Foetal Alcohol Spectrum Disorder (FASD) diagnostic guidelines: a neuropsychological diagnostic criteria review proposal

Bastons-Compta, Adriana; Astals, Marta; Garcı́a-Algar, Óscar

doi:10.4172/2472-095x.1000e104

Cited by 5 publications

(4 citation statements)

References 16 publications

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“…Our study showed that FASD patients share a common profile of maternal alcohol consumption, low height and lip-philtrum affectation (Hoyme et al, 2016 ). FAS profile shows impaired intelligence domains observed in WISC V test, as previously reported (Bastons-Compta et al, 2016 ). Prematurity, growth retardation, weight affectation, short palpebral fissures, eyes and upper limbs affectation and attention problems are highlighted in FAS profile compared to non-FASD, being part of the specific diagnosis (Hoyme et al, 2016 ; Wang et al, 2020 ).…”

Section: Discussionsupporting

confidence: 86%

“…These domains create a spectrum from the most severe condition of FASD, the fetal alcohol syndrome (FAS) to alcohol-related brain damage (ARBD), with partial FAS (pFAS) and alcohol-related neurodevelopmental disorder (ARND) as intermediate terms. Several guidelines are commonly used, including those from the Institute of Medicine, Canadian Guidelines, Centers for Disease Control (CDC), and the University of Washington's 4-digit code (Bastons-Compta et al, 2016 ; Maya-Enero et al, 2021 ). The Institute of Medicine (IOM) criteria, which include craniofacial anomalies, growth retardation, mental disabilities and developmental disorders, are currently recommended for diagnosis (Hoyme et al, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

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Machine learning algorithms to the early diagnosis of fetal alcohol spectrum disorders

Ramos-Triguero,

Navarro-Tapia,

Vieiros

et al. 2024

Front. Neurosci.

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IntroductionFetal alcohol spectrum disorders include a variety of physical and neurocognitive disorders caused by prenatal alcohol exposure. Although their overall prevalence is around 0.77%, FASD remains underdiagnosed and little known, partly due to the complexity of their diagnosis, which shares some symptoms with other pathologies such as autism spectrum, depression or hyperactivity disorders.MethodsThis study included 73 control and 158 patients diagnosed with FASD. Variables selected were based on IOM classification from 2016, including sociodemographic, clinical, and psychological characteristics. Statistical analysis included Kruskal-Wallis test for quantitative factors, Chi-square test for qualitative variables, and Machine Learning (ML) algorithms for predictions.ResultsThis study explores the application ML in diagnosing FASD and its subtypes: Fetal Alcohol Syndrome (FAS), partial FAS (pFAS), and Alcohol-Related Neurodevelopmental Disorder (ARND). ML constructed a profile for FASD based on socio-demographic, clinical, and psychological data from children with FASD compared to a control group. Random Forest (RF) model was the most efficient for predicting FASD, achieving the highest metrics in accuracy (0.92), precision (0.96), sensitivity (0.92), F1 Score (0.94), specificity (0.92), and AUC (0.92). For FAS, XGBoost model obtained the highest accuracy (0.94), precision (0.91), sensitivity (0.91), F1 Score (0.91), specificity (0.96), and AUC (0.93). In the case of pFAS, RF model showed its effectiveness, with high levels of accuracy (0.90), precision (0.86), sensitivity (0.96), F1 Score (0.91), specificity (0.83), and AUC (0.90). For ARND, RF model obtained the best levels of accuracy (0.87), precision (0.76), sensitivity (0.93), F1 Score (0.84), specificity (0.83), and AUC (0.88). Our study identified key variables for efficient FASD screening, including traditional clinical characteristics like maternal alcohol consumption, lip-philtrum, microcephaly, height and weight impairment, as well as neuropsychological variables such as the Working Memory Index (WMI), aggressive behavior, IQ, somatic complaints, and depressive problems.DiscussionOur findings emphasize the importance of ML analyses for early diagnoses of FASD, allowing a better understanding of FASD subtypes to potentially improve clinical practice and avoid misdiagnosis.

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Section: Discussionsupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Machine learning algorithms to the early diagnosis of fetal alcohol spectrum disorders

Ramos-Triguero,

Navarro-Tapia,

Vieiros

et al. 2024

Front. Neurosci.

