Autism In Toddlers Research Articles

Effectiveness of autism training program introduction at primary health care (PHC) level

Background: Autism spectrum disorder (ASD) has become a public health issue in many countries especially in developing countries. Family members who have a toddler with ASD face significant physical, emotional, and financial challenges. Early detection is crucial to achieve improvement in children with ASD. Objectives: The aim of the current research is to study the implementation of a training program for Autism in 4 health care facilities and to evaluate its initial outcomes. Methodology: An interventional study conducted among 63 health care workers dealing with children 18-30 months in 4 health care facilities (2 urban health care facilities and 2 rural health care facilities) in Giza governorate. A tailored autism health education message as well as training on using the Arabic validated version of the Modified Checklist for Autism in Toddlers (M-CHAT) were provided to the HCWs. Results: 58.7% of participating primary health care workers (HCWs) had a satisfactory level of awareness about childhood autism prior to the intervention, and 71.4% had a satisfactory level of understanding following it. When comparing the study subjects' pre-intervention knowledge scores to their post-intervention knowledge scores, there was a statistically significant improvement in their knowledge about autism (p < 0.001). Conclusion: The study's findings validate the value of specialized training programs in raising healthcare workers' awareness of childhood autism. Recommendations: Incorporation of autism spectrum disorder (ASD) within the educational curriculum of medical and nursing schools and ongoing education and training in ASD for health care workers.

Accuracy of the Screening Tool for Autism in Toddlers and Young Children in the primary care setting.

Specialists conduct autism evaluations using tools that are expensive and difficult to get trained on. Families often wait a long time and travel far to get a diagnosis for their child. To help with this problem, primary care practitioners can be trained to provide evaluations in local communities. However, usable and accurate tools developed for non-specialists are needed. The Screening Tool for Autism in Toddlers and Young Children (STAT) was created for this purpose, but limited research has been done on accuracy of the tool in community primary care. This study tested the STAT when used by primary care practitioners as part of a diagnostic evaluation in 130, 14- to 48-month-old children. We tested (1) STAT agreement with the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), and diagnosis based on an expert research evaluation, and (2) the relationship between STAT classification, primary care practitioner diagnosis, and expert diagnosis. STAT classification matched the ADOS-2 in 77% of cases and expert diagnosis in 78% of cases. Autistic children incorrectly classified by the STAT were older, had higher developmental and adaptive skills, and fewer autism symptoms. In 86% of cases, the STAT classification agreed with primary care practitioner diagnosis. STAT classification, primary care practitioner diagnosis, and expert diagnosis agreed in 73% of cases. Overall, the STAT shows good accuracy when used by primary care practitioners as part of a community primary care autism evaluation.

Challenging Case: Family Navigation for Autism Spectrum Disorder.

Leo is a 28-month-old boy from a monolingual Spanish-speaking family who was referred to a developmental-behavioral pediatrics (DBP) clinic for concerns regarding autism. His parents migrated to the United States 8 years ago and currently live and work on a farm. He was born in a US hospital after an uncomplicated pregnancy and has been generally healthy. His parents first became concerned about his development when he was 16 months old. He stopped saying mama/dada in Spanish and started lining up random objects. He had frequent temper tantrums and was difficult to console during unexpected changes in his routine. He screened positive on the Modified Checklist for Autism in Toddlers,Revised with Follow-Up (M-CHAT-R/F) at his 18-month well-child visit, and his pediatrician referred him to the local early intervention program. Calls from the early intervention program to his parents were unanswered. At his 24-month well-child visit, he again screened positive on the M-CHAT-R/F, and his pediatrician placed a referral for a DBP consultation. During the DBP visit at 28 months of age, developmental testing indicated his receptive and expressive language skills to be in the extremely low range, with significant scatter in his cognitive and adaptive skills. Behavioral observations were consistent with parental history and showed differences in social communication and interaction, the presence of repetitive behaviors, and extreme distress with transitions. He was diagnosed with autism spectrum disorder. Recommendations, including referral to early intervention, applied behavior analysis therapy, speech and language therapy, audiology evaluation, and genetic testing, were discussed with his parents through an interpreter. An autism packet, written in Spanish, with detailed information about autism and community resources was given to the family. By the time of a follow-up DBP visit 6 months later, Leo had not started on any early intervention or therapeutic services. Where do you go from here?

Investigating the Predictive Validity of the Quantitative Checklist for Autism in Toddlers and the Autism Diagnostic Observation Schedule-2 in Children at Elevated Likelihood for Autism.

