JAMA Pediatrics

BackgroundGastrointestinal (GI) symptoms are prevalent, persistent, and frequently disabling among autistic individuals. Existing research has focused predominantly on children, with comparatively little attention to GI experiences in adulthood. Qualitative studies in pediatric populations document substantial unmet GI-related healthcare needs, including negative healthcare encounters and limited access to autism-informed services. MethodsUsing a community-based participatory research (CBPR) framework, we conducted qualitative interviews with 26 participants (21 autistic adults, 5 parents reporting on behalf of an adult autistic child), of varying race, sexual orientation, genders, socioeconomic and educational statuses, and ages. Interviews were conducted on Zoom, ranging from 22-110 minutes long, exploring the physical, emotional, and functional impacts of GI symptoms; how these experiences relate to autism; barriers to treatment; and participants needs and priorities for improving GI health care (priorities reported elsewhere). We conducted a reflexive thematic analysis following Braun and Clarke, using an interpretivist-constructivist epistemological stance. Coding and theme development were inductive and data-driven. Themes were refined collaboratively through repeated engagement with the data, analytic memoing, and discussion of areas of interpretive uncertainty until shared meaning and coherent thematic structure were achieved. Once the codebook and thematic structure were finalized, all transcripts were systematically coded for analysis. ResultsParticipants described gastrointestinal symptoms as chronic, unpredictable, and highly consequential, shaping physical functioning, emotional wellbeing, daily routines, autonomy, and social participation. Symptoms were understood as arising from interacting biological, sensory, emotional, and contextual factors, with triggers often difficult to identify or anticipate. Experiences with healthcare were frequently characterized by dismissal, communication barriers, system complexity, and prior trauma, contributing to delayed or avoided care and heightened distress. In response, autistic adults and caregivers relied on individualized, trial-and-error management strategies - including avoidance of triggers, routine and environmental planning, dietary and pharmacologic approaches, and sensory or emotional regulation - alongside social support and peer communities to cope with persistent uncertainty and limited clinical guidance. ConclusionGI symptoms in autistic adults frequently have dramatic negative impacts on everyday life, reducing both quality of life and restricting the ability to fully engage in society and desired activities. Despite the clear magnitude of impact, knowledge and support are lacking and management remains difficult, confusing, and often unsuccessful. Improving care will require multi-layered, neurodiversity-informed approaches that recognize autistic adults as central knowledge-holders and active partners in research and clinical decision-making.

Background Education outcomes predict life chances. However, poverty, ill-health and disability are barriers to achievement. We examined determinants of academic attainment of children with and without major congenital anomalies in state-funded mainstream schools at ages 11 and 16 (key stages [KS] 2 and 4). Methods and Findings Routinely collected electronic records for children born in Wales 01/01/1998-31/12/2007 until 31/12/2019 were linked in the Secure Anonymised Information Linkage (SAIL) Databank. Education outcomes were explored using logistic regression, adjusting for: anomalies, maternal and child deprivation, prescribing, hospitalisation, gestation length, childs sex, and special education needs (SEN) provision. Children with anomalies were less likely to achieve academic standards: however, attainment was more closely associated with affluence. At age 11, 81.87% (7167/8754) with and 93.80% (232,450/247,814) without anomalies passed (odds ratio [OR] 0.30, 95% confidence intervals [CI] 0.28-0.32). At age 16, 46.76% (2070/4427) with and 56.10% (69,732/124,300) without anomalies achieved 5 General Certificates of Secondary Education (GCSEs) at grades C-A* including English/Welsh, Maths and Science (EWMS) (OR 0.69, 0.65-0.73). Discrepancies narrowed in adjusted analyses, particularly when SEN provision was accounted: aOR 0.72 (0.66-0.78) at KS2, and aOR 0.93, (0.87-1.00) for 5 GCSEs C-A* with EWMS. These GCSEs were achieved by 29.65% (307/1034) children with anomalies and 38.42% (10,875/28,305) of unaffected children in the most deprived quintile{dagger}: in the most affluent quintile, figures were 67.57% (547/810) and 74.98% (16,978/22,644). Children with anomalies, receiving maximum SEN support, eligible for Free School Meals (FSM) were the least successful: 5/192 (2.6%) passed 5 GCSEs C-A* with EWMS, as did 37/354 (10.4%) ineligible for FSM. The strongest associations with these GCSEs were SEN statements (aOR 0.07, 0.06-0.07), FSM eligibility (aOR 0.39, 0.37-0.41), and epilepsy (aOR 0.60, 0.45-0.80). However, data were unavailable for 15-18% of children, mainly those educated outside mainstream schools, and some co-morbidities. Generalisation of findings to other countries rests with readers. Conclusions Many children with anomalies from affluent households succeeded. The children left behind lived with poverty and ill-health from congenital anomalies and/or epilepsy. SEN provision mitigated the impact of disadvantage, but poor children with anomalies were unlikely to succeed. {dagger}taking maternal Welsh Index of Multiple Deprivation (WIMD) 2014 at birth.

