Early developmental milestone clusters of autistic children based on electronic health records / Joshua GUEDALIA ; Keren ILAN ; Galit SHEFER ; Roe COHEN ; Lidia V. GABIS in Autism Research, 17-8 (August 2024)  

Public ISBD [article]  inAutism Research > 17-8 (August 2024) . - p.1616-1627 Titre : Early developmental milestone clusters of autistic children based on electronic health records Type de document : Texte imprimé et/ou numérique Auteurs : Joshua GUEDALIA, Auteur ; Keren ILAN, Auteur ; Galit SHEFER, Auteur ; Roe COHEN, Auteur ; Lidia V. GABIS, Auteur Article en page(s) : p.1616-1627 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : Abstract Autistic children vary in symptoms, co-morbidities, and response to interventions. This study aimed to identify clusters of autistic children with a distinct pattern of attaining early developmental milestones (EDMs). The clustering of 5836 autistic children was based on the attainment of 43 gross motor, fine motor, language, and social developmental milestones during the first 3?years of life as recorded in baby wellness visits. K-means cluster analysis detected four EDM clusters: mild (n = 1686); moderate (n = 1691); severe (n = 2265); and global (n = 194). The most prominent cluster differences were in the language domain. The global cluster showed earlier and greater developmental delay across domains, unique early gross motor delays, and more were born preterm via cesarean section. The severe cluster had poor language development prominently in the second year of life, and later fine motor delays. Moderate cluster had mainly language delays in the third year of life. The mild cluster mostly passed milestones. EDM clusters differed demographically, with higher socioeconomic status in mild cluster and lowest in global cluster. However, the severe cluster had more immigrant and non-Jewish mothers followed by the moderate cluster. The rates of parental concerns and provider developmental referrals were significantly higher in the global, followed by the severe, moderate, and mild EDM clusters. Autistic children's language and motor delay in the first 3?years can be grouped by common magnitude and onset profiles as distinct groups that may link to specific etiologies (like prematurity or genetics) and specific intervention programs. Early autism screening should be tailored to these different developmental profiles. En ligne : https://doi.org/10.1002/aur.3177 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=533 [article] Early developmental milestone clusters of autistic children based on electronic health records [Texte imprimé et/ou numérique] / Joshua GUEDALIA, Auteur ; Keren ILAN, Auteur ; Galit SHEFER, Auteur ; Roe COHEN, Auteur ; Lidia V. GABIS, Auteur . - p.1616-1627. Langues : Anglais (eng) in Autism Research > 17-8 (August 2024) . - p.1616-1627 Index. décimale : PER Périodiques Résumé : Abstract Autistic children vary in symptoms, co-morbidities, and response to interventions. This study aimed to identify clusters of autistic children with a distinct pattern of attaining early developmental milestones (EDMs). The clustering of 5836 autistic children was based on the attainment of 43 gross motor, fine motor, language, and social developmental milestones during the first 3?years of life as recorded in baby wellness visits. K-means cluster analysis detected four EDM clusters: mild (n = 1686); moderate (n = 1691); severe (n = 2265); and global (n = 194). The most prominent cluster differences were in the language domain. The global cluster showed earlier and greater developmental delay across domains, unique early gross motor delays, and more were born preterm via cesarean section. The severe cluster had poor language development prominently in the second year of life, and later fine motor delays. Moderate cluster had mainly language delays in the third year of life. The mild cluster mostly passed milestones. EDM clusters differed demographically, with higher socioeconomic status in mild cluster and lowest in global cluster. However, the severe cluster had more immigrant and non-Jewish mothers followed by the moderate cluster. The rates of parental concerns and provider developmental referrals were significantly higher in the global, followed by the severe, moderate, and mild EDM clusters. Autistic children's language and motor delay in the first 3?years can be grouped by common magnitude and onset profiles as distinct groups that may link to specific etiologies (like prematurity or genetics) and specific intervention programs. Early autism screening should be tailored to these different developmental profiles. En ligne : https://doi.org/10.1002/aur.3177 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=533

Fetal brain growth and infant autistic traits / Ezra AYDIN in Molecular Autism, 15 (2024)  

