Significant use of non-evidence-based therapeutics in a cohort of Australian fibromyalgia patients.

BACKGROUND: Fibromyalgia is a common condition characterised by chronic widespread musculoskeletal pain and central sensitivity features. Appropriate management requires a multidisciplinary approach prioritising non-pharmacological strategies. Evidence-based fibromyalgia medications are not always easily available, effective or tolerated. AIM: To characterise actual medication usage in Australian fibromyalgia patients. METHODS: Demographic and clinical data, including medication use information, were gathered by chart review from patients attending the Monash Fibromyalgia Clinic between January 2019 and June 2022. Eligible patients were invited to complete an anonymous questionnaire between June and August 2022 to assess current therapeutic use. The questionnaire assessed fibromyalgia clinical features by using the Revised Fibromyalgia Impact Questionnaire and the 2016 modified American College of Rheumatology Fibromyalgia criteria. RESULTS: The chart review included 474 patients, and 108 participants completed the questionnaire. Most chart review (78.7%) and questionnaire participants (85.2%) reported using at least one medication for their fibromyalgia. 48.5% of chart review patients and 58.3% of questionnaire participants reported using at least one evidence-based medication, usually amitriptyline, duloxetine or pregabalin. However, the most common individual medications for questionnaire participants were non-steroidal anti-inflammatory drugs (48.2%), paracetamol (59.3%) and opioids (34.3%), with most opioids being typical opioids. Among questionnaire participants, 14.8% reported using cannabinoids, and 70.4% reported using at least one supplement, vitamin or herbal/naturopathic preparation. Not all medication or substance use was recorded during clinic appointments. CONCLUSION: Fibromyalgia patients engage in various pharmacotherapeutic strategies that are not always evidence-based or disclosed to their treating clinicians.

Commentary: Embracing innovation is necessary to improve assessment and care for individuals with ASD: a reflection on Kanne and Bishop (2020).

This commentary is offered in response to Kanne and Bishop (2020) who urge caution in adopting new devices and processes for ASD assessment and advocate that that comprehensive, expert-driven, diagnostic models for ASD remain essential to maintain quality standards. While we agree that there is a critical shortage in current care, we propose that developing suites of tools and innovative approaches for screening, risk-classification, formal diagnosis, and rich assessment of abilities and challenges may be of great value to families and necessary to improve current systems of care. As well, the evaluation of 'assessment quality' should take into consideration both content and process, with a focus on achieving meaningful outcomes and optimizing family experience.

A Predictive Multimodal Framework to Alert Caregivers of Problem Behaviors for Children with ASD (PreMAC).

Autism Spectrum Disorder (ASD) impacts 1 in 54 children in the US. Two-thirds of children with ASD display problem behavior. If a caregiver can predict that a child is likely to engage in problem behavior, they may be able to take action to minimize that risk. Although experts in Applied Behavior Analysis can offer caregivers recognition and remediation strategies, there are limitations to the extent to which human prediction of problem behavior is possible without the assistance of technology. In this paper, we propose a machine learning-based predictive framework, PreMAC, that uses multimodal signals from precursors of problem behaviors to alert caregivers of impending problem behavior for children with ASD. A multimodal data capture platform, M2P3, was designed to collect multimodal training data for PreMAC. The development of PreMAC integrated a rapid functional analysis, the interview-informed synthesized contingency analysis (IISCA), for collection of training data. A feasibility study with seven 4 to 15-year-old children with ASD was conducted to investigate the tolerability and feasibility of the M2P3 platform and the accuracy of PreMAC. Results indicate that the M2P3 platform was well tolerated by the children and PreMAC could predict precursors of problem behaviors with high prediction accuracies.

Transgenic overexpression of CTRP3 prevents alcohol-induced hepatic triglyceride accumulation.