BackgroundSuicide is the second leading cause of death for patients aged 10 to 26 years old. Pediatric suicidality is underreported, which poses significant challenges for effective intervention and prevention strategies. Identifying populations at risk for suicidality can provide critical benefits in terms of study cohort selection, prevalence estimation and resource allocation. Objective(1) Measure prevalence of mental health comorbidities associated with suicidality; (2) propensity match diagnosed suicidality cohorts to select high-risk undiagnosed suicidality cohorts. MethodsICD-10 diagnosis codes were analyzed for patients aged 6-18 years old presenting to the emergency department at a large academic pediatric hospital between June 1, 2016, and June 1, 2022. Suicidality case definition included subtypes for severity: ideation, self-harm, and attempt. Comorbidities were measured as conditional probabilities of suicidality given a co-occurring ICD-10 diagnosis code. Propensity scores were used to match known suicidality cases to undiagnosed patients at risk of suicidality. ResultsIn total, 2.9% of ED encounters met an ICD-10-based case definition of suicidality during the study period. Comorbidities of suicidality were statistically significant for 55 frequently co-occurring diagnosis codes. Nearly half (26/55) were not present in the DSM-5 codeset and nearly a quarter (12/55) included ICD-10 codes for harm without documented self-harm intent. The probability of suicidality diagnosis was 44% for patients with personality disorder, gender dysphoria (43%), bipolar disorder (36%), depression (33%), and schizophrenia spectrum disorders (32%). Compared to ground truth comparison, 53.4% of propensity matched comparators were true positive suicidality cases. ConclusionsPropensity score matching is informative for selection of undiagnosed suicidality cases whose comorbidity profiles closely resemble known cases of suicidality.

BackgroundEarly diagnosis and intervention for autism spectrum disorder (ASD) are associated with improved outcomes, but access remains uneven in many low- and middle-income countries (LMICs). Kazakhstan has seen increasing awareness of ASD, yet systemic challenges in diagnosis and care persist. ObjectiveTo compare the perspectives of parents and physicians regarding the diagnosis, treatment, and post-diagnostic support of children with autism in Kazakhstan. MethodsA cross-sectional, mixed-methods survey was conducted with 190 parents and 110 physicians across Kazakhstan. Structured questionnaires assessed early symptom recognition, diagnostic experiences, treatment practices, training needs, and beliefs about autism. ResultsWhile 76.6% of parents identified concerns before age three, diagnostic delays were common, and follow-up support was inconsistent. Physicians reported confidence in early identification (86.7%) but low use of standardized tools (26.7%). Notably, 30.0% believed autism could be outgrown with proper treatment, and 36.7% viewed ASD as having a poor prognosis even with early intervention. Nearly half of parents (46.8%) reported being advised to pursue pharmacologic treatment, often in the absence of behavioural therapy. Both groups identified training gaps, limited access to services, and fragmented care coordination as persistent challenges. ConclusionThis dual-perspective study highlights ongoing systemic and perceptual barriers to autism care in Kazakhstan. Addressing misconceptions among clinicians, expanding evidence-based training, and strengthening diagnostic and therapeutic infrastructure are critical for improving outcomes and aligning national practices with global standards.