Public ISBD [article]  inMolecular Autism > 15 (2024) . - 11p. Titre : Fetal brain growth and infant autistic traits Type de document : Texte imprimé et/ou numérique Auteurs : Ezra AYDIN, Auteur ; Alex TSOMPANIDIS, Auteur ; Daren CHAPLIN, Auteur ; Rebecca HAWKES, Auteur ; Carrie ALLISON, Auteur ; Gerald HACKETT, Auteur ; Topun AUSTIN, Auteur ; Egl? PADAIGAIT?, Auteur ; Lidia V. GABIS, Auteur ; John SUCKING, Auteur ; Rosemary HOLT, Auteur ; Simon BARON-COHEN, Auteur Article en page(s) : 11p. Langues : Anglais (eng) Mots-clés : Male  Infant  Pregnancy  Female  Humans  Autistic Disorder/diagnostic imaging  Brain/diagnostic imaging  Gestational Age  Autistic traits  Early brain development  Q-chat  Transcerebellar diameter  Ultrasound Index. décimale : PER Périodiques Résumé : BACKGROUND: Structural differences exist in the brains of autistic individuals. To date only a few studies have explored the relationship between fetal brain growth and later infant autistic traits, and some have used fetal head circumference (HC) as a proxy for brain development. These findings have been inconsistent. Here we investigate whether fetal subregional brain measurements correlate with autistic traits in toddlers. METHODS: A total of 219 singleton pregnancies (104 males and 115 females) were recruited at the Rosie Hospital, Cambridge, UK. 2D ultrasound was performed at 12-, 20- and between 26 and 30 weeks of pregnancy, measuring head circumference (HC), ventricular atrium (VA) and transcerebellar diameter (TCD). A total of 179 infants were followed up at 18-20 months of age and completed the quantitative checklist for autism in toddlers (Q-CHAT) to measure autistic traits. RESULTS: Q-CHAT scores at 18-20 months of age were positively associated with TCD size at 20 weeks and with HC at 28 weeks, in univariate analyses, and in multiple regression models which controlled for sex, maternal age and birth weight. LIMITATIONS: Due to the nature and location of the study, ascertainment bias could also have contributed to the recruitment of volunteer mothers with a higher than typical range of autistic traits and/or with a significant interest in the neurodevelopment of their children. CONCLUSION: Prenatal brain growth is associated with toddler autistic traits and this can be ascertained via ultrasound starting at 20 weeks gestation. En ligne : https://dx.doi.org/10.1186/s13229-024-00586-5 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=538 [article] Fetal brain growth and infant autistic traits [Texte imprimé et/ou numérique] / Ezra AYDIN, Auteur ; Alex TSOMPANIDIS, Auteur ; Daren CHAPLIN, Auteur ; Rebecca HAWKES, Auteur ; Carrie ALLISON, Auteur ; Gerald HACKETT, Auteur ; Topun AUSTIN, Auteur ; Egl? PADAIGAIT?, Auteur ; Lidia V. GABIS, Auteur ; John SUCKING, Auteur ; Rosemary HOLT, Auteur ; Simon BARON-COHEN, Auteur . - 11p. Langues : Anglais (eng) in Molecular Autism > 15 (2024) . - 11p. Mots-clés : Male  Infant  Pregnancy  Female  Humans  Autistic Disorder/diagnostic imaging  Brain/diagnostic imaging  Gestational Age  Autistic traits  Early brain development  Q-chat  Transcerebellar diameter  Ultrasound Index. décimale : PER Périodiques Résumé : BACKGROUND: Structural differences exist in the brains of autistic individuals. To date only a few studies have explored the relationship between fetal brain growth and later infant autistic traits, and some have used fetal head circumference (HC) as a proxy for brain development. These findings have been inconsistent. Here we investigate whether fetal subregional brain measurements correlate with autistic traits in toddlers. METHODS: A total of 219 singleton pregnancies (104 males and 115 females) were recruited at the Rosie Hospital, Cambridge, UK. 2D ultrasound was performed at 12-, 20- and between 26 and 30 weeks of pregnancy, measuring head circumference (HC), ventricular atrium (VA) and transcerebellar diameter (TCD). A total of 179 infants were followed up at 18-20 months of age and completed the quantitative checklist for autism in toddlers (Q-CHAT) to measure autistic traits. RESULTS: Q-CHAT scores at 18-20 months of age were positively associated with TCD size at 20 weeks and with HC at 28 weeks, in univariate analyses, and in multiple regression models which controlled for sex, maternal age and birth weight. LIMITATIONS: Due to the nature and location of the study, ascertainment bias could also have contributed to the recruitment of volunteer mothers with a higher than typical range of autistic traits and/or with a significant interest in the neurodevelopment of their children. CONCLUSION: Prenatal brain growth is associated with toddler autistic traits and this can be ascertained via ultrasound starting at 20 weeks gestation. En ligne : https://dx.doi.org/10.1186/s13229-024-00586-5 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=538