This study tested the ability of a novel adipose tissue derived cytokine, C1q TNF-related protein-3 (CTRP3), to prevent alcohol-induced hepatic lipid accumulation, or alcoholic fatty liver disease (ALD). Previous work has demonstrated that CTRP3 is effective at preventing high-fat diet-induced fatty liver; however, the potential of CTRP3 to inhibit ALD has not been explored. To test the potential protective effects of CTRP3, transgenic mice overexpressing CTRP3 (Tg) or wild-type littermates (WT) were subjected to one of two different models of ALD. In the first model, known as the NIAAA model, mice were fed control or alcohol-containing liquid diets (5% vol/vol) for 10 days followed by a single gavage of ethanol (5 g/kg). In the second model, the chronic model, mice were fed control or alcohol-containing diets for 6 wk with no gavage. This study found that CTRP3 reduced triglyceride accumulation in the chronic model of alcohol consumption by ~50%, whereas no reduction was observed in the NIAAA model. Further analysis of isolated primary hepatocytes from WT and Tg mice demonstrated that CTRP3 increased oxygen consumption in the presence of fatty acids, indicating that CTRP3 increases hepatic fatty acid utilization. In conclusion, this study indicates that CTRP3 attenuates hepatic triglyceride accumulation in response to long-term chronic, but not short-term, alcohol consumption.

Longitudinal prediction of language emergence in infants at high and low risk for autism spectrum disorder.

This study used a prospective longitudinal design to examine the early developmental pathways that underlie language growth in infants at high risk (n = 50) and low risk (n = 34) for autism spectrum disorder in the first 18 months of life. While motor imitation and responding to joint attention (RJA) have both been found to predict expressive language in children with autism spectrum disorder and those with typical development, the longitudinal relation between these capacities has not yet been identified. As hypothesized, results revealed that 15-month RJA mediated the association between 12-month motor imitation and 18-month expressive vocabulary, even after controlling for earlier levels of RJA and vocabulary. These results provide new information about the developmental sequencing of skills relevant to language growth that may inform future intervention efforts for children at risk for language delay or other developmental challenges.

Screening, Diagnosis, and Intervention for Autism: Experiences of Black and Multiracial Families Seeking Care.

PURPOSE: Despite advances in screening and awareness, Black and multiracial families continue to experience challenges when seeking an autism diagnosis for their children. METHODS: We surveyed 400 Black and multiracial families of young children with autism from an existing research database in the United States about their retrospective diagnostic experiences. We gathered quantitative and qualitative data and engaged in iterative coding to understand timing and content of first concerns, families' experiences of care providers and systems, and the impact of race and culture on accessing care. RESULTS: Families provided examples of early developmental concern and described provider, systemic, and cultural barriers and facilitators to care. Families also provided insight into the influence of culture and made recommendations on how the medical system could better care for Black and multiracial families of children with autism. CONCLUSIONS: Results add to a growing body of literature supporting the need for culturally sensitive and accessible care related to developmental monitoring, diagnosis, and follow-up care for Black and multiracial children.

Screening Options in Autism Telediagnosis: Examination of TAP, M-CHAT-R, and DCI Concordance and Predictive Value in a Telediagnostic Model.

Tele-assessment of autism in early childhood has increased. However, it is unclear how autism screening tools (M-CHAT-R, DCI) function as part of tele-assessment and relate to a commonly used tele-assessment instrument, the TAP. 361 families from a clinically referred sample of children (mean age: 27.63 months, sd = 4.86 months) completed the M-CHAT-R and DCI prior to a tele-assessment visit utilizing the TAP. Data was collected on demographic background, measure scores, and diagnostic outcome. No significant differences in measure scores or diagnostic findings emerged in age at referral, age group, age at diagnosis, or child sex, ethnicity, or racial background. The M-CHAT-R and DCI correlated strongly and positively. Older age was associated with lower risk scores on screening instruments. Children with autism had significantly higher scores on all screener and subdomain scores, with the exception of DCI Behavior. Subdomains of the DCI emerged as the strongest predictor of diagnostic outcome. Both the DCI total score and the M-CHAT-R significantly related to diagnostic outcome and TAP score in this tele-assessment model, regardless of child age or sex. Findings also support use of the DCI for children under 24 months of age.

