JAMA Pediatrics

BackgroundAlthough COVID-19 morbidity is significantly lower in pediatrics than in adults, the risk of severe COVID-19 may still pose substantial healthcare resource burden. This study aimed to describe healthcare resource utilization (HCRU) and costs associated with COVID-19 in pediatrics aged 1-17 years in England. MethodsA population-based retrospective cohort study of pediatrics with COVID-19 using Clinical Practice Research Datalink (CPRD Aurum) primary care data and, where available, linked Hospital Episode Statistics Admitted Patient Care (HES APC) secondary care data. HCRU and associated costs to the National Health Service (NHS) were stratified by age, risk of severe COVID-19, and immunocompromized status, separately for those with and without hospitalization records (hospitalized cohort: COVID-19 diagnosis August 2020-March 2021; primary care cohort: COVID-19 diagnosis August 2020-January 2022). ResultsThis study included 564,644 patients in the primary care cohort and 60 in the hospitalized cohort. Primary care consultations were more common in those aged 1-4 years (face-to-face: 4.3%; telephone: 6.0%) compared to those aged 5-11 (2.0%; 2.1%) and 12-17 years (2.2%; 2.5%). In the hospitalized cohort, mean [SD] length of stay was longer (5.0 [5.8] days) among those aged 12-17 years (n=24) than those aged 1-4 (n=15; 1.8 [0.9] days) and 5-11 years (n=21; 2.8 [2.1] days). ConclusionsMost pediatrics diagnosed with COVID-19 were managed in the community. However, hospitalizations were an important driver of HCRU and costs, particularly for those aged 12-17 years. Our results may help optimize the management and resource allocation of COVID-19 in this population.

Background and ObjectivesWhereas adverse early life experiences (ACEs) correlate with cognitive, emotional and physical health at the population level, existing ACEs screens are only weakly predictive of outcomes for an individual child. This raises the possibility that important elements of the early-life experiences that drive vulnerability and resilience are not being captured. We previously demonstrated that unpredictable parental and household signals constitute an ACE with cross-cultural relevance. We created the 5-item Questionnaire of Unpredictability in Childhood (QUIC-5) that can be readily administered in pediatric clinics. Here, we tested if combined screening with the QUIC-5 and an ACEs measure in this real-world setting significantly improved prediction of child health outcomes. MethodsLeveraging existing screening with the Pediatric ACEs and Related Life Events Screener (PEARLS) at annual well-child visits, we implemented QUIC-5 screening in 19 pediatric clinics spanning the diverse sociodemographic constituency of Orange County, CA. Children (12yr+) and caregivers (for children 0-17years) completed both screens. Health diagnoses were abstracted from electronic health records (N=29,305 children). ResultsFor both screeners, increasing exposures were associated with a higher probability of a mental (ADHD, anxiety, depression, externalizing problems, sleep disorder) or physical (obesity abdominal pain, asthma, headache) health diagnosis. Across most diagnoses, PEARLS and QUIC provided unique predictive contributions. Importantly, for three outcomes (depression, obesity, sleep disorders) QUIC-5 identified vulnerable individuals that were missed by PEARLS alone. ConclusionsScreening for unpredictability as an additional ACE in primary care is feasible, acceptable and provides unique, actionable information about child psychopathology and physical health. Whats Known on This SubjectWhereas ACEs correlate with neurodevelopmental and physical health of children at the population level, ACEs scales (e.g., PEARLS) are only weakly predictive at the level of the individual child. Are important elements of early-life adversity missed by these scales? What This Study AddsBecause unpredictable signals constitute a unique ACE, we developed the Questionnaire of Unpredictability in Childhood (QUIC-5). Administering QUIC-5 and PEARLS to 30,000 families identified youth at risk for depression, obesity and other health problems, who would be missed by PEARLS alone.

Individuals with Turner syndrome (TS) are known to be at increased risk for neurodevelopmental disorders (NDD) and mental health (MH) conditions, but data from large, population-based pediatric samples remain limited. We examined the prevalence of NDD and MH diagnoses among youth with TS (N = 2,145) compared to matched female controls (N = 8,580) across six U.S. pediatric health systems. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using generalized estimating equations. Youth with TS had significantly higher odds of an NDD diagnosis (24.2% vs. 11.9%; OR 2.37, 95% CI 2.11-2.67), particularly for speech-language, motor, learning, and attentional disorders. Increased odds were also observed for autism spectrum disorder (ASD) and intellectual developmental disorder (IDD), though these remained relatively uncommon. In contrast, MH diagnoses, such as anxiety and mood disorders, were not more prevalent in TS compared to controls (17.3% vs. 18.5%; OR 0.92, 95% CI 0.81-1.05). These findings support the need for proactive neurodevelopmental screening in TS and raise important questions about the recognition and documentation of MH conditions in this population. Additional research is warranted to understand whether MH symptoms are underdiagnosed in youth with TS or emerge later in development.