Predicting autism traits from baby wellness records: A machine learning approach / Joshua GUEDALIA ; Keren ILAN ; Meirav SHAHAM ; Galit SHEFER ; Roe COHEN ; Yuval TAMIR ; Lidia V. GABIS in Autism, 28-12 (December 2024)  

Public ISBD [article]  inAutism > 28-12 (December 2024) . - p.3063-3077 Titre : Predicting autism traits from baby wellness records: A machine learning approach Type de document : Texte imprimé et/ou numérique Auteurs : Joshua GUEDALIA, Auteur ; Keren ILAN, Auteur ; Meirav SHAHAM, Auteur ; Galit SHEFER, Auteur ; Roe COHEN, Auteur ; Yuval TAMIR, Auteur ; Lidia V. GABIS, Auteur Article en page(s) : p.3063-3077 Langues : Anglais (eng) Mots-clés : autism spectrum conditions  developmental milestones  electronic health records  machine learning  screening Index. décimale : PER Périodiques Résumé : Early detection of autism spectrum condition is crucial for children to maximally benefit from early intervention. The study examined a machine learning model predicting the increased likelihood for autism from wellness records from 0 to 24?months. The study included 591,989 non-autistic and 12,846 autistic children. A gradient boosting model with a threefold cross-validation and SHAPley additive explanation tool quantified feature importance. The model had an average area under the curve of 0.81 (SD = 0.004). The high-likelihood group detected by the model had a 0.073 autism spectrum condition incidence rate; 3.42-fold more than in the entire cohort (0.02). Sex-specific models had higher specificity (0.81 boys and 0.79 girls) than sensitivity (0.64 boys and 0.66 girls). The common predictors were more parental concerns, older mothers, never nursing, lower initial and higher last weight percentiles, and several delayed milestones. SHAPley additive explanation tool results show common, important predictors in the full sample and separate boys' and girls' models. These included birth, growth, familial, postnatal parameters and delayed language, fine motor, and social milestones from 12 to 24?months. Machine learning algorithms can help detect increased autism signs by relying on the multidimensional data routinely recorded during the first 2 years. Lay abstract Timely identification of autism spectrum conditions is a necessity to enable children to receive the most benefit from early interventions. Emerging technological advancements provide avenues for detecting subtle, early indicators of autism from routinely collected health information. This study tested a model that provides a likelihood score for autism diagnosis from baby wellness visit records collected during the first 2 years of life. It included records of 591,989 non-autistic children and 12,846 children with autism. The model identified two-thirds of the autism spectrum condition group (boys 63% and girls 66%). Sex-specific models had several predictive features in common. These included language development, fine motor skills, and social milestones from visits at 12-24?months, mother?s age, and lower initial growth but higher last growth measurements. Parental concerns about development or hearing impairment were other predictors. The models differed in other growth measurements and birth parameters. These models can support the detection of early signs of autism in girls and boys by using information routinely recorded during the first 2 years of life. En ligne : https://dx.doi.org/10.1177/13623613241253311 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=543 [article] Predicting autism traits from baby wellness records: A machine learning approach [Texte imprimé et/ou numérique] / Joshua GUEDALIA, Auteur ; Keren ILAN, Auteur ; Meirav SHAHAM, Auteur ; Galit SHEFER, Auteur ; Roe COHEN, Auteur ; Yuval TAMIR, Auteur ; Lidia V. GABIS, Auteur . - p.3063-3077. Langues : Anglais (eng) in Autism > 28-12 (December 2024) . - p.3063-3077 Mots-clés : autism spectrum conditions  developmental milestones  electronic health records  machine learning  screening Index. décimale : PER Périodiques Résumé : Early detection of autism spectrum condition is crucial for children to maximally benefit from early intervention. The study examined a machine learning model predicting the increased likelihood for autism from wellness records from 0 to 24?months. The study included 591,989 non-autistic and 12,846 autistic children. A gradient boosting model with a threefold cross-validation and SHAPley additive explanation tool quantified feature importance. The model had an average area under the curve of 0.81 (SD = 0.004). The high-likelihood group detected by the model had a 0.073 autism spectrum condition incidence rate; 3.42-fold more than in the entire cohort (0.02). Sex-specific models had higher specificity (0.81 boys and 0.79 girls) than sensitivity (0.64 boys and 0.66 girls). The common predictors were more parental concerns, older mothers, never nursing, lower initial and higher last weight percentiles, and several delayed milestones. SHAPley additive explanation tool results show common, important predictors in the full sample and separate boys' and girls' models. These included birth, growth, familial, postnatal parameters and delayed language, fine motor, and social milestones from 12 to 24?months. Machine learning algorithms can help detect increased autism signs by relying on the multidimensional data routinely recorded during the first 2 years. Lay abstract Timely identification of autism spectrum conditions is a necessity to enable children to receive the most benefit from early interventions. Emerging technological advancements provide avenues for detecting subtle, early indicators of autism from routinely collected health information. This study tested a model that provides a likelihood score for autism diagnosis from baby wellness visit records collected during the first 2 years of life. It included records of 591,989 non-autistic children and 12,846 children with autism. The model identified two-thirds of the autism spectrum condition group (boys 63% and girls 66%). Sex-specific models had several predictive features in common. These included language development, fine motor skills, and social milestones from visits at 12-24?months, mother?s age, and lower initial growth but higher last growth measurements. Parental concerns about development or hearing impairment were other predictors. The models differed in other growth measurements and birth parameters. These models can support the detection of early signs of autism in girls and boys by using information routinely recorded during the first 2 years of life. En ligne : https://dx.doi.org/10.1177/13623613241253311 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=543