This study examined the recurrence rate of autism in siblings at elevated likelihood (EL) and the predictive validity of the Q-CHAT and ADOS-2 at 14 and 24months (m) for a clinical best estimate (CBE) autism diagnosis at 3years. 331 EL-siblings (47.9% girls) from the prospective longitudinal EuroSibs study underwent ADOS-2 assessments and caregivers completed the Q-CHAT at 14m and 24m. At 3years CBE was determined using DSM-5 criteria. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were estimated. Autism recurrence rate was 25.7% [95% CI (21.1, 30.6)]. Q-CHAT sensitivity was 31.8% [95% CI (21.4, 43.6)] at 14m and 30.6% [95% CI (20.7, 41.7)] at 24m. Specificity was 81.2% [95% CI (75.4, 86.2)] at 14m and 94.8% [95% CI (91.2, 97.2)] at 24m. PPV was 35.6% [95% CI (24.2, 48.2)] at 14m and 66.7% [95% CI (49.8, 81.1)] at 24m. NPV was 78.5% [95% CI (72.6, 83.7)] and 79.9% [95% CI (74.7, 84.6)] respectively. ADOS-2 demonstrated a of 64.3% [95% CI (45.9, 80.2)] and 69.3% [95% CI (58.4, 79.0)] and a specificity of 71.1% [95% CI (60.3, 80.4)] and 68.7% [95% CI (62.5, 74.5)] at 14m and 24m respectively. PPV was 45% [95% CI (30.3, 60.4)] at 14m and 41.9% [95% CI (33.5, 50.7)] at 24m. NPV was 84.4% [95% CI (74.2, 91.8)] at 14m and 87.3% [95% CI (81.9, 91.6)] at 24m. Q-CHAT and ADOS-2 at 14m and 24m can aid in early differentiation between EL-siblings who need further assessment and those who do not, but neither has sufficient sensitivity and PPV for standalone CBE diagnosis prediction.

Predictors of Early Intervention Referral after a Positive Developmental Screen in Community Primary Care Clinics

BackgroundPrimary care physicians (PCPs) may rely upon factors other than screening test scores in making referral decisions to developmental services. This study investigated which patient, provider, and screening test factors predict a PCP’s IDEA Part C Early Intervention (EI) referral after a positive screening test result. MethodsChild demographics, developmental screening test results and EI referral decisions were collected via medical record review of 2,756 15-, 18-, 24- and 30-month well-child checks conducted at 7 community primary care clinics in 4 Oregon counties, in 2020-2021. A provider survey collected PCP demographic and professional characteristics. We tested the association of receipt of EI referral with screening test (Ages & Stages-3 [ASQ-3] and Modified Checklist for Autism in Toddlers – Revised [MCHAT-R]) scores, provider demographic information, child demographic data (sex, language, race/ ethnicity), using multivariable logistic regression. Results54.1% of children with positive MCHAT-R screens, and 42% of children with positive ASQ-3 screens received EI referrals. Multivariable analyses showed that MCHAT-R score, ASQ-3 Communication and Gross Motor scores were associated with referral after a positive screen. Child sex, race, ethnicity, and language, and provider demographics had no multivariable association with referral. Referral rates varied substantially by site and individual provider. ConclusionThe majority of toddlers with positive developmental screens were not receiving EI referrals from their PCP during the COVID-19 pandemic. Screening test thresholds and clinical thresholds for EI referral differ substantially, and some portions of the ASQ-3 do not seem to impact provider referral decisions. These findings may help inform physician training on developmental screening in primary care, specifically during times of unprecedented healthcare challenges.

Screening and Prediction of Autism in Toddlers Using SORF in Videos of Brief Family Interactions.

The purpose of this study was to validate the utility of the Systematic Observation of Red Flags (SORF) for autism screening during 10-minute parent-child interactions at ages 15-24 months. A total of 54 children participated in this study, including 19 with autism spectrum disorder (ASD), 23 with developmental delay, and 12 typically developing children. Coders coded 10-minute videos of parent-child interactions based on the defined scoring criteria. The discriminative ability for outcome diagnosis was evaluated for total score, social communication score, restricted repetitive behavior score, number of red flags, and composite score. SORF scores demonstrated good discriminative ability between ASD and non-ASD children, with the composite score (AUC = 0.884) showing the best discriminative ability for outcome diagnosis and predicting likelihood of ASD in young children. The composite score represented a simplified measurement, with the cutoff score of 7 and sensitivity and specificity of 0.789 and 0.800, respectively.