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.

BackgroundSince 2020, recognition of long COVID (post-acute sequelae of COVID-19) has prompted rapid multidisciplinary research across medicine, public health, psychology, and the social sciences. The literature is extensive and heterogeneous, making it challenging to synthesise current knowledge, identify evidence gaps, and inform research priorities. MethodsWe performed a bibliometric review of long COVID publications indexed in Scopus from January 2020 to March 2025. Records were analysed using VOSviewer and Biblioshiny to assess publication trends, country and institutional contributions, authorship networks, citation impact, and thematic clusters. ResultsPublications on long COVID grew at an annual rate of 19.81%, peaking in 2024, reflecting intensified global attention. The United States, China, and the United Kingdom were the largest contributors. Thematic mapping revealed three dominant clusters: clinical research on manifestations and diagnostics; psychological research on mental health and cognitive sequelae; and social and rehabilitation research addressing disability, return to work, and service delivery. Prominent institutions and key authors played a central role in knowledge production and collaboration networks. Notable gaps included limited studies on paediatric long COVID, scarce long-term outcome data from diverse populations and settings, and few rigorous evaluations of interventions and service models. ConclusionsThe long COVID research landscape from 2020 to 2025 is dynamic and increasingly collaborative, yet exhibits geographic and topical imbalances. To advance understanding and improve patient outcomes, stakeholders should support inclusive international collaborations, prioritise funding for underexplored populations and intervention trials, and accelerate translation of findings into clinical guidelines and integrated care models. Continued bibliometric monitoring will help target research investments and policy responses.

ObjectivesTo examine the burden of mental health-related hospitalisations among adolescents by levels of previous child protection contact. Design, setting and participantsWhole-of-population study of children born in South Australia, 1991-1999 (n=175,115), using de-identified linked administrative data from the Better Evidence Better Outcomes Linked Data (BEBOLD) platform. Main outcome measuresAdolescents: proportion of adolescents aged 12-17 years with mental health hospitalisations; Hospitalisations: proportion of all adolescent mental health hospitalisations according to the level of child protection contact from 0-11 years. ResultsOverall, 15.5% (27,203/175,115 children) of adolescents had a history of child protection contact between ages 0-11 years, and 3.2% (5,646/175,115; 95% CI, 3.1 - 3.3) had a mental health-related hospitalisation between ages 12-17 years. Of the 10,633 mental health-related hospitalisations, 44.9% (95% CI, 44.0 - 45.9) were among adolescents with previous child protection contact even though they comprised only 15.5% of the study population. Of 5,646 adolescents with at least one mental health-related hospitalisation, 40.4% (95% CI, 39.1 - 41.7) had previous child protection contact. Among the population who experienced out-of-home care, 17.5% (209/1,191; 95% CI, 15.5 - 19.8) had experienced a mental health-related hospitalisation during adolescence, compared to 2.3% (3,366/147,912; 95% CI, 2.2 - 2.4) of adolescents with no prior child protection contact. ConclusionAlmost 45% of mental health hospitalisations for 12-17-year-olds occurred among children who had child protection contact, despite that group comprising only 15.5% of the study population. Potential trauma sequelae associated with child protection history is important to consider in the response to adolescents hospitalised due to mental health challenges. Significance of StudyO_ST_ABSThe knownC_ST_ABSAdolescent mental health is an important public health issue and those in child protection are at higher risk of experiencing mental health challenges. The newWe have quantified the burden of adolescent mental health hospitalisations attributable to the population with prior child protection system contact. For adolescents aged 12-17 years, those with a child protection history accounted for 44.9% of all adolescent mental health hospitalisations. The implicationsPotential trauma sequelae associated with child protection history are important to consider in the response to adolescents hospitalised due to mental health challenges.

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.