Prolonged auditory brainstem responses in infants with autism / Oren MIRON in Autism Research, 9-6 (June 2016)  

Public ISBD [article]  inAutism Research > 9-6 (June 2016) . - p.689-695 Titre : Prolonged auditory brainstem responses in infants with autism Type de document : Texte imprimé et/ou numérique Auteurs : Oren MIRON, Auteur ; Daphne ARI-EVEN ROTH, Auteur ; Lidia V. GABIS, Auteur ; Yael HENKIN, Auteur ; Shahar SHEFER, Auteur ; Ilan DINSTEIN, Auteur ; Ronny GEVA, Auteur Article en page(s) : p.689-695 Langues : Anglais (eng) Mots-clés : autism spectrum disorder  auditory brainstem response  hearing Index. décimale : PER Périodiques Résumé : Numerous studies have attempted to identify early physiological abnormalities in infants and toddlers who later develop autism spectrum disorder (ASD). One potential measure of early neurophysiology is the auditory brainstem response (ABR), which has been reported to exhibit prolonged latencies in children with ASD. We examined whether prolonged ABR latencies appear in infancy, before the onset of ASD symptoms, and irrespective of hearing thresholds. To determine how early in development these differences appear, we retrospectively examined clinical ABR recordings of infants who were later diagnosed with ASD. Of the 118 children in the participant pool, 48 were excluded due to elevated ABR thresholds, genetic aberrations, or old testing age, leaving a sample of 70 children: 30 of which were tested at 0–3 months, and 40 were tested at toddlerhood (1.5–3.5 years). In the infant group, the ABR wave-V was significantly prolonged in those who later developed ASD as compared with case-matched controls (n?=?30). Classification of infants who later developed ASD and case-matched controls using this measure enabled accurate identification of ASD infants with 80% specificity and 70% sensitivity. In the group of toddlers with ASD, absolute and interpeak latencies were prolonged compared to clinical norms. Findings indicate that ABR latencies are significantly prolonged in infants who are later diagnosed with ASD irrespective of their hearing thresholds; suggesting that abnormal responses might be detected soon after birth. Further research is needed to determine if ABR might be a valid marker for ASD risk. Autism Res 2016, 9: 689–695. © 2015 The Authors Autism Research published by Wiley Periodicals, Inc. on behalf of International Society for Autism Research En ligne : http://dx.doi.org/10.1002/aur.1561 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=290 [article] Prolonged auditory brainstem responses in infants with autism [Texte imprimé et/ou numérique] / Oren MIRON, Auteur ; Daphne ARI-EVEN ROTH, Auteur ; Lidia V. GABIS, Auteur ; Yael HENKIN, Auteur ; Shahar SHEFER, Auteur ; Ilan DINSTEIN, Auteur ; Ronny GEVA, Auteur . - p.689-695. Langues : Anglais (eng) in Autism Research > 9-6 (June 2016) . - p.689-695 Mots-clés : autism spectrum disorder  auditory brainstem response  hearing Index. décimale : PER Périodiques Résumé : Numerous studies have attempted to identify early physiological abnormalities in infants and toddlers who later develop autism spectrum disorder (ASD). One potential measure of early neurophysiology is the auditory brainstem response (ABR), which has been reported to exhibit prolonged latencies in children with ASD. We examined whether prolonged ABR latencies appear in infancy, before the onset of ASD symptoms, and irrespective of hearing thresholds. To determine how early in development these differences appear, we retrospectively examined clinical ABR recordings of infants who were later diagnosed with ASD. Of the 118 children in the participant pool, 48 were excluded due to elevated ABR thresholds, genetic aberrations, or old testing age, leaving a sample of 70 children: 30 of which were tested at 0–3 months, and 40 were tested at toddlerhood (1.5–3.5 years). In the infant group, the ABR wave-V was significantly prolonged in those who later developed ASD as compared with case-matched controls (n?=?30). Classification of infants who later developed ASD and case-matched controls using this measure enabled accurate identification of ASD infants with 80% specificity and 70% sensitivity. In the group of toddlers with ASD, absolute and interpeak latencies were prolonged compared to clinical norms. Findings indicate that ABR latencies are significantly prolonged in infants who are later diagnosed with ASD irrespective of their hearing thresholds; suggesting that abnormal responses might be detected soon after birth. Further research is needed to determine if ABR might be a valid marker for ASD risk. Autism Res 2016, 9: 689–695. © 2015 The Authors Autism Research published by Wiley Periodicals, Inc. on behalf of International Society for Autism Research En ligne : http://dx.doi.org/10.1002/aur.1561 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=290