Measuring Developmental Delays: Comparison of Parent Report and Direct Testing.

PURPOSE: Developmental assessment is part of a comprehensive autism evaluation. During in-person evaluations, developmental assessment is completed via direct testing by an examiner. In telehealth evaluations, developmental assessment relies on caregiver-report instruments. This study examined correspondence between caregiver report and direct testing of developmental skills. METHODS: Participants were 93 children, aged 18-42 months, undergoing evaluation for possible autism spectrum disorder (ASD). Caregivers were interviewed with the Developmental Profile, 4th edition (DP-4) via telehealth platform and children were tested in person 2-4 weeks later using the Mullen Scales of Early Learning (MSEL). RESULTS: Correlations between the DP-4 and MSEL were high (ranging from 0.50 to 0.82) across standard scores, age equivalents, and functional categories, as well as across individual subtests and overall composite scores. CONCLUSION: The high convergent validity found in this study suggests that the DP-4 provides a suitable proxy for direct developmental testing using the MSEL in the context of telehealth evaluations for ASD in young children, delivering a good estimate of both developmental functioning and presence of delays. TRIAL REGISTRATION: Data were obtained from registered clinical trial NCT05047224, date of registration 2021-09-07.

Increased photocorrosion resistance of ZnO foams via transition metal doping.

ZnO is a widely studied photocatalyst, but practical use is hindered by its low resistance to photocorrosion in water, which leads to metal leaching and loss of performance over time. In this work, highly porous and mechanically stable ZnO foams, called MolFoams, were doped by adding 1% or 2% Co, Ni or Cu salts to the starting Zn salt, followed by air insufflation during a sol-gel rection and sintering. The resulting doped foams showed a major increase in stability, with a 60-85% reduction in Zn2+ leaching after irradiation, albeit with a reduction in photocatalytic activity. A systematic analysis using XRD, Raman, XPS and XANES allowed for the identification of dopant species in the foams revealing the presence of Co3O4, NiO and Cu2O within the ZnO lattice with doping leading to a reduced band gap and significant increases in the resistance to photocorrosion of ZnO while identifying the cause of the reduction in photocatalytic activity to be shifting of the band edge positions. These results provide a pathway to significantly reduce the photocorrosion of ZnO in water, with further work required to maintain the photocatalytic activity of undoped ZnO.

Correction: Increased photocorrosion resistance of ZnO foams via transition metal doping.

[This corrects the article DOI: 10.1039/D2RA06730G.].

Development of a Novel Telemedicine Tool to Reduce Disparities Related to the Identification of Preschool Children with Autism.

The wait for ASD evaluation dramatically increases with age, with wait times of a year or more common as children reach preschool. Even when appointments become available, families from traditionally underserved groups struggle to access care. Addressing care disparities requires designing identification tools and processes specifically for and with individuals most at-risk for health inequities. This work describes the development of a novel telemedicine-based ASD assessment tool, the TELE-ASD-PEDS-Preschool (TAP-Preschool). We applied machine learning models to a clinical data set of preschoolers with ASD and other developmental concerns (n = 914) to generate behavioral targets that best distinguish ASD and non-ASD features. We conducted focus groups with clinicians, early interventionists, and parents of children with ASD from traditionally underrepresented racial/ethnic and linguistic groups. Focus group themes and machine learning analyses were used to generate a play-based instrument with assessment tasks and scoring procedures based on the child's language (i.e., TAP-P Verbal, TAP-P Non-verbal). TAP-P procedures were piloted with 30 families. Use of the instrument in isolation (i.e., without history or collateral information) yielded accurate diagnostic classification in 63% of cases. Children with existing ASD diagnoses received higher TAP-P scores, relative to children with other developmental concerns. Clinician diagnostic accuracy and certainty were higher when confirming existing ASD diagnoses (80% agreement) than when ruling out ASD in children with other developmental concerns (30% agreement). Utilizing an equity approach to understand the functionality and impact of tele-assessment for preschool children has potential to transform the ASD evaluation process and improve care access.