The Impact of Using Standardized Autism Screening on Referral to Specialist Evaluation for Young Children on the Autism Spectrum: A Cluster-Randomized Controlled Trial

We tested whether the implementation of standardized, high-fidelity screening for autism during routine well-child check-ups results in the following: increasing the number of children with suspected autism referred to diagnostic evaluation; lowering the age at which they are referred; and facilitating autism diagnosis for children across a more diverse range of demographic backgrounds and clinical presentations, including those with subtle manifestations. As part of a multi-site cluster randomized trial, pediatric practices were randomly assigned to an experimental condition involving training and supervision in the universal, standardized, high-fidelity implementation of the Modified Checklist for Autism in Toddlers, Revised with Follow-Up (M-CHAT-R/F), or a usual care condition. Children in both conditions identified as having a high likelihood of autism during well-child visits were referred to a diagnostic evaluation conducted by clinicians naive to referral source. Children referred to the diagnostic evaluation from the practices in the experimental condition were more numerous (n= 186) and younger (mean age= 20.65 months) than those referred from the practices in the usual care condition (n= 39; mean age= 23.58 months). Children referred by experimental practices who received an autism diagnosis had milder clinical presentations across measures of cognitive, language, adaptive, and social-communication functioning, compared to those referred from usual care practices. Demographic characteristics were similar across groups. Standardized, high-fidelity implementation of autism screening during pediatric well-child visits facilitates the identification of children with high autism likelihood at a younger age, including those presenting with more subtle clinical manifestations. Promoting Positive Outcomes for Individuals With ASD: Linking Early Detection, Treatment, and Long-term Outcomes; https://clinicaltrials.gov/; NCT03333629.

Positive Autism Screening Rates in Toddlers Born During the COVID-19 Pandemic

Stress and viral illness during pregnancy are associated with neurodevelopmental conditions in offspring. Autism screening positivity for children born during the pandemic remains unknown. To examine associations between prenatal exposure to the pandemic milieu and maternal SARS-CoV-2 infection with rates of positive Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R) screenings. Data for this cohort study were drawn from the COVID-19 Mother Baby Outcomes (COMBO) Initiative. M-CHAT-R scores obtained from children aged 16 to 30 months during routine clinical care at Columbia University Irving Medical Center in New York City were abstracted from electronic health records (EHRs) for children born between January 2018 and September 2021 (COMBO-EHR cohort). Separately, the M-CHAT-R was administered at 18 months for children born between February 2020 and September 2021 through a prospective longitudinal study (COMBO-RSCH cohort). Prenatal pandemic exposure (birth after March 1, 2020) and maternal SARS-CoV-2 status during pregnancy was determined through EHRs. Data were analyzed from March 2022 to June 2024. Prenatal exposures to the pandemic milieu and maternal SARS-CoV-2 infection. The primary outcome was rate of positive M-CHAT-R screenings. For all primary analyses, unadjusted χ2 tests and adjusted logistic regression models were performed. The COMBO-EHR cohort included 1664 children (442 born before the pandemic and 1222 born during the pandemic; 997 SARS-CoV-2 unexposed, 130 SARS-CoV-2 exposed, and 95 with unknown SARS-CoV-2 exposure status), of whom 266 (16.0%) were Black, 991 (59.6%) were Hispanic, 400 (24.0%) were White, 1245 (74.8%) were insured through Medicaid, 880 (52.9%) were male, and 204 (12.3%) were born prematurely. The COMBO-RSCH cohort included 385 children (74 born before the pandemic and 311 born during the pandemic; 201 SARS-CoV-2 unexposed, 101 SARS-CoV-2 exposed, and 9 with unknown SARS-CoV-2 exposure status), of whom 39 (10.1%) were Black, 168 (43.6%) were Hispanic, 157 (40.8%) were White, 161 (41.8%) were insured through Medicaid, 222 (57.7%) were male, and 38 (9.9%) were born prematurely. Prenatal pandemic exposure was not associated with a higher positive M-CHAT-R screening rate in either the COMBO-EHR or COMBO-RSCH cohort. Prenatal exposure to maternal SARS-CoV-2 infection was associated with a lower rate of M-CHAT-R positivity in the COMBO-EHR cohort (12.3% [16 children] vs 24.0% [239 children]; adjusted odds ratio, 0.40; 95% CI, 0.22-0.68; P = .001), but no association was found in the COMBO-RSCH cohort (12.9% [13 children] vs 19.9% [40 children]; adjusted odds ratio, 0.51; 95% CI, 0.24-1.04; P = .07). In this cohort study of 2 groups of children with prenatal pandemic exposure and/or exposure to maternal SARS-CoV-2 infection, neither exposure was associated with greater M-CHAT-R positivity.