A Survey of Out-of-Pocket Expenditures for Children with Autism Spectrum Disorder in Israel / Raanan RAZ in Journal of Autism and Developmental Disorders, 43-10 (October 2013)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 43-10 (October 2013) . - p.2295-2302 Titre : A Survey of Out-of-Pocket Expenditures for Children with Autism Spectrum Disorder in Israel Type de document : Texte imprimé et/ou numérique Auteurs : Raanan RAZ, Auteur ; Liat LERNER-GEVA, Auteur ; Odelia LEON, Auteur ; Gabriel CHODICK, Auteur ; Lidia V. GABIS, Auteur Article en page(s) : p.2295-2302 Langues : Anglais (eng) Mots-clés : Pervasive developmental disorders  Autism spectrum disorders  Health services  Out-of-pocket costs Index. décimale : PER Périodiques Résumé : We describe a survey of children with ASD aged 4–10 years. The main dependent variables were out-of-pocket expenditures for health services and hours of therapy. Multivariable logistic regression models were used in order to find independent predictors for service utilization. Parents of 178 of the children (87 %) agreed to participate. The average annual out-of-pocket cost was 8,288,withamedianof4,473 and a range of $0-89,754. Higher severity of ASD and a parent with an academic degree were associated with higher expenditure. Having at least one older sibling, siblings without developmental disorders, regular education setting, lower parent education and low income were associated with lower expenditure. En ligne : http://dx.doi.org/10.1007/s10803-013-1782-2 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=215 [article] A Survey of Out-of-Pocket Expenditures for Children with Autism Spectrum Disorder in Israel [Texte imprimé et/ou numérique] / Raanan RAZ, Auteur ; Liat LERNER-GEVA, Auteur ; Odelia LEON, Auteur ; Gabriel CHODICK, Auteur ; Lidia V. GABIS, Auteur . - p.2295-2302. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 43-10 (October 2013) . - p.2295-2302 Mots-clés : Pervasive developmental disorders  Autism spectrum disorders  Health services  Out-of-pocket costs Index. décimale : PER Périodiques Résumé : We describe a survey of children with ASD aged 4–10 years. The main dependent variables were out-of-pocket expenditures for health services and hours of therapy. Multivariable logistic regression models were used in order to find independent predictors for service utilization. Parents of 178 of the children (87 %) agreed to participate. The average annual out-of-pocket cost was 8,288,withamedianof4,473 and a range of $0-89,754. Higher severity of ASD and a parent with an academic degree were associated with higher expenditure. Having at least one older sibling, siblings without developmental disorders, regular education setting, lower parent education and low income were associated with lower expenditure. En ligne : http://dx.doi.org/10.1007/s10803-013-1782-2 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=215

Time Trends in Reported Autism Spectrum Disorders in Israel, 1986–2005 / Gilad GAL in Journal of Autism and Developmental Disorders, 42-3 (March 2012)  

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