ImportancePediatric SARS-CoV-2 infections and hospitalizations are rising in the US and other countries after the emergence of Omicron variant. However data on disease severity from Omicron compared with Delta in children under 5 in the US is lacking. ObjectivesTo compare severity of clinic outcomes in children under 5 who contracted COVID infection for the first time before and after the emergence of Omicron in the US. Design, Setting, and ParticipantsThis is a retrospective cohort study of electronic health record (EHR) data of 79,592 children under 5 who contracted SARS-CoV-2 infection for the first time, including 7,201 infected between 12/26/2021-1/6/2022 when the Omicron predominated (Omicron cohort), 63,203 infected between 9/1/2021-11/15/2021 when the Delta predominated (Delta cohort), and another 9,188 infected between 11/16/2021-11/30/2021 when the Delta predominated but immediately before the Omicron variant was detected in the US (Delta-2 cohort). ExposuresFirst time infection of SARS-CoV-2. Main Outcomes and MeasuresAfter propensity-score matching, severity of COVID infections including emergency department (ED) visits, hospitalizations, intensive care unit (ICU) admissions, and mechanical ventilation use in the 3-day time-window following SARS-CoV-2 infection were compared between Omicron and Delta cohorts, and between Delta-2 and Delta cohorts. Risk ratios, and 95% confidence intervals (CI) were calculated. ResultsAmong 7,201 infected children in the Omicron cohort (average age, 1.49 {+/-} 1.42 years), 47.4% were female, 2.4% Asian, 26.1% Black, 13.7% Hispanic, and 44.0% White. Before propensity score matching, the Omicron cohort were younger than the Delta cohort (average age 1.49 vs 1.73 years), comprised of more Black children, and had fewer comorbidities. After propensity-score matching for demographics, socio-economic determinants of health, comorbidities and medications, risks for severe clinical outcomes in the Omicron cohort were significantly lower than those in the Delta cohort: ED visits: 18.83% vs. 26.67% (risk ratio or RR: 0.71 [0.66-0.75]); hospitalizations: 1.04% vs. 3.14% (RR: 0.33 [0.26-0.43]); ICU admissions: 0.14% vs. 0.43% (RR: 0.32 [0.16-0.66]); mechanical ventilation: 0.33% vs. 1.15% (RR: 0.29 [0.18-0.46]). Control studies comparing Delta-2 to Delta cohorts show no difference. Conclusions and RelevanceFor children under age 5, first time SARS-CoV-2 infections occurring when the Omicron predominated (prevalence >92%) was associated with significantly less severe outcomes than first-time infections in similar children when the Delta variant predominated.

We evaluated the efficacy of Frankini, a 12-month early parent-child intervention that combines online parent counseling with hybrid speech restructuring to reduce stuttering severity and promote fluency-supportive interaction. This retrospective, nonrandomized pilot trial included cases enrolled between September 2019 and November 2023. For analysis, only participants who completed Module 1 (indirect parental training) and Module 2 (the first hybrid speech restructuring module) were included. A total of 51 cases met all inclusion criteria, and 30 of these completed all three modules. To simulate a wait-list-controlled design, eligible participants were divided into early and delayed groups using median split. The early group completed Module 2 nine months after baseline, the delayed group twelve months after baseline. Groups were matched on key characteristics and differed only in the timing of the first direct intervention. Blinded raters assessed stuttering severity. Primary outcomes included the Stuttering Severity Index, parental severity rating, and a 10-item parent report. At 9 months, the early group showed reduced stuttering severity, while the delayed group showed no change (mean difference = -8.33 95%CI [-12.98, -3.68], p < 0.001, with d = -1.14). By 12 months, both groups improved, and group difference were no longer significant (mean difference = -3.37 95%CI [-8.23, 1.50], p = 0.168 and d = -0.48). Parental ratings mirrored these outcomes showing consistent improvement after each module. Speech restructuring significantly improved speech fluency and parent counseling enhanced parents confidence, supporting the value of initiating treatment before age 6; however, follow-up is needed to assess long-term effects. Trial RegistrationDRKS00034731.