Demographic and socioeconomic characteristics of patients diagnosed with autism through the Rapid Interactive screening Test for Autism in Toddlers.

We evaluated the integration of the Rapid Interactive screening Test for Autism in Toddlers (RITA-T) model in a community, comparing autism spectrum disorder (ASD) toddlers' demographic and socioeconomic characteristics. Of 394 ASD toddlers, 323 were screened with RITA-T. Those screened were from more deprived areas, traveled farther and were diagnosed earlier. The model improved the diagnosis of ASD in underserved areas.

Autism screening and diagnostic outcomes among toddlers bornpreterm.

To examine the Modified Checklist for Autism in Toddlers, Revised, with Follow-Up (M-CHAT-R/F), with follow-up screening and diagnostic outcomes for children born preterm. A secondary aim was to examine diagnostic evaluation attendance after screening to inform clinical practice. Using a cross-sectional design, 9725 toddlers (4951 males; 4774 females) whose gestational age was reported were screened at 15-month, 18-month, or 24-month well-child visits; screen-positive children were invited for an autism evaluation. Screening measure performance and diagnostic outcomes were evaluated according to preterm classification (Screening: nExtPreterm = 111; nVeryPreterm = 186; nModPreterm = 1122; nFullTerm = 8306; Evaluation: nExtPreterm = 27; nVeryPreterm = 21; nModPreterm = 86; nFullTerm = 301). Screen-positive rates were highest for children born extremely preterm (51.35%) and lowest for children born at term (6.95%). Evaluation attendance for screen-positive cases did not differ according to preterm classification. Rates of autism diagnoses differed depending on preterm birth status: for children born extremely preterm, it was 16.05%; for children born very preterm, it was 2.00%; for children born moderately preterm, it was 2.89%; and for children born at term, it was 1.49%. M-CHAT-R/F sensitivity decreased with increasing gestational age, whereas specificity improved with increasing gestational age. Positive predictive value was highest for children born extremely preterm and children born at term. Negative predictive value was consistently strong across all groups. The likelihood ratio for positive screening increased with gestational age. The sensitivity and specificity of the M-CHAT-R/F are acceptable in toddlers born preterm. Autism screening-positive rates and prevalence increased with earlier preterm birth. Those born extremely preterm showed the greatest likelihood of an autism diagnosis; screening should not be delayed based on adjusted age.

Autism spectrum disorder (ASD) diagnosis: A biochemical investigation into the diagnostic utility of S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH) levels and the SAM/SAH ratio

BackgroundThe balance between SAM and SAH ratios is critical for cellular methylation capacity such that a decrease in this ratio signals decrease the methylation potential, impacting cellular functions. In Autism Spectrum Disorder (ASD), impaired methylation processes are prominent, disrupting essential methyl group transfers crucial for DNA methylation, neurotransmitter synthesis, and detoxification. This disturbance affects gene expression and neural function, contributing to ASD development. This paper aims to explore ASD's pathogenesis by investigating biochemical parameters linked to the methylation cycle. For this purpose, some laboratory parameters are employed to aid in the understanding of potential laboratory abnormalities in ASD in children aged 2 to 8 years. Materials and MethodsThis study included a cohort of 43 children aged 2 to 8 years diagnosed ASD, alongside a control group of 43 age-and gender-matched healthy subjects. The serum of blood samples taken was used to measure biochemical factors. Specimens were processed using ELISA instrumentation and hemogram auto analyzers. The study conducted a statistical comparison between the ASD-diagnosed subjects and healthy controls, focusing on levels of S-adenosyl methionine (SAM), S-adenosyl homocysteine (SAH), Glycine N-methyltransferase (GNMT), and platelet counts. RESULTSThe levels of SAH and platelets were significantly higher in the case group compared to the control group. Conversely, levels of SAM, as well as the SAM/SAH ratio, were found to be significantly lower in the case group than in the control group (p < 0.05). No statistically significant difference was observed in the levels of GNMT when compared (p > 0.05). Receiver Operating Characteristic (ROC) analysis revealed that the diagnostic performance for SAM had an area under the curve (AUC) of 0.876, with a cut-off point determined at 286.9 ng/mL, yielding a sensitivity of 85 % and a specificity of 75 %. For SAH, the AUC was calculated to be 0.671, with a cut-off point set at 0.49 ng/mL, resulting in a sensitivity and specificity of 64 %. The SAM/SAH ratio demonstrated an AUC of 0.806, with the cut-off point established at 576.3, leading to a sensitivity and specificity of 72 %. A significant negative correlation was detected between the scores of the Modified Checklist for Autism in Toddlers (M-CHAT) and both SAM levels and the SAM/SAH ratio. The analysis indicated that an increase of one unit (1 ng/mL) in SAM levels is associated with a decreased autism risk by a factor of 1/0.914 = 1.1 %, whereas an increase of one unit (1 × 103/µL) in platelet count is associated with an increased autism risk by a factor of 1.019 %. Regarding glycine N-methyltransferase, no significant difference was observed between the two groups. ConclusionFollow-up studies with larger samples will be needed to better understand the potential for SAM, SAH, and SAM/SAH as a potential biomarker, at least for a subset of those with ASD. The correlation between these markers and the total score on the M-Chat raises further interest in this possibility. The correlation between these markers and the total score on the M-Chat further supports their utility as clinical biochemical laboratory parameters that could aid in the diagnosis of ASD.

Brief Report: Relationships Between Caregiver-Reported Externalizing and Internalizing Behaviors and the Modified Checklist for Autism in Toddlers.

Early detection and intervention are associated with improved outcomes for autistic children. Thus, it is important to understand factors influencing early screening tools designed to detect autism. This study examined the relationship between caregiver-reported emotional and behavioral symptoms and children's scores on a commonly used autism screening questionnaire, the Modified Checklist for Autism in Toddlers-Revised with Follow-Up (M-CHAT-R/F). Toddlers were recruited from four primary care clinics between 2018 and 2021. Their caregivers completed the M-CHAT-R/F as well as the Child Behavior Checklist (CBCL), a well-validated, normed measure of emotional and behavioral functioning. Correlational and group analyses were evaluated to examine relationships between CBCL scales and M-CHAT-R/F scores. 1765 toddlers were recruited for the study. CBCL scores for the internalizing, externalizing, autism, ADHD, and anxiety scales were all modestly positively correlated with M-CHAT-R/F scores. Compared to toddlers with elevated autism scale scores only, toddlers with elevations in both autism and ADHD/externalizing scales had higher M-CHAT-R/F scores. In contrast, no significant difference in scores were found between toddlers with elevated autism scale scores only compared to those with elevated scores on both autism and internalizing scales. Findings suggest that, for children with elevated autism behaviors, the presence of externalizing symptoms, including ADHD-related concerns, is associated with elevated scores on the M-CHAT-R/F. In contrast, internalizing symptoms did not show an association with elevated M-CHAT-R/F scores among toddlers with elevated autism-related behaviors. Interpretation of the M-CHAT-R/F should include consideration of co-occurring psychiatric conditions, especially externalizing conditions such as ADHD.

Two-Year Outcomes of Umbilical Cord Milking in Nonvigorous Infants

Compared with early cord clamping (ECC), umbilical cord milking (UCM) reduces delivery room cardiorespiratory support, hypoxic-ischemic encephalopathy, and therapeutic hypothermia in nonvigorous near-term and full-term infants. However, UCM postdischarge outcomes are not known. To determine the 2-year outcomes of children randomized to UCM or ECC at birth in the Milking in Nonvigorous Infants (MINVI) trial. A secondary analysis to evaluate longer-term outcomes of a cluster-randomized crossover trial was conducted from January 9, 2021, to September 25, 2023. The primary trial took place in 10 medical centers in the US, Canada, and Poland from January 5, 2019, to June 1, 2021, and hypothesized that UCM would reduce admission to the neonatal intensive care unit compared with ECC; follow-up concluded September 26, 2023. The population included near-term and full-term infants aged 35 to 42 weeks' gestation at birth who were nonvigorous; families provided consent to complete developmental screening questionnaires through age 2 years. UCM and ECC. Ages and Stages Questionnaire, 3rd Edition (ASQ-3) and Modified Checklist for Autism in Toddlers, Revised/Follow-Up (M-CHAT-R/F) questionnaires at ages 22 to 26 months. Intention-to-treat analysis and per-protocol analyses were used. Among 1730 newborns from the primary trial, long-term outcomes were evaluated in 971 children (81%) who had ASQ-3 scores available at 2 years or died before age 2 years and 927 children (77%) who had M-CHAT-R/F scores or died before age 2 years. Maternal and neonatal characteristics by treatment group were similar, with median birth gestational age of 39 (IQR, 38-40) weeks in both groups; 224 infants (45%) in the UCM group and 201 (43%) in the ECC group were female. The median ASQ-3 total scores were similar (UCM: 255 [IQR, 225-280] vs ECC: 255 [IQR, 230-280]; P = .87), with no significant differences in the ASQ-3 subdomains. Medium- to high-risk M-CHAT-R/F scores were also similar (UCM, 9% [45 of 486] vs ECC, 8% [37 of 441]; P = .86). In this secondary analysis of a randomized clinical trial among late near-term and full-term infants who were nonvigorous at birth, ASQ-3 scores at age 2 years were not significantly different between the UCM and ECC groups. Combined with previously reported important short-term benefits, this follow-up study suggests UCM is a feasible, no-cost intervention without longer-term neurodevelopmental risks of cord milking in nonvigorous near-term and term newborns. ClinicalTrials.gov Identifier: NCT03631940.

Improving Completion Rates for Autism Screening - A Quality Improvement Project

Introduction: Autism spectrum disorder (ASD) may be the most well-known and most studied neurocognitive disorder responsible for developmental delay. The medical community, in response to the noted increase in prevalence, emphasized the importance of routine screenings at 18 months and 24 to 30 months of age. Ascension St. John Children’s Hospital Resident Clinic utilizes the Modified Checklist for Autism in Toddlers, Revised with Follow-up (M-CHAT-R/F) or MCHAT for short, validated for ages 16 through 30 months. It was noted that screening is frequently missed or undocumented. Because of the need for timely diagnosis and intervention, these missed opportunities can be costly for children and their families. Purpose: To improve compliance with the American Academy of Pediatrics’ (AAP) recommendation to screen all children for ASD at 18 and 24 months of age. Methods: An educational lecture was provided to the pediatric residents to screen all children in the above age group being seen for a well-child visit. A visual reminder red pen mark was also applied to eligible patient charts as they were checked in. Baseline completion rates in two three month periods, one year before and three months after the intervention, were compared. Results: A total of 337 charts were reviewed with similar baseline characteristics between pre- and post-intervention groups. Overall MCHAT completion rates were lower after the intervention: 64% pre- vs. 49% post-intervention (p &lt;0.05). Subgroup analysis of visits where screening was directly indicated (excluding ages 16-17 months, &gt;24 month olds where a screen was already passed at a 24 month well visit, or children already diagnosed with autism, n = 281), had similar completion rates (67.5% and 64.5% respectively, p = 0.59). Conclusion: MCHAT completion did not improve after the combined intervention of a single, in-person lecture and visual reminder chart marking.

NFS-29. DEVELOPMENTAL SCREENING AND MONITORING IN NEUROFIBROMATOSIS-1

Abstract BACKGROUND Pilot data showed developmental screening at Neurofibromatosis-1 (NF1) appointments is feasible to identify those needing neuropsychology or other referrals. Outcomes for this larger sample, many re-screened and/or seen for a neuropsychology visit, allow us to describe evolving clinical management. METHODS Screenings are offered annually (ages 2-17) at NF1 clinic appointments by the psychosocial team. Forty-eight early childhood patients (ages 2-5) were screened (54% male, 66.7% White,) while 35 were ineligible (e.g., recent neuropsychology visit) or experienced logistical barriers to screening. These groups did not differ in race/ethnicity, sex, glioma status, or childhood opportunity index. Parents completed well-validated measures including the PEDS: Developmental Milestones – Assessment Level (PEDS:DM), Modified Checklist for Autism in Toddlers, and/or an ADHD Rating for preschoolers. RESULTS On initial screens, 73.9% showed a delay of 25% or more on at least one PEDS:DM domain. Measures often aligned with clinical impressions (81.3%); however, when findings were contextualized with record review, there were false positives (8.3%) and negatives (10.4%). Screening identified emerging concerns in attention, fine-motor, and academic skills. Nearly half (47.9%) of patients had services at the time of screening, and new/modified recommendations were offered for 70.8%. One third were referred to our Education Coordinator or Social Worker for educational advocacy, support through Early Intervention/school evaluation, or outpatient referrals. Twenty-two (45.8%) were referred to Neuropsychology and 18 have now been seen (consultation, targeted testing, or comprehensive evaluation) to confirm or rule-out neurodevelopmental diagnoses (e.g., autism, ADHD, language or global delay) and further guide educational or intervention management. Follow-up screens (N = 21) have monitored developmental progress, previously subclinical symptoms rising to a significant level, and need for re-evaluation or additional services. CONCLUSIONS Multipronged systematic screening results in referrals for diagnostic clarity, guides transition from Early Intervention to school services, and supports dynamic management of changing concerns.

Testing an online screening for autism in the COVID-19 pandemic: a psychometric study of the Q-CHAT-24 in Chilean toddlers.

The aim of this study was to examine some psychometric characteristics of the Chilean-adapted version of the Quantitative Checklist for Autism in Toddlers (Q-CHAT-24) (24) in a group of unselected children (community sample). This version was administered remotely through an online version during the pandemic period to caregivers of children, aged 18-24 months, registered in four primary care polyclinics of the Health Service Araucanía Sur, Chile. An intentional non-probabilistic sampling was used. Three hundred and thirteen toddlers were examined. Participants completed an online version of the Q-CHAT-24 which was disseminated through the REDCap platform. Evidence of reliability through internal consistency and evidence of predictive validity through ROC curve analysis were realized. The mean age of the children evaluated was 21.16 months. The Shapiro-Wilk test revealed that Q-CHAT-24 scores was normally distributed. 71 cases (23.12%) scored 38 points or more on the Q-CHAT-24, qualifying as Autistic Risk. 48 cases (15.63%) were confirmed as autistic through the ADOS-2 Module T. All items were positively correlated with Q-CHAT-24 total score. All items were positively correlated with Q-CHAT-24 total score. Internal consistency was acceptable for the Q-CHAT-24 (Cronbach ´s α=0.78). The internal consistencies were analyzed for the Q-CHAT-24 Factors, and they were good for factor 1 "Communication and Social Interaction" (Cronbach ´s α=0.85) and acceptable for factor 2 "Restrictive and Repetitive Patterns" (Cronbach ´s α=0.74). Receiver operating characteristic (ROC) curve analyses were performed. The AUC values were 0.93 with statistical significance (p<0.01). For the cut-off point of 38, the Sensitivity, Specificity and Youden index values were 0.89, 0.8 and 0.7, respectively. The Positive Predictive Value (PPV) was 86% and the Negative Predictive Value (NPV) was 85%. In accordance with the objectives of this study, evidence of reliability and predictive validity was demonstrated for the Q-CHAT-24 in this Chilean population. More importantly, this study provides Sensitivity and Specificity data for a remote application version of an autism screening tool already validated in Chile. The implications of this have to do with the possibility of establishing a remote assessment system for children at risk of autism on a population scale.

Combining developmental and sleep health measures for autism spectrum disorder screening: an ECHO study.

Sleep problems are reported for up to 80% of autistic individuals. We examined whether parsimonious sets of items derived from the Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R) and the Brief Infant Sleep Questionnaire (BISQ) are superior to the standard M-CHAT-R in predicting subsequent autism spectrum disorder (ASD) diagnoses. Participants from 11 Environmental influences on Child Health Outcomes (ECHO) cohorts were included. We performed logistic LASSO regression models with 10-fold cross-validation to identify whether a combination of items derived from the M-CHAT-R and BISQ are superior to the standard M-CHAT-R in predicting ASD diagnoses. The final sample comprised 1552 children. The standard M-CHAT-R had a sensitivity of 44% (95% CI: 34, 55), specificity of 92% (95% CI: 91, 94), and AUROC of 0.726 (95% CI: 0.663, 0.790). A higher proportion of children with ASD had difficulty falling asleep or resisted bedtime during infancy/toddlerhood. However, LASSO models revealed parental reports of sleep problems did not improve the accuracy of the M-CHAT-R in predicting ASD diagnosis. While children with ASD had higher rates of sleep problems during infancy/toddlerhood, there was no improvement in ASD developmental screening through the incorporation of parent-report sleep metrics. Parental-reported sleep problems are common in autism spectrum disorder (ASD). We investigated whether the inclusion of parental-reports of infant/toddler sleep patterns enhanced the effectiveness of developmental screening for autism. We reported higher rates of difficulty falling asleep and resisting bedtime during infancy and toddlerhood among children later diagnosed with ASD; however, we did not find an improvement in ASD developmental screening through the incorporation of parent-report sleep metrics. In our sample, the standard M-CHAT-R had a sensitivity of 39% among children of mothers with government insurance compared with a sensitivity of 53% among children of mothers with employer-based insurance.

Unraveling the Spectrum: A Comprehensive Review of Autism Spectrum Disorder in India.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by deficits in social interaction, communication difficulties, and repetitive behaviors that profoundly impact the lives of affected individuals and their families. This article provides a comprehensive overview of ASD, focusing on screening, diagnosis, and intervention strategies. Early signs of ASD can manifest in infancy, but parents may not recognize them until their child falls behind in meeting social milestones. This delay in recognition is often due to a lack of awareness, societal stigma, and limited knowledge about developmental and behavioral disorders. Globally, ASD prevalence is increasingpotentially due to broader diagnostic criteria, increased awareness, and improved screening practices. Screening for ASD is crucial for early identification and intervention. Various tools are available such as the Modified Checklist for Autism in Toddlers (M-CHATs), Trivandrum Autism Behavioral Checklist (TABC), and the Social Communication Questionnaire (SCQ). Diagnosing ASD involves using established criteria such as the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), and specific diagnostic tools like the Autism Diagnostic Observation Schedule (ADOS) and the Indian Scale for the Assessment of Autism (ISAA). Interventions for ASD should be multidisciplinary, involving professionals such as developmental pediatricians, psychologists, psychiatrists, special educators, occupational therapists, physiotherapists, speech therapists, and social workers. Applied behavior analysis (ABA), naturalistic developmental behavioral interventions (NDBIs), and parent-mediated treatment are among the evidence-based approaches. Additionally, speech-language therapy, motor therapy, and sensory integration therapy play vital roles in addressing the diverse needs of individuals with ASD. Medical interventions should be used alongside behavioral and environmental strategies. Early screening, accurate diagnosis, and tailored interventions are essential for improving the lives of individuals with ASD. A multidisciplinary approach and increased awareness are crucial in addressing the growing prevalence of ASD worldwide.

"Everyone screens to some extent": Barriers and facilitators of developmental screening among children with sickle cell disease: A mixed methods study.

Developmental delays are common among children with sickle cell disease (SCD). Existing guidelines support consistent screening to increase the identification of deficits and support referral to rehabilitative interventions, yet adherence remains variable. This study sought to assess current practices and identify barriers and facilitators to improve developmental screening for children 0-3years with SCD. A mixed methods approach, guided by the Exploration and Preparation stages of the Exploration, Preparation, Implementation, and Sustainment (EPIS) framework, assessed developmental screening practices among primary care providers and hematologists. Phase 1 included the SCD Developmental Surveillance and Screening Guideline and Practice Survey. Phase 2 included the SCD Developmental Screening Organizational Survey alongside semi-structured interviews. Descriptive and qualitative methods summarized the findings. Thirty-three providers from general pediatrics and hematology completed phase 1. Use of standardized developmental screening measures was variable, with the most frequently used being the Modified Checklist for Autism in Toddlers (77%) and the Ages and Stages Questionnaire (55%). Fifteen providers participated in phase 2, and reported they were most likely to engage in changes to improve their practice (mean=4.4/5) and least likely to support spiritual health and well-being (mean=3.5/5). Three themes emerged:(i) developmental screening is not standardized or specific to SCD, (ii) children with SCD benefit from a multidisciplinary team, and (iii) healthcare system limitations are a barrier. Developmental screening is inconsistent and insufficient for young children with SCD. Providers are interested in supporting children with SCD, but report a lack of standardized measures and consistent guidance as barriers.

Development of a school-age extension of the Modified Checklist for Autism in Toddlers through expert consensus and stakeholder input.

The American Academy of Pediatrics recommends universal screening to identify children at higher likelihood for autism at 18- and 24-month well-child visits. There are many children, however, that are missed during this toddler age who do not get diagnosed until much later in development, delaying access to autism-specific interventions. Currently, brief measures for universal autism screening for school-age children, however, are lacking. In this project, we adapted a commonly used autism screener for toddlers, the Modified Checklist for Autism in Toddlers, Revised, with Follow-Up (M-CHAT-R/F), to be used for school-age children. This measure, called the M-CHAT-School (M-CHAT-S), is a parent- and teacher-report questionnaire to be used to screen for autism in school-age children aged 4 to 8 years of age. M-CHAT-S was developed through feedback from autism experts, as well as interviews with parents and teachers to provide input on the items. Two versions of M-CHAT-S were developed, one for verbally fluent and one for minimally verbal school-age children. M-CHAT-S is a brief measure, with updated items to reflect changes in the way experts think and talk about autism, making it a useful measure to use for autism screening in elementary aged children. The next steps include further testing to ensure that M-CHAT-S performs well in identifying children with increased likelihood of autism, after which it will be made available to parents, educators, and other professionals.