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“…Until very recently, the specific domains of function to be evaluated during the neurodevelopmental assessment have been relatively undefined and have lacked consensus [ 12 ]. The diagnostic guidelines have had a tendency to focus on the severity of the neurodevelopmental impairments rather than the specificity of the impairments.…”

Section: Introductionmentioning

confidence: 99%

Neurodevelopmental profile of Fetal Alcohol Spectrum Disorder: A systematic review

et al. 2017

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BackgroundIn an effort to improve the screening and diagnosis of individuals with Fetal Alcohol Spectrum Disorder (FASD), research has focused on the identification of a unique neurodevelopmental profile characteristic of this population. The objective of this review was to identify any existing neurodevelopmental profiles of FASD and review their classification function in order to identify gaps and limitations of the current literature.MethodsA systematic search for studies published up to the end of December 2016 reporting an identified neurodevelopmental profile of FASD was conducted using multiple electronic bibliographic databases. The search was not limited geographically or by language of publication. Original research published in a peer-reviewed journal that involved the evaluation of the classification function of an identified neurodevelopmental profile of FASD was included.ResultsTwo approaches have been taken to determine the pathognomonic neurodevelopmental features of FASD, namely the utilization of i) behavioral observations/ratings by parents/caregivers and ii) subtest scores from standardized test batteries assessing a variety of neurodevelopmental domains. Both approaches show some promise, with the former approach (which is dominated by research on the Neurobehavioral Screening Tool) having good sensitivity (63% to 98%), but varying specificity (42% to 100%), and the latter approach having good specificity (72% to 96%), but varying sensitivity (60% to 88%).ConclusionsThe current review revealed that research in this area remains limited and a definitive neurodevelopmental profile of FASD has not been established. However, the identification of a neurodevelopmental profile will aid in the accurate identification of individuals with FASD, by adding to the armamentarium of clinicians. The full review protocol is available in PROSPERO (http://www.crd.york.ac.uk/PROSPERO/); registration number CRD42016039326; registered 20 May 2016.

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“…Within the spectrum of FASD profiles, Jaime presents FAS, which is the most severe form (Bastons-Compta et al 2016). Children with FAS exhibit deficits that include language disorder, attention deficit, learning difficulties, and impaired motor skills (Wilczyński and Jabłońska 2016;Williams and Smith 2015).…”

Section: Discussionmentioning

confidence: 99%

Language Development Disorder in Fetal Alcohol Spectrum Disorders (FASD), a Case Study

2020

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Prenatal alcohol exposure can cause developmental damage in children. There are different types and ranges of alterations that fall under the name of fetal alcohol spectrum disorders (FASD). Disabilities in learning, cognition, and behavior are observed. Environmental conditions are an influencing factor in this population since they are generally adverse and are either not diagnosed at an early stage or given the appropriate support and approach. We present a case study of a 9-year-old child, in which all the variables affecting his development (FASD diagnosis and socioenvironmental conditions) were observed and analyzed. His early childhood under institutional care, the move to a foster home at the age of 6, and several measures of evaluation from foster care to the present are described. Difficulties in vocabulary, access to vocabulary, morphology, syntax, grammar, oral narrative, pragmatics, speech, and communication were observed, along with cognitive difficulties in memory, perception and executive functioning, social adaptation, learning, and behavior. An early diagnosis and approach enable this population to develop skills in different dimensions to address early adversity despite their neurological and behavioral commitment. Speech-language pathologist services are crucial for the diagnosis and treatment of the language and communication difficulties that characterize this syndrome.

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Foetal Alcohol Spectrum Disorder (FASD) diagnostic guidelines: a neuropsychological diagnostic criteria review proposal

Cited by 5 publications

References 16 publications

Machine learning algorithms to the early diagnosis of fetal alcohol spectrum disorders

Machine learning algorithms to the early diagnosis of fetal alcohol spectrum disorders

Neurodevelopmental profile of Fetal Alcohol Spectrum Disorder: A systematic review

Language Development Disorder in Fetal Alcohol Spectrum Disorders (FASD), a Case Study

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