Despite the many health risks of physical inactivity, studies have demonstrated individual, family, and environmental determinants of inactivity for autistic children. However, these studies never examined these correlates at the same time. Therefore, the purpose of this study was to explore these ecological domains concurrently when examining physical inactivity correlates for autistic children. This study used data from the 2016-2020 National Survey of Childrens Health. The authors predicted physical inactivity while controlling for child, parental/household, and neighborhood correlates with autism status as the comparison group. When controlling for covariates, children with co-occurring autism and intellectual and developmental disability (IDD) (adjusted odds ratio (aOR)= 1.91, 95% confidence interval (CI): 1.36-2.68) or ASD only (aOR = 1.91, CI: 1.48-2.48) were significantly more likely to be inactive when compared to children without autism or IDD. However, autism medicine and autism severity were not predictors for obese autistic children. These findings indicate that it is important to take a holistic, ecological approach when exploring the correlates of inactivity for autistic children.

IMPORTANCEDuring the COVID-19 pandemic children and adolescents were massively infected worldwide. In 2022 reinfections became increasingly common and they may continue to be a main feature of the endemic phase of SARS-CoV-2. It is important to understand the epidemiology and clinical impact of reinfections. OBJECTIVETo assess the incidence, risk, and severity of SARS-CoV-2 reinfection in children and adolescents. DESIGN, SETTING, AND PARTICIPANTSA population-level observational study was performed using surveillance data from the Autonomous Province of Vojvodina, Serbia between March 6, 2020 and April 30, 2022 with follow-up until July 31, 2022. The population-based sample consisted of 32 524 residents of Vojvodina <18 years of age with laboratory confirmed SARS-CoV-2 infection. EXPOSURESThe surveillance database of the Institute for Public Health of Vojvodina was harnessed for epidemiological data of laboratory-confirmed SARS-CoV-2 infections. MAIN OUTCOMES AND MEASURESIncidence rates of documented SARS-CoV-2 reinfection per 1000 person-months. Estimated risk of documented reinfection [&ge;]90 days after laboratory confirmation of primary infection. Reinfection severity and associated hospitalizations and deaths. RESULTSA total of 964 children (3.0%) experienced documented reinfection. The incidence rate of SARS-CoV-2 documented reinfections was 3.2 (CI 3.0-3.4) cases per 1000 person-months and was highest in adolescents aged 12-17 years (3.4; CI 3.2-3.7). Most reinfections (905, 93.9%) were recorded in 2022. The reinfection risk was 1.3% at six months, 1.9% at nine months, 4.0% at 12 months, 6.7% at 15 months, 7.2% at 18 months and 7.9% after 21 months. Pediatric COVID-19 cases were generally mild. The proportion of severe clinical forms decreased from 14 (1.4%) in initial episodes to 3 (0.3%) in reinfections. Reinfected children were 4.7 times more likely to suffer from severe disease during initial infection compared to reinfection (McNemar OR=4.7; 95%CI 1.3-16.2, p=0.015). Pediatric reinfections rarely led to hospitalization (0.5% vs. 1.3% during primary infections) and none resulted in death. CONCLUSION AND RELEVANCEReinfections are becoming more frequent as the pandemic progresses, yet the risk remains substantially lower for children and adolescents compared to adults. Pediatric infections rarely had clinical consequences and reinfections were even milder than primary infections. Key PointsO_ST_ABSQuestionC_ST_ABSWhat is the incidence, risk and severity of SARS-CoV-2 reinfection in children and adolescents? FindingsThis observational population-level study showed that the risk of pediatric reinfection remained less than 8% two years into the pandemic with an incidence rate of 3.2 (CI 3.0-3.4) cases per 1000 person-months. Pediatric COVID-19 cases were generally mild and reinfected children were 4.7 times more likely to suffer from severe disease during the initial infection compared to reinfection. MeaningThese findings suggest that documented reinfection risk remains substantially lower in the pediatric versus the adult population, with an even more favorable profile compared to primary infections.

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.

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.

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.