Background and ObjectivesAs survival after pediatric critical illness improves, attention has shifted to post-intensive care syndrome (PICS-p) and specifically the long-term mental health of PICU survivors, who face elevated risks including posttraumatic stress, anxiety, and depression. However, little is known about actual patterns of post-discharge mental health care. The objective of this study is to examine the rates of mental health follow-up and psychopharmacology use among publicly insured children following PICU hospitalization, compared with those hospitalized on acute care wards, using a multi-state administrative dataset. MethodsWe performed a retrospective cohort study using 2016-2021 Medicaid claims across 10-12 states. The cohort comprised children aged 3-18 years discharged home after an index hospitalization and excluded perinatal admissions and hospitalizations primarily for mental health or traumatic brain injury. The primary exposure was pediatric intensive care unit (PICU) admission. The primary outcome was new mental health visits within one-year post-discharge. Secondary outcomes included visit provider type, visit diagnoses category, and new psychiatric prescriptions. We report descriptive statistics and measure associations with covariates using logistic regression. ResultsAmong 144,763 Medicaid-insured pediatric hospitalizations (20.7% with PICU stays), only 8.8% initiated new mental health care. When compared to hospitalizations without PICU exposure, those with PICU exposure were more likely to complete new mental health visits (n=1,697 [6.1%] of PICU hospitalizations vs 5,252 [4.9%] of non-PICU hospitalizations). However, PICU exposure was not independently associated with a new mental health visit after adjustment (OR 1.06, 95% CI 1 - 1.13; p=0.067). Older age, complex chronic conditions, and longer length of stay were associated with new mental health visits. Hospitalizations with a PICU stay were significantly associated with increased rate of visits to psychologists or supportive therapists compared to those without a PICU stay (p<0.001). ConclusionsMental health follow-up after pediatric hospitalization is rare. Future studies should investigate barriers to care and identify effective methods for systematic screening and proactive referral.

Symptom-based SARS-CoV-2 screening and testing decisions in children have important implications on daycare and school exclusion policies. Single symptoms account for a substantial volume of testing and disruption to in-person learning and childcare, yet their predictive value is unclear, given the clinical overlap with other circulating respiratory viruses and non-infectious etiologies. We aimed to determine the relative frequency and predictive value of single symptoms for paediatric SARS-CoV-2 infections from an Ottawa COVID-19 assessment centre from October 2020 through April 2021. Overall, 46.3% (n=10,688) of pediatric encounters were for single symptoms, and 2.7% of these tested positive. The most common presenting single symptoms were rhinorrhea (31.8%), cough (17.4%) and fever (14.0%). Among children with high-risk exposures children in each age group, the following single symptoms had a higher proportion of positive SARS-CoV-2 cases compared to no symptoms; fever and fatigue (0-4 years); fever, cough, headache, and rhinorrhea (5-12 years); fever, loss of taste or smell, headache, rhinorrhea, sore throat, and cough (13-17 years). There was no evidence that the single symptom of either rhinorrhea or cough predicted SARS-CoV-2 infections among 0-4 year olds, despite accounting for a large volume (61.1%) of single symptom presentations in the absence of high-risk exposures. Symptom-based screening needs to be responsive to changes in evidence and local factors, including the expected resurgence of other respiratory viruses following relaxation of social distancing/masking, to reduce infection-related risks in schools and daycare settings.