Development of an App for Tracking Family Engagement With Early Intervention Services: Focus Groups and Pilot Evaluation Study.

BACKGROUND: Expedient access to early intervention (EI) systems has been identified as a priority for children with developmental delays, identified disabilities, and other special health care needs. Despite the mandated availability of EI, it remains challenging for families to navigate referral processes and establish appropriate services. Such challenges disproportionately affect families from traditionally underserved communities. Mobile health apps can improve clinical outcomes, increase accessibility to health services, and promote adherence to health-related interventions. Though promising, the implementation of apps within routine care is in its infancy, with limited research examining the components of what makes an effective app or how to reach families most impacted by inequities in health care delivery. OBJECTIVE: In study 1, we conducted focus groups to access a broad range of perspectives on the process of navigating the EI system, with the dual goals of identifying ways in which a patient-facing app might facilitate this process and identifying barriers to use with traditionally underrepresented and underserved groups. In study 2, focus group findings informed the development of a patient-facing app, which was subsequently tested with a pilot sample of 5 families. METHODS: In study 1, the focus groups included 29 participants from 4 shareholder groups. Targeted sampling was used to recruit participants from traditionally underrepresented groups. Focus group questions sought information about barriers families experience as they navigate the EI system, ideal features of a patient-facing app designed to track family engagement with the EI system, and potential barriers. Focus group procedures were informed by the Consolidated Framework for Implementation Research framework. In study 2, a pilot app was developed. The app was tested with a sample of 5 families of young children involved in the EI system. Families provided information on app functionality and usability. RESULTS: Qualitative analysis revealed a desire for increased communication and information about the process of accessing EI services, potential utility of an app for communication purposes, and clear recommendations for app features. Insights from focus groups were used to inform the development of the Family on Track app and related implementation supports. App features included survey customization, timing and delivery of prompts, and questions related to barriers and service satisfaction. Implementation supports include a visual guide for app installation, resources related to common family questions, and availability of study personnel to guide families through installation and provide ongoing support. Field testing provided preliminary information about app usability, including identifying future directions. CONCLUSIONS: The results of this study could support the development of a new way for the EI system to communicate and connect with families, provide families with a means to communicate satisfaction and frustration, and access the supports they need to be active participants in their child's care.

A Randomized Trial of the Accuracy of Novel Telehealth Instruments for the Assessment of Autism in Toddlers.

PURPOSE: Telemedicine approaches to autism (ASD) assessment have become increasingly common, yet few validated tools exist for this purpose. This study presents results from a clinical trial investigating two approaches to tele-assessment for ASD in toddlers. METHODS: 144 children (29% female) between 17 and 36 months of age (mean = 2.5 years, SD = 0.33 years) completed tele-assessment using either the TELE-ASD-PEDS (TAP) or an experimental remote administration of the Screening Tool for Autism in Toddlers (STAT). All children then completed traditional in-person assessment with a blinded clinician, using the Mullen Scales of Early Learning (MSEL), Vineland Adaptive Behavior Scales, 3rd Edition (VABS-3), and Autism Diagnostic Observation Schedule (ADOS-2). Both tele-assessment and in-person assessment included a clinical interview with caregivers. RESULTS: Results indicated diagnostic agreement for 92% of participants. Children diagnosed with ASD following in-person assessment who were missed by tele-assessment (n = 8) had lower scores on tele- and in-person ASD assessment tools. Children inaccurately identified as having ASD by tele-assessment (n = 3) were younger than other children and had higher developmental and adaptive behavior scores than children accurately diagnosed with ASD by tele-assessment. Diagnostic certainty was highest for children correctly identified as having ASD via tele-assessment. Clinicians and caregivers reported satisfaction with tele-assessment procedures. CONCLUSION: This work provides additional support for the use of tele-assessment for identification of ASD in toddlers, with both clinicians and families reporting broad acceptability. Continued development and refinement of tele-assessment procedures is recommended to optimize this approach for the needs of varying clinicians, families, and circumstances.

Design of a Desktop Virtual Reality-Based Collaborative Activities Simulator (ViRCAS) to Support Teamwork in Workplace Settings for Autistic Adults.

Autistic adults possess many skills sought by employers, but may be at a disadvantage in the workplace if social-communication differences negatively impact teamwork. We present a novel collaborative virtual reality (VR)-based activities simulator, called ViRCAS, that allows autistic and neurotypical adults to work together in a shared virtual space, offering the chance to practice teamwork and assess progress. ViRCAS has three main contributions: 1) a new collaborative teamwork skills practice platform; 2) a stakeholder-driven collaborative task set with embedded collaboration strategies; and 3) a framework for multimodal data analysis to assess skills. Our feasibility study with 12 participant pairs showed preliminary acceptance of ViRCAS, a positive impact of the collaborative tasks on supported teamwork skills practice for autistic and neurotypical individuals, and promising potential to quantitatively assess collaboration through multimodal data analysis. The current work paves the way for longitudinal studies that will assess whether the collaborative teamwork skill practice that ViRCAS provides also contributes towards improved task performance.

Paisley: Preliminary validation of a novel app-based e-Screener for ASD in children 18-36 months.

The purpose of this study was to assess the validity of an autism e-screener, Paisley, when utilized in a clinical research setting via a tablet application. The Paisley application used a series of play-based activities, all of which incorporated varying aspects of the ASD-PEDS. Participants included children (18-36 months; n = 198) referred for evaluation of autism spectrum disorder (ASD) and community providers (n = 66) with differing levels of familiarity with ASD. Community providers administered the Paisley application to children who then completed a comprehensive psychological evaluation. Based on comprehensive evaluation, 75% of children met diagnostic criteria for ASD. Paisley scores were significantly higher for children diagnosed with ASD (15.06) versus those not diagnosed (9.34). The newly determined cutoff ASD-PEDS cutoff score of 13 had significantly higher specificity and positive predictive value than the originally proposed cutoff of 11. Results support the use of Paisley by community providers to identify autism risk in toddlers. Limitations and strengths of the work, as well as opportunities for future clinical validation, are described.

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

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

Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2020.

Problem/Condition: Autism spectrum disorder (ASD). Period Covered: 2020. Description of System: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance program that provides estimates of the prevalence of ASD among children aged 8 years. In 2020, there were 11 ADDM Network sites across the United States (Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin). To ascertain ASD among children aged 8 years, ADDM Network staff review and abstract developmental evaluations and records from community medical and educational service providers. A child met the case definition if their record documented 1) an ASD diagnostic statement in an evaluation, 2) a classification of ASD in special education, or 3) an ASD International Classification of Diseases (ICD) code. Results: For 2020, across all 11 ADDM sites, ASD prevalence per 1,000 children aged 8 years ranged from 23.1 in Maryland to 44.9 in California. The overall ASD prevalence was 27.6 per 1,000 (one in 36) children aged 8 years and was 3.8 times as prevalent among boys as among girls (43.0 versus 11.4). Overall, ASD prevalence was lower among non-Hispanic White children (24.3) and children of two or more races (22.9) than among non-Hispanic Black or African American (Black), Hispanic, and non-Hispanic Asian or Pacific Islander (A/PI) children (29.3, 31.6, and 33.4 respectively). ASD prevalence among non-Hispanic American Indian or Alaska Native (AI/AN) children (26.5) was similar to that of other racial and ethnic groups. ASD prevalence was associated with lower household income at three sites, with no association at the other sites.Across sites, the ASD prevalence per 1,000 children aged 8 years based exclusively on documented ASD diagnostic statements was 20.6 (range = 17.1 in Wisconsin to 35.4 in California). Of the 6,245 children who met the ASD case definition, 74.7% had a documented diagnostic statement of ASD, 65.2% had a documented ASD special education classification, 71.6% had a documented ASD ICD code, and 37.4% had all three types of ASD indicators. The median age of earliest known ASD diagnosis was 49 months and ranged from 36 months in California to 59 months in Minnesota.Among the 4,165 (66.7%) children with ASD with information on cognitive ability, 37.9% were classified as having an intellectual disability. Intellectual disability was present among 50.8% of Black, 41.5% of A/PI, 37.8% of two or more races, 34.9% of Hispanic, 34.8% of AI/AN, and 31.8% of White children with ASD. Overall, children with intellectual disability had earlier median ages of ASD diagnosis (43 months) than those without intellectual disability (53 months). Interpretation: For 2020, one in 36 children aged 8 years (approximately 4% of boys and 1% of girls) was estimated to have ASD. These estimates are higher than previous ADDM Network estimates during 2000-2018. For the first time among children aged 8 years, the prevalence of ASD was lower among White children than among other racial and ethnic groups, reversing the direction of racial and ethnic differences in ASD prevalence observed in the past. Black children with ASD were still more likely than White children with ASD to have a co-occurring intellectual disability. Public Health Action: The continued increase among children identified with ASD, particularly among non-White children and girls, highlights the need for enhanced infrastructure to provide equitable diagnostic, treatment, and support services for all children with ASD. Similar to previous reporting periods, findings varied considerably across network sites, indicating the need for additional research to understand the nature of such differences and potentially apply successful identification strategies across states.

Early Identification of Autism Spectrum Disorder Among Children Aged 4 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2020.

Problem/Condition: Autism spectrum disorder (ASD). Period Covered: 2020. Description of System: The Autism and Developmental Disabilities Monitoring Network is an active surveillance program that estimates prevalence and characteristics of ASD and monitors timing of ASD identification among children aged 4 and 8 years. In 2020, a total of 11 sites (located in Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin) conducted surveillance of ASD among children aged 4 and 8 years and suspected ASD among children aged 4 years. Surveillance included children who lived in the surveillance area at any time during 2020. Children were classified as having ASD if they ever received 1) an ASD diagnostic statement in an evaluation, 2) a special education classification of autism (eligibility), or 3) an ASD International Classification of Diseases (ICD) code (revisions 9 or 10). Children aged 4 years were classified as having suspected ASD if they did not meet the case definition for ASD but had a documented qualified professional's statement indicating a suspicion of ASD. This report focuses on children aged 4 years in 2020 compared with children aged 8 years in 2020. Results: For 2020, ASD prevalence among children aged 4 years varied across sites, from 12.7 per 1,000 children in Utah to 46.4 in California. The overall prevalence was 21.5 and was higher among boys than girls at every site. Compared with non-Hispanic White children, ASD prevalence was 1.8 times as high among Hispanic, 1.6 times as high among non-Hispanic Black, 1.4 times as high among Asian or Pacific Islander, and 1.2 times as high among multiracial children. Among the 58.3% of children aged 4 years with ASD and information on intellectual ability, 48.5% had an IQ score of ≤70 on their most recent IQ test or an examiner's statement of intellectual disability. Among children with a documented developmental evaluation, 78.0% were evaluated by age 36 months. Children aged 4 years had a higher cumulative incidence of ASD diagnosis or eligibility by age 48 months compared with children aged 8 years at all sites; risk ratios ranged from 1.3 in New Jersey and Utah to 2.0 in Tennessee. In the 6 months before the March 2020 COVID-19 pandemic declaration by the World Health Organization, there were 1,593 more evaluations and 1.89 more ASD identifications per 1,000 children aged 4 years than children aged 8 years received 4 years earlier. After the COVID-19 pandemic declaration, this pattern reversed: in the 6 months after pandemic onset, there were 217 fewer evaluations and 0.26 fewer identifications per 1,000 children aged 4 years than children aged 8 years received 4 years earlier. Patterns of evaluation and identification varied among sites, but there was not recovery to pre-COVID-19 pandemic levels by the end of 2020 at most sites or overall. For 2020, prevalence of suspected ASD ranged from 0.5 (California) to 10.4 (Arkansas) per 1,000 children aged 4 years, with an increase from 2018 at five sites (Arizona, Arkansas, Maryland, New Jersey, and Utah). Demographic and cognitive characteristics of children aged 4 years with suspected ASD were similar to children aged 4 years with ASD. Interpretation: A wide range of prevalence of ASD by age 4 years was observed, suggesting differences in early ASD identification practices among communities. At all sites, cumulative incidence of ASD by age 48 months among children aged 4 years was higher compared with children aged 8 years in 2020, indicating improvements in early identification of ASD. Higher numbers of evaluations and rates of identification were evident among children aged 4 years until the COVID-19 pandemic onset in 2020. Sustained lower levels of ASD evaluations and identification seen at a majority of sites after the pandemic onset could indicate disruptions in typical practices in evaluations and identification for health service providers and schools through the end of 2020. Sites with more recovery could indicate successful strategies to mitigate service interruption, such as pivoting to telehealth approaches for evaluation. Public Health Action: From 2016 through February of 2020, ASD evaluation and identification among the cohort of children aged 4 years was outpacing ASD evaluation and identification 4 years earlier (from 2012 until March 2016) among the cohort of children aged 8 years in 2020 . From 2016 to March 2020, ASD evaluation and identification among the cohort of children aged 4 years was outpacing that among children aged 8 years in 2020 from 2012 until March 2016. The disruptions in evaluation that coincided with the start of the COVID-19 pandemic and the increase in prevalence of suspected ASD in 2020 could have led to delays in ASD identification and interventions. Communities could evaluate the impact of these disruptions as children in affected cohorts age and consider strategies to mitigate service disruptions caused by future public health emergencies.

Systemic Bevacizumab for Severe Recurrent Respiratory Papillomatosis.

Recurrent respiratory papillomatosis (RRP) is the most common benign pediatric laryngeal neoplasm. Various adjuvant medical therapies have failed to reliably decrease surgical frequency in this challenging airway disease. Recently, systemic bevacizumab has shown promise in advanced, treatment-resistant papillomatosis. We describe the use of systemic bevacizumab in two children with severe RRP unresponsive to other therapies. Voice and breathing improved dramatically in both patients with minimal side effects. Both patients have not required surgery in 24 months and 16 months, respectively. Systemic bevacizumab is a promising long-term treatment for severe RRP, with oncology playing an important role in patient care.

Black Families' Experiences of Developmental Screening: Review of Well-Child Visits to Inform Enhanced Autism Spectrum Disorder Risk Assessment.

OBJECTIVE: Black families face barriers to early diagnosis of autism spectrum disorder (ASD). Most work emphasizes systemic delays to diagnosis rather than how existing screening procedures may affect identification. Our goal was to examine pediatric care visits in which screening was most likely to occur to document behaviors of parents and providers. METHODS: We examined 18- to 36-month primary care visits in our electronic health record system (n = 99) of thirty-nine 4- and 8-year-old Black children later diagnosed with ASD. We extracted qualitative and quantitative data and engaged in consensus coding. We captured whether formal screening occurred, the content of concerns of parents and providers, and referral patterns for follow-up care or evaluation. RESULTS: Consistent with existing work, we found differences in parent and provider concerns and discrepancies in referral rates. Parents often endorsed concerns about language, sleeping or eating habits, behavior, or motor skills rather than ASD, but specific mention of ASD as a concern increased over time. Referrals for follow-up care were more likely when providers, not parents alone, expressed concerns about patient development. CONCLUSION: Pediatric providers cannot place the burden on families to raise autism concerns. Although some level of developmental risk was noted at most visits for children later diagnosed with ASD, referrals were only made when providers were also concerned, and most of these were for speech-language evaluation. Ongoing work is necessary to better understand how existing care systems interact with diverse families to inform the creation of inclusive screening practices that mitigate diagnostic delays.