BackgroundThere is a paucity of data on the factors associated with severe COVID-19 disease, especially in children. This systematic review and meta-analysis aim to identify the risk factors for acute adverse outcomes of COVID-19 within paediatric populations, using the recruitment setting as a proxy of initial disease severity. MethodsA systematic review and meta-analysis were performed representing published evidence from the start of the pandemic up to 14 February 2022. Our primary outcome was the identification of risk factors for adverse outcomes, stratified by recruitment setting (community, hospital). No geographical restrictions were imposed. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to evaluate the certainty in the body of evidence for each meta-analysis. In anticipation of significant clinical and methodological heterogeneity in the meta-analyses, we fitted logistic regression models with random effects. FindingsOur review identified 47 studies involving 94,210 paediatric cases of COVID-19. Infants up to 3 months were more likely to be hospitalised than older children. Gender and ethnicity were not associated with an increased likelihood of adverse outcomes among children within the community setting. Concerning comorbidities, having at least one pre-existing disease increased the odds of hospitalisation. Concerning BMI, underweight children and severely obese were noted to have an increased likelihood of hospital admission. The presence of metabolic disorders and children with underlying cardiovascular diseases, respiratory disorders, neuromuscular disorders and neurologic conditions were also more likely to be hospitalised. Concerning underlying comorbidities, paediatric hospitalised patients with congenital/genetic disease, those obese, with malignancy, cardiovascular diseases and respiratory disease were associated with higher odds of being admitted to ICU or ventilated. InterpretationOur findings suggest that age, male, gender, and paediatric comorbidities increased the likelihood of hospital and ICU admission. Obesity, malignancy, and respiratory and cardiovascular disorders were among the most important risk factors for hospital and ICU admission among children with COVID-19. The extent to which these factors were linked to actual severity or where the application of cautious preventive care is an area in which further research is needed.

BackgroundLinear growth faltering and stunting are associated with childhood mortality, morbidity, and impaired growth and cognitive development. ObjectivesWe sought to identify groups of children with different growth trajectories in their first two years of life and determine if there is an association between those early-life trajectories and attained linear growth and stunting at age five. MethodsWe used the MAL-ED birth cohort studys dataset in this analysis. The latent class growth modeling (LCGM) technique was used to identify unique classes of children who followed similar trajectories in terms of length for age z-score (LAZ) during the age of 0 to 24 months. Mixed-effects linear and logistic regression models were used to investigate the association of the LCGM-derived trajectories with height for age z-score (HAZ) and stunting at age 60 months, respectively, considering the study site as the random effect. ResultsWe detected five LAZ trajectories in 1471 children aged 0 to 2 years and designated them as follows: Class 1: severely attenuated linear growth (9%); class 2: moderately attenuated linear growth (25%); class 3: mildly attenuated linear growth (34%); class 4: stable linear growth (25%); class 5: improved linear growth (7%). In adjusted model, LAZ trajectories in the first 2 years of life were associated with HAZ and stunting at 5 years. Compared to the stable linear growth class, the improved linear growth class had a predicted 0.86 higher HAZ at age 5 years (95% CI: 0.67, 1.04), but the severely attenuated linear growth classes had lower HAZ at age 5 years ({beta} = -2.10; 95% CI: -2.26, -1.95). ConclusionsLinear growth trajectories during the first two years of life are crucial as they predict the attained linear growth and stunting at 5 years. Emphasis should be given to improving linear growth in early life through community interventions.

