A predictive model for paediatric autism screening.

Autism spectrum disorder is an umbrella term for a group of neurodevelopmental disorders that is associated with impairments to social interaction, communication, and behaviour. Typically, autism spectrum disorder is first detected with a screening tool (e.g. modified checklist for autism in toddlers). However, the interpretation of autism spectrum disorder behavioural symptoms varies across cultures: the sensitivity of modified checklist for autism in toddlers is as low as 25 per cent in Sri Lanka. A culturally sensitive screening tool called pictorial autism assessment schedule has overcome this problem. Low- and middle-income countries have a shortage of mental health specialists, which is a key barrier for obtaining an early autism spectrum disorder diagnosis. Early identification of autism spectrum disorder enables intervention before atypical patterns of behaviour and brain function become established. This article proposes a culturally sensitive autism spectrum disorder screening mobile application. The proposed application embeds an intelligent machine learning model and uses a clinically validated symptom checklist to monitor and detect autism spectrum disorder in low- and middle-income countries for the first time. Machine learning models were trained on clinical pictorial autism assessment schedule data and their predictive performance was evaluated, which demonstrated that the random forest was the optimal classifier (area under the receiver operating characteristic (0.98)) for embedding into the mobile screening tool. In addition, feature selection demonstrated that many pictorial autism assessment schedule questions are redundant and can be removed to optimise the screening process.

Culturally adapted pictorial screening tool for autism spectrum disorder: A new approach.

AIM: To assess the performance of a newly designed, culturally adapted screening tool for autism spectrum disorder (ASD). METHODS: Items for the screening tool were modeled from already documented checklists and diagnostic criteria for ASD. Each item in text was paired with a photograph that illustrated the written content, which was in the 2 main local languages. The final product had 21 items and was named the pictorial autism assessment schedule (PAAS). Performance of PAAS was tested on a clinical sample of 18-48 mo old children, diagnosis naïve, presenting with developmental deficits. Mothers completed PAAS checklist. Based on clinical diagnosