multi-Institutional Pediatric Learning Health System to Identify Systemic Lupus Erythematosus and Lupus Nephritis: Development and Validation of Computable Phenotypes.

BACKGROUND AND OBJECTIVES: Performing adequately powered clinical trials in pediatric diseases, such as SLE, is challenging. Improved recruitment strategies are needed for identifying patients. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Electronic health record algorithms were developed and tested to identify children with SLE both with and without lupus nephritis. We used single-center electronic health record data to develop computable phenotypes composed of diagnosis, medication, procedure, and utilization codes. These were evaluated iteratively against a manually assembled database of patients with SLE. The highest-performing phenotypes were then evaluated across institutions in PEDSnet, a national health care systems network of >6.7 million children. Reviewers blinded to case status used standardized forms to review random samples of cases (n=350) and noncases (n=350). RESULTS: Final algorithms consisted of both utilization and diagnostic criteria. For both, utilization criteria included two or more in-person visits with nephrology or rheumatology and ≥60 days follow-up. SLE diagnostic criteria included absence of neonatal lupus, one or more hydroxychloroquine exposures, and either three or more qualifying diagnosis codes separated by ≥30 days or one or more diagnosis codes and one or more kidney biopsy procedure codes. Sensitivity was 100% (95% confidence interval [95% CI], 99 to 100), specificity was 92% (95% CI, 88 to 94), positive predictive value was 91% (95% CI, 87 to 94), and negative predictive value was 100% (95% CI, 99 to 100). Lupus nephritis diagnostic criteria included either three or more qualifying lupus nephritis diagnosis codes (or SLE codes on the same day as glomerular/kidney codes) separated by ≥30 days or one or more SLE diagnosis codes and one or more kidney biopsy procedure codes. Sensitivity was 90% (95% CI, 85 to 94), specificity was 93% (95% CI, 89 to 97), positive predictive value was 94% (95% CI, 89 to 97), and negative predictive value was 90% (95% CI, 84 to 94). Algorithms identified 1508 children with SLE at PEDSnet institutions (537 with lupus nephritis), 809 of whom were seen in the past 12 months. CONCLUSIONS: Electronic health record-based algorithms for SLE and lupus nephritis demonstrated excellent classification accuracy across PEDSnet institutions.

A Longitudinal Comparison of Alternatives to Body Mass Index Z-Scores for Children with Very High Body Mass Indexes.

OBJECTIVE: The current Centers for Disease Control and Prevention (CDC) body mass index (BMI) z-scores are inaccurate for BMIs of ≥97th percentile. We, therefore, considered 5 alternatives that can be used across the entire BMI distribution: modified BMI-for-age z-score (BMIz), BMI expressed as a percentage of the 95th percentile (%CDC95th percentile), extended BMIz, BMI expressed as a percentage of the median (%median), and %median adjusted for the dispersion of BMIs. STUDY DESIGN: We illustrate the behavior of the metrics among children of different ages and BMIs. We then compared the longitudinal tracking of the BMI metrics in electronic health record data from 1.17 million children in PEDSnet using the intraclass correlation coefficient to determine if 1 metric was superior. RESULTS: Our examples show that using CDC BMIz for high BMIs can result in nonsensical results. All alternative metrics showed higher tracking than CDC BMIz among children with obesity. Of the alternatives, modified BMIz performed poorly among children with severe obesity, and %median performed poorly among children who did not have obesity at their first visit. The highest intraclass correlation coefficients were generally seen for extended BMIz, adjusted %median, and %CDC95th percentile. CONCLUSIONS: Based on the examples of differences in the BMI metrics, the longitudinal tracking results and current familiarity BMI z-scores and percentiles. Both extended BMIz and extended BMI percentiles may be suitable replacements for the current z-scores and percentiles. These metrics are identical to those in the CDC growth charts for BMIs of <95th percentile and are superior for very high BMIs. Researchers' familiarity with the current CDC z-scores and clinicians with the CDC percentiles may ease the transition to the extended BMI scale.

Development and evaluation of an EHR-based computable phenotype for identification of pediatric Crohn's disease patients in a National Pediatric Learning Health System.

OBJECTIVES: To develop and evaluate the classification accuracy of a computable phenotype for pediatric Crohn's disease using electronic health record data from PEDSnet, a large, multi-institutional research network and Learning Health System. STUDY DESIGN: Using clinician and informatician input, algorithms were developed using combinations of diagnostic and medication data drawn from the PEDSnet clinical dataset which is comprised of 5.6 million children from eight U.S. academic children's health systems. Six test algorithms (four cases, two non-cases) that combined use of specific medications for Crohn's disease plus the presence of Crohn's diagnosis were initially tested against the entire PEDSnet dataset. From these, three were selected for performance assessment using manual chart review (primary case algorithm, n = 360, primary non-case algorithm, n = 360, and alternative case algorithm, n = 80). Non-cases were patients having gastrointestinal diagnoses other than inflammatory bowel disease. Sensitivity, specificity, and positive predictive value (PPV) were assessed for the primary case and primary non-case algorithms. RESULTS: Of the six algorithms tested, the least restrictive algorithm requiring just ≥1 Crohn's diagnosis code yielded 11 950 cases across PEDSnet (prevalence 21/10 000). The most restrictive algorithm requiring ≥3 Crohn's disease diagnoses plus at least one medication yielded 7868 patients (prevalence 14/10 000). The most restrictive algorithm had the highest PPV (95%) and high sensitivity (91%) and specificity (94%). False positives were due primarily to a diagnosis reversal (from Crohn's disease to ulcerative colitis) or having a diagnosis of "indeterminate colitis." False negatives were rare. CONCLUSIONS: Using diagnosis codes and medications available from PEDSnet, we developed a computable phenotype for pediatric Crohn's disease that had high specificity, sensitivity and predictive value. This process will be of use for developing computable phenotypes for other pediatric diseases, to facilitate cohort identification for retrospective and prospective studies, and to optimize clinical care through the PEDSnet Learning Health System.

Prevalence of prescription medication use in preschool-age children seen in pediatric otolaryngology.

OBJECTIVE: To examine the prevalence of daily medication use and prescribing patterns in preschool aged children presenting to otolaryngology clinics. STUDY DESIGN: Retrospective summary of prescription-related data from PEDSnet database of two tertiary care children's hospitals within single health system. METHODS: All new patients between birth and 5 years of age seen in otolaryngology clinics from October 1, 2016 through September 30, 2017 were included. Existing diagnoses, active prescriptions at time of visit, prescription dates, and demographics were abstracted. Summary analysis was performed on medication prevalence, quantity and duration of use, comparing all variables between age, gender, and geographical regions. RESULTS: Of 7532 patient encounters, 20% presented with active daily medication use. Eustachian tube dysfunction and otitis media were the most common diagnoses regardless of daily medication usage. Corticosteroids, specifically hydrocortisone (Delaware) and Flovent (Florida), were the most common medication prescribed. The number of medications strongly correlated with the number of encounter diagnoses. Overall, patients in Delaware were 4.5 times more likely to have at least one prescription prior to encounter (p < 0.05, 95% CI 3.2-4.8). This pattern was preserved across age and gender. Patients with medication in Delaware and Florida had a median of 2 (IQR 3.0-1.0) and 1 prescriptions (IQR 2.0-1.0), respectively (p < 0.001). There were no differences based on insurance type and no correlations between medication count and age or gender. CONCLUSION: Children in Delaware presented to otolaryngology clinics with significantly more prescribed medications than in Florida. Regional differences were consistent across age and gender. Most children were on these medications for a significant duration.

Learning health systems.

Healthcare organizations have invested significant resources into integrating comprehensive electronic health record (EHR) systems into clinical care. EHRs digitize healthcare in ways that allow for repurposing of clinical information to support quality improvement, research, population health, and health system analytics. This has facilitated the development of Learning Health Systems. Learning health systems (LHS) merge healthcare delivery with research, data science, and quality improvement processes. The LHS cycle begins and ends with the clinician-patient interaction, and aspires to provide continuous improvements in quality, outcomes, and health care efficiency. Although, the health sector has been slow to embrace the LHS concept, innovative approaches for improving healthcare, such as a LHS, have shown that better outcomes can be achieved by engaging patients and physicians in communities committed to a common purpose. Here, we explore the mission of a pediatric LHS, such as PEDSnet, which is driven by the distinctive goals of a child's well-being. Its vision is to create a national LHS architecture in which all pediatric institutions can participate. While challenges still exist in the development and adoption of LHS, these challenges are being met with innovative strategies and strong collaborative relationships to reduce system uncertainty while improving patient outcomes.