ImportanceEarly identification and treatment of Attention-Deficit/Hyperactivity Disorder (ADHD) symptoms in preschool-age children is important for mitigating social-emotional and academic problems. Clinical practice guidelines recommend first-line behavior intervention before considering medication treatment for children 4-5-years-old. ObjectiveTo assess variation in rates of ADHD identification and rates and timing of medication treatment in children 3-5-years-old in primary care settings across eight US pediatric health systems and to identify patient factors associated with the time from diagnosis to prescription. DesignRetrospective cohort study of electronic health records. SettingPrimary care clinics affiliated with eight academic institutions participating in the PEDSnet Clinical Research Network. ParticipantsChildren 3-5-years-old seen in primary care between 2016-2023. ExposureADHD diagnosis at age 4-5 years. Main Outcomes and MeasuresOutcomes: (1) rate of ADHD diagnosis; (2) rate of stimulant and non-stimulant prescription after diagnosis before age 7, (3) time from first ADHD-related diagnosis (including symptom-level diagnoses) to medication prescription. Independent variables: institution, year of diagnosis, patient age, sex, race/ethnicity, medical insurance, and presence of comorbidities. ResultsOf 712,478 children seen in primary care at ages 3-5 years, 9,708 (1.4%) received an ADHD diagnosis at age 4-5 years (range 0.5-3.1% across institutions). Of those with ADHD, 76.4% (n=7414) were male, 39.0% (n=3782) were White. Of 9,708 preschool-age children with ADHD, 68.2% (6624) were prescribed ADHD medications before age 7, 42.2% (n=4092) were prescribed medications within 30 days of the first documentation of an ADHD-related diagnosis (range 26.0-49.0% across institution). Asian (aHR 0.50, CI 0.38-0.65), Hispanic (aHR 0.75, CI 0.70-0.81), and Black (aHR 0.90, CI 0.85-0.96) children with ADHD were less likely to be prescribed medication early compared to White children. Older (aHR 1.64, CI 1.57-1.72), male (aHR 1.74, CI 1.11-1.24) and publicly insured (aHR 1.10, CI 1.04-1.17) patients were more likely to be prescribed medication early compared to younger, female and privately insured patients, respectively. Conclusion and RelevanceMany preschool-age children with ADHD seen in primary care in 8 large pediatric health systems were prescribed medications at or shortly after the first documented diagnosis. Future analysis of clinical documentation is needed to understand the reasoning behind early prescription patterns.

BackgroundChronic medical conditions are a risk factor for moderate or severe COVID-19 in children, but little is known about post-acute sequelae of SARS-CoV-2 infection (PASC) in children with chronic medical conditions (CMCs). To understand whether SARS-CoV-2 infection led to potential exacerbation of underlying chronic disease in children, we explored whether children with CMCs had increased healthcare utilization in the post-acute (28 days after infection) period compared to children with CMCs without SARS-CoV-2 infection. MethodsWe conducted a retrospective, matched-cohort study using electronic health record data collected from 8 pediatric health care systems participating in the PEDSnet network. We included children <21 years of age with a wide array of chronic conditions, defined by the presence of diagnostic codes, who were diagnosed with COVID-19 between March 1, 2020 and February 28, 2022. Cohort entry was defined by presence of a positive SARS-CoV-2 PCR test (polymerase chain reaction or antigen) or diagnostic codes for COVID-19, PASC or MIS-C. A comparison cohort of patients testing negative or without these conditions was matched using a stratified propensity score model and exact matching on age group, race/ethnicity, institution, test location, and month of cohort entry. A negative binomial model was used to examine our primary outcome: composite and setting-specific (inpatient, outpatient, ED) utilization rate ratios between the positive and comparison cohorts. Secondary outcomes included time to first utilization in the post-acute period, and utilization stratified by severity at cohort entry. ResultsWe identified 748,692 patients with at least one chronic condition, 78,744 of whom met inclusion criteria for the COVID-19 cohort. 96% of patients from the positive cohort were matched. Cohorts were well-balanced for chronic condition clusters, total number of conditions, time since first diagnosis, baseline utilization, cohort entry period, age, sex, race/ethnicity and test location. We found that among children with chronic medical conditions, those with COVID-19 had higher healthcare utilization than those with no recorded COVID-19 diagnosis or positive test, with utilization rate ratio of 1.21 (95% CI: 1.18-1.24). The utilization was highest for inpatient care with utilization rate ratio of 2.03 (95% CI: 1.85-2.23) but the utilization was increased across all settings. Hazard ratios estimated in time-to-first-utilization analysis mirrored these results. Patients with severe or moderate acute COVID-19 illness had greater increases in utilization in all settings than those with mild or asymptomatic disease. ConclusionsWe found that care utilization in all settings was increased following COVID-19 in children with chronic medical conditions in the post-acute period, particularly in the inpatient setting. Increased utilization was correlated with more severe COVID-19. Additional research is needed to better understand the reasons for higher care utilization by studying condition-specific outcomes in children with chronic disease.

ObjectiveLong COVID, marked by persistent, recurring, or new symptoms post-COVID-19 infection, impacts childrens 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. MethodsThe 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. ResultsThe sample comprised 651 pediatric patients (339 females, Mage = 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). ConclusionsAlthough 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.