ImportanceDiagnosis coding is essential for clinical care, research validity, and hospital reimbursement. In neonatal settings, manual coding is frequently error-prone, contributing to misclassification and financial losses. Large language models (LLMs) offer a scalable approach to improve diagnostic consistency and optimize revenue. ObjectiveTo compare the diagnostic accuracy of LLMs with human coders in identifying common neonatal diagnoses and assess the potential impact on revenue from Diagnosis-Related Group (DRG) assignment. DesignThis was a retrospective cross-sectional study conducted using data from 2022 to 2023. LLMs were prompted with all physician notes from the admission. Two neonatologists independently and blindly adjudicated diagnoses from three sources: human coders, GPT-4o, and GPT-o3-mini. SettingA single academic referral centers neonatal intensive care unit (NICU). ParticipantsThe study included a consecutive sample of 100 infants admitted to the NICU who did not require respiratory support. All available physician notes from the hospital stay were included. ExposureTwo HIPAA-compliant LLMs (GPT-4o and GPT-o3-mini) were prompted to assign diagnoses from a standardized list based on physician notes. Three prompt iterations were developed and reviewed for optimization prior to final evaluation. Main Outcomes and MeasuresThe primary outcome was diagnostic accuracy compared with physician adjudication. Secondary outcomes included changes in expected DRG assignment and projected annual revenue. ResultsAmong 100 infants (median gestational age 35.6 weeks, 52% male), GPT-o3-mini achieved 79.1% diagnostic accuracy (95% CI, 74.0%-84.2%), comparable to human coders at 76.3% (95% CI, 70.9%-81.7%; P = .52). GPT-4o underperformed at 58.6% (95% CI, 52.5%-64.7%; P < .001 vs both). Accuracy of GPT-o3-mini did not differ by DRG impact. Extrapolated to one year, correct GPT-o3-mini diagnoses yielded projected revenue of $5.71 million, compared to $4.82 million from human coders, an 18% increase. Conclusions and RelevanceA HIPAA-compliant LLM demonstrated diagnostic accuracy comparable to human coders in neonatal billing while identifying higher-acuity diagnoses that improved projected reimbursement. LLMs may serve as effective adjuncts to manual coding in neonatal care, with potential clinical and financial benefit. Key PointsO_ST_ABSQuestionC_ST_ABSCan a large language model support accurate diagnosis generation for neonatal billing? FindingsIn this retrospective study of 100 neonates hospitalized in the Neonatal Intensive Care Unit, GPT-o3-mini demonstrated diagnostic accuracy comparable to human coders, as confirmed by physician review. Its implementation could yield an estimated 18% increase in revenue. MeaningLarge language models may serve as effective adjuncts in neonatal coding, offering both diagnostic precision and financial benefit.

BackgroundAutism care in Kazakhstan continues to develop amid limited training, unclear referral systems, and uneven provider readiness. While gaps in formal infrastructure have been well documented, the informal adaptations used by families and Physicians have received less attention. AimTo explore how informal learning, peer knowledge, and role modelling shape autism diagnosis and care in Kazakhstan, by examining the everyday behaviours and improvised routines that form a hidden curriculum alongside formal systems. MethodsThis study uses secondary analysis of two datasets: semi-structured interviews with parents of autistic children (n = 10), and national survey data from parents (n = 190) and physicians (n = 110). A concept-driven thematic analysis was applied to both interview and survey responses to identify recurring informal behaviours and decision-making patterns. Descriptive survey statistics were used to contextualise these qualitative findings. ResultsParents frequently reported being left without post-diagnostic guidance, prompting them to rely on social media, peer groups, and personal networks. Physicians, especially those early in their careers, described relying on observation or mimicking more experienced colleagues in the absence of formal training. These behaviours reflect a hidden curriculum, unofficial but influential practices that shape practices that lead to inconsistent post-diagnostic guidance. ConclusionIn Kazakhstan, informal knowledge-sharing and improvisation often affect care consistency or outcomes. These practices help fill urgent gaps but also introduce inconsistencies and shift burdens onto families, especially mothers. Policy and training reforms must acknowledge and address these informal structures to improve equitable care.

The effect of pretend play in 2 to 5-year-old children with ASD was investigated in the largest and the longest observational study to-date. Parents assessed the development of 7,069 children quarterly for three years on five subscales: combinatorial receptive language, expressive language, sociability, sensory awareness, and health. Pretend play was associated with superior developmental trajectories: 1.9-fold faster improvement of combinatorial receptive language (p<0.0001), 1.4-fold faster improvement of expressive language (p<0.0001), and 1.3-fold faster improvement of sensory awareness (p=0.0009). Pretend play had little effect on sociability and health. The strong association of pretend play with combinatorial receptive language remained significant even when controlling for expressive language. Similarly, the effect of pretend play on expressive language remained significant even when controlling for combinatorial receptive language. The effect of pretend play on combinatorial receptive language (but not on the expressive language) was stronger than the effects of seizures, sleep problems or high-TV exposure. The strong effect of pretend-play supports earlier studies indicating that it is an important stepping stone for language acquisition, particularly, the acquisition of combinatorial language.

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.

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.