Unmet health-related social needs (HRSNs) are major drivers of poor health outcomes in early childhood. Children with unmet HRSNs are at greater risk for developmental delays, caregiver stress, and increased healthcare utilization, yet current screening approaches in pediatric primary care are resource-intensive and inconsistently implemented. AI-powered chatbots (conversational agents or virtual assistants) may offer a private, secure, scalable, and cost-effective alternative for identifying unmet needs and connecting families to services. This protocol describes a pilot randomized controlled trial designed to evaluate the feasibility, acceptability, and usability of DAPHNE, an AI-driven chatbot developed to facilitate the identification of unmet HRSNs and provide personalized community resource referrals. One hundred caregivers of children under two years of age will be recruited from Nationwide Childrens Hospital pediatric primary care clinics and randomized to either the standard care (control) group or DAPHNE+ Standard care (intervention) group (n=50 each arm). Caregivers will complete surveys at baseline, 1 month, 3 months, and 6 months post-intervention (depending on the measure). For the intervention group, participants will receive weekly chatbot prompts and on-demand access throughout the 6-month study period. Primary outcomes include study feasibility (recruitment, retention, and survey completion across both arms), acceptability (caregiver-reported ratings in both arms and intervention-specific ratings), and usability of the DAPHNE chatbot (System Usability Scale among intervention participants). Secondary outcomes include caregiver-reported outcome measures (caregiver stress, self-efficacy, satisfaction with resource access, quality of life), and electronic health record-derived measures (including documentation of HRSN screening and referrals, adherence to well-child visits, missed appointments, emergency department utilization, and estimated healthcare costs). In addition, ten primary care providers will also participate to assess workflow integration and report on current HRSN practices. Mixed-methods analyses will integrate survey data, chatbot engagement metrics, and qualitative interviews to refine both the intervention and the study protocol. The results of this study will inform the design of a future multi-site trial to evaluate the efficacy and implementation of DAPHNE for addressing HRSNs in pediatric primary care. Trial registration: NCT07168382.

BackgroundResearch demonstrates that SARS-CoV-2 infection (COVID-19) among adults disproportionately impacts racial and ethnic minorities and those living in lower-income communities. Similar research in children is limited due, in part, to the relatively low COVID-19 incidence in children compared to adults. This analysis, conducted as part of the RECOVER Initiative, explores this question. MethodsElectronic health record (EHR) data from PEDSnet, a multi-institutional research network of pediatric healthcare organizations, were geocoded and linked to two indices of contextual social deprivation: the Area Deprivation Index and the Child Opportunity Index. Univariate statistics were employed to test the association between each index and COVID19 positivity among children ages 0-20 tested at one of six Childrens hospitals. Multivariate logistic regression was used to explore the relationship between these social context indices and racial disparities in positivity, controlling co-variates. ResultsBoth ADI and COI were significantly associated with COVID-19 positivity in univariate and adjusted models, particularly in the pre-delta and delta variant waves. ADI showed a stronger association. Higher rates of positivity were found for non-Hispanic Black, Hispanic, and multi-racial children compared to non-Hispanic White children. These racial disparities remained significant after control for either index and for other variables. ConclusionADI and COI are significantly associated with COVID-19 test positivity in a population of children and adolescents tested in childrens hospital settings. These social contextual variables do not fully explain racial disparities, arguing that racial disparities are not solely a reflection of socioeconomic status. Future disparities research should consider both race and social context.

ImportanceDeclining mortality in the field of pediatric critical care medicine has shifted practicing clinicians attention to preserving patients neurodevelopmental potential as a main objective. Earlier identification of critically ill children at risk for incurring neurologic morbidity would facilitate heightened surveillance that could lead to timelier clinical detection, earlier interventions, and preserved neurodevelopmental trajectory. ObjectiveDevelop machine-learning models for identifying acquired neurologic morbidity while hospitalized with critical illness and assess correlation with contemporary serum-based, brain injury-derived biomarkers. DesignRetrospective cohort study. SettingTwo large, quaternary childrens hospitals. ExposuresCritical illness. Main Outcomes and MeasuresThe outcome was neurologic morbidity, defined according to a computable, composite definition at the development site or an order for neurocritical care consultation at the validation site. Models were developed using varying time windows for temporal feature engineering and varying censored time horizons prior to identified neurologic morbidity. Optimal models were selected based on F1 scores, cohort sizes, calibration, and data availability for eventual deployment. A generalizable created at the development site was assessed at an external validation site and optimized with spline recalibration. Correlation was assessed between development site model predictions and measurements of brain biomarkers from a convenience cohort. ResultsAfter exclusions there were 14,222-25,171 encounters from 2010-2022 in the development site cohorts and 6,280-6,373 from 2018-2021 in the validation site cohort. At the development site, an extreme gradient boosted model (XGBoost) with a 12-hour time horizon and 48-hour feature engineering window had an F1-score of 0.54, area under the receiver operating characteristics curve (AUROC) of 0.82, and a number needed to alert (NNA) of 2. A generalizable XGBoost model with a 24-hour time horizon and 48-hour feature engineering window demonstrated an F1-score of 0.37, AUROC of 0.81, AUPRC of 0.51, and NNA of 4 at the validation site. After recalibration at the validation site, the Brier score was 0.04. Serum levels of the brain injury biomarker glial fibrillary acidic protein measurements significantly correlated with model output (rs=0.34; P=0.007). Conclusions and RelevanceWe demonstrate a well-performing ensemble of models for predicting neurologic morbidity in children with biomolecular corroboration. Prospective assessment and refinement of biomarker-coupled risk models in pediatric critical illness is warranted. Key PointsQuestion Can interoperable models for predicting neurological deterioration in critically ill children be developed, correlated with serum-based brain-derived biomarkers, and validated at an external site? Findings A development site model demonstrated an area under the receiver operating characteristics curve (AUROC) of 0.82 and a number needed to alert (NNA) of 2. Predictions correlated with levels of glial fibrillary acidic protein in a subset of children. A generalizable model demonstrated an AUROC of 0.81 and NNA of 4 at the validation site. Meaning Well performing prediction models coupled with brain biomarkers may help to identify critically ill children at risk for acquired neurological morbidity.

IntroductionRoutine developmental surveillance is fundamental for timely identification of developmental delays. We explored sex-related differences in milestone attainment rate and evaluated the clinical need for sex-specific developmental scales. MethodsThis is a retrospective cross-sectional study, utilizing data from a national child surveillance program. The study included children from birth to six years of age, assessed between 2014-2021 (n=643,958 and n=309,181 for the main and validation cohorts, respectively). We measured the differences between sexes in normative attainment age of 59 milestones from four developmental domains and calculated the projected error rates when conducting unified vs. sex-specific surveillance. ResultsGirls preceded boys in most milestones of all domains. Conducting developmental surveillance using unified rather than sex-specific scales resulted in potential missing of girls at risk of developmental delay (19.3% of failed assessments), and false alerts for boys (5.9%). ConclusionThese findings suggest that using sex-specific scales may improve the accuracy of early childhood developmental surveillance.

Maternal stress and viral illness during pregnancy are associated with neurodevelopmental conditions in offspring. Children born during the COVID-19 pandemic, including those exposed prenatally to maternal SARS-CoV-2 infections, are reaching the developmental age for the assessment of risk for neurodevelopmental conditions. We examined associations between birth during the COVID-19 pandemic, prenatal exposure to maternal SARS-CoV-2 infection, and rates of positive screenings on the Modified Checklist for Autism in Toddlers-Revised (M-CHAT-R). Data were drawn from the COVID-19 Mother Baby Outcomes (COMBO) Initiative. Participants completed the M-CHAT-R as part of routine clinical care (COMBO-EHR cohort) or for research purposes (COMBO-RSCH cohort). Maternal SARS-CoV-2 status during pregnancy was determined through electronic health records. The COMBO-EHR cohort includes n=1664 children (n=442 historical cohort, n=1222 pandemic cohort; n=997 SARS-CoV-2 unexposed prenatally, n=130 SARS-CoV-2 exposed prenatally) who were born at affiliated hospitals between 2018-2023 and who had a valid M-CHAT-R score in their health record. The COMBO-RSCH cohort consists of n=359 children (n=268 SARS-CoV-2 unexposed prenatally, n=91 SARS-CoV-2 exposed prenatally) born at the same hospitals who enrolled into a prospective cohort study that included administration of the M-CHAT-R at 18-months. Birth during the pandemic was not associated with greater likelihood of a positive M-CHAT-R screen in the COMBO-EHR cohort. Maternal SARS-CoV-2 was associated with lower likelihood of a positive M-CHAT-R screening in adjusted models in the COMBO-EHR cohort (OR=0.40, 95% CI=0.22 - 0.68, p=0.001), while analyses in the COMBO-RSCH cohort yielded similar but non-significant results (OR=0.67, 95% CI=0.31-1.37, p=0.29).These results suggest that children born during the first 18 months of the COVID-19 pandemic and those exposed prenatally to a maternal SARS-CoV-2 infection are not at greater risk for screening positive on the M-CHAT-R.

The impact of post-acute sequelae of SARS-CoV-2 infection (PASC) in children is underrecognized. We developed an EHR-based algorithm across eight pediatric institutions to identify children with COVID-19 based on serology testing from 3/2020 through 4/2022 who had not been identified by PCR. Overall, serology tests were used 100-fold less than PCR. Seroprevalence of IgG anti-nucleocapsid antibodies remained stable, while rates of positive IgG anti-spike antibodies increased in teenagers after COVID-19 vaccine approval. Through data harmonization and after excluding 1,410 serology test results that may have been influenced by vaccines, we identified 2,714 children that were COVID-19 positive exclusively by serology. These patients were frequently tested as inpatients (24% vs. 2%), had chronic conditions more frequently (37% vs 24%), and a MIS-C diagnosis (23% vs. <1%) compared with PCR-positive children. Identification of children that could have been paucisymptomatic, not tested, or missed is critical to define the burden of PASC in children.

INTRODUCTIONSocial determinants of health (SDOH) may impact caregivers ability to implement evidence-based health practices at home during early childhood, especially in families with children with intellectual and developmental disabilities (IDD). Therefore, we examined the influence of SDOH and childrens diagnosis (typically developing [TD], Down syndrome [DS], autism) on caregivers self-report of meeting evidence-based health practices. METHODSCaregivers (n=172) of children ages 2-6 years (TD: n=93, DS: n=40, autism: n=39) completed an online survey on SDOH and health practices related to child nutrition (CN), physical activity (PA), outdoor play (OP), and screen time (ST). A total SDOH score was computed by assigning 1 point for each favorable SDOH metric (range 0-13). Linear regressions were used to examine associations between SDOH and CN, PA, OP, ST health practices and the moderating effect of IDD diagnosis. RESULTSMost caregivers were non-Hispanic White (84.3%), female (76.7%), 18-35 years old (55.2%), and married (89.5%). The DS group had the lowest SDOH score (mean = 8.4{+/-}1.0) compared to autism (mean = 10.1{+/-}1.0) and TD (mean = 11.0{+/-}0.9). No family scored 100% in evidence-based practices for any health practice. SDOH score was significantly associated with evidence-based practices met score for CN (b = 1.94, 95% CI = 0.84, 3.04; p = 0.001) and PA (b = 4.86, 95% CI = 2.92, 6.79; p <0.0001). Moderation analysis showed no association in the DS and autism groups between SDOH score and CN percent total score, or between SDOH score and CN, PA, and OP for percent evidence-based practices met. SDOH score was also not associated with OP percent total score for the DS group. CONCLUSIONSThis study highlights the differential influence of SDOH on caregivers implementing health practices in families with children of different IDD diagnoses. Future research is needed to understand impacts of SDOH on non-typically developing children.

ObjectivePediatric patients have different diseases and outcomes than adults; however, existing phecodes do not capture the distinctive pediatric spectrum of disease. We aim to develop specialized pediatric phecodes (Peds-Phecodes) to enable efficient, large-scale phenotypic analyses of pediatric patients. Materials and MethodsWe adopted a hybrid data- and knowledge-driven approach leveraging electronic health records (EHRs) and genetic data from Vanderbilt University Medical Center to modify the most recent version of phecodes to better capture pediatric phenotypes. First, we compared the prevalence of patient diagnoses in pediatric and adult populations to identify disease phenotypes differentially affecting children and adults. We then used clinical domain knowledge to remove phecodes representing phenotypes unlikely to affect pediatric patients and create new phecodes for phenotypes relevant to the pediatric population. We further compared phenome-wide association study (PheWAS) outcomes replicating known pediatric genotype-phenotype associations between Peds-Phecodes and phecodes. ResultsThe Peds-Phecodes aggregate 15,533 ICD-9-CM codes and 82,949 ICD-10-CM codes into 2,051 distinct phecodes. Peds-Phecodes replicated more known pediatric genotype-phenotype associations than phecodes (248 versus 192 out of 687 SNPs, p<0.001). DiscussionWe introduce Peds-Phecodes, a high-throughput EHR phenotyping tool tailored for use in pediatric populations. We successfully validated the Peds-Phecodes using genetic replication studies. Our findings also reveal the potential use of Peds-Phecodes in detecting novel genotype-phenotype associations for pediatric conditions. We expect that Peds-Phecodes will facilitate large-scale phenomic and genomic analyses in pediatric populations. ConclusionPeds-Phecodes capture higher-quality pediatric phenotypes and deliver superior PheWAS outcomes compared to phecodes.

BackgroundAdults with SARS-CoV-2 infection have shown higher risks of dyslipidaemia and abnormal body mass index (BMI). Whether similar associations exist in children and adolescents is unclear. MethodWe did a retrospective cohort study using the RECOVER paediatric Electronic Health Record (EHR) datasets from 25 US childrens hospitals, covering March 2020 to September 2023. For dyslipidaemia analyses, we included 384,289 patients aged 0-21 years with at least 6 months of follow-up and 1,080,413 COVID-19-negative controls. For BMI analyses, we included 285,559 patients aged 2-21 years and 817,315 controls. Documented infection was defined as a positive PCR, serology, or antigen test, or a clinical diagnosis of COVID-19 or post-acute sequelae of SARS-CoV-2. Outcomes were new diagnoses of dyslipidaemia, defined by laboratory thresholds for total cholesterol, triglycerides, LDL cholesterol, HDL cholesterol, and non-HDL cholesterol, and abnormal BMI (BMI-for-age [&ge;]95th percentile at ages 2-19 years or BMI [&ge;]30 kg/m{superscript 2} at ages 19-21 years). Adjusted relative risks (aRRs) were estimated using propensity score-stratified Poisson regression. Sensitivity analyses included empirical calibration with negative control outcomes and stratification by baseline obesity. InterpretationChildren and adolescents with documented COVID-19 were associated with higher risks of new-onset dyslipidaemia and abnormal BMI in the post-acute period compared with COVID-19-negative peers. Associations were consistent across lipid fractions, remained after empirical calibration, and were similar after accounting for baseline obesity. Research in context Evidence before this studyAdults with SARS-CoV-2 infection have been reported to develop dyslipidaemia and abnormal body mass index (BMI) after the acute phase, raising concerns about long-term metabolic health. In children and adolescents, evidence has been scarce. Available studies are small, cross-sectional, or based mainly on diagnosis codes, with few incorporating laboratory lipid values or age-specific BMI thresholds against contemporaneous controls. The risk of post-acute dyslipidaemia and BMI abnormalities in paediatric populations therefore remains uncertain. Added value of this studyUsing the Researching COVID to Enhance Recovery (RECOVER) electronic health record (EHR) database from 25 US hospitals, we examined more than 1.6 million children and adolescents with at least 6 months of follow-up. Outcomes were defined using laboratory lipid panels and age-specific BMI measures. With propensity score stratification across hundreds of covariates and calibration using negative control outcomes, documented COVID-19 was associated with higher adjusted risks of abnormal HDL cholesterol, LDL cholesterol, total cholesterol, triglycerides, and BMI. Associations were consistent across sensitivity analyses and stratified by baseline obesity. Implications of all the available evidenceTogether with findings from adult studies, our results indicate that metabolic sequelae after SARS-CoV-2 infection are also relevant in paediatric populations. Children and adolescents with documented COVID-19 were more likely to develop dyslipidaemia and abnormal BMI in the early post-acute phase. These findings support routine lipid and BMI monitoring in paediatric follow-up care, which could enable earlier identification of metabolic dysfunction and guide preventive strategies for long-term cardiometabolic health.

The net effect of the pandemic mitigation strategies on childhood mortality is not known. During the first year of the COVID-19 pandemic, mitigation policies and behaviors were widespread, and although vaccinations and effective treatments were not yet widely available, the risk of death from SARS-CoV-2 infection was low. In that first year, there was a 7% decrease in medical ("natural causes") mortality among children ages 0-9 during the first pandemic year (5% among infants <1 year and 15% among children ages 1-9) in the United States, resulting in an estimated 1,488 deaths due to medical causes averted among children ages 0-9, and 1,938 deaths averted over 24 months. The usual expected surge in winter medical deaths, particularly among children ages >1 year was absent. However, smaller increases in external ("non-natural causes") mortality were also observed during the study period, which decreased the overall number of pediatric deaths averted during both years and the pandemic period. In total, 1,468 fewer all-cause pediatric deaths than expected occurred in the United States during the first 24 months of the COVID-19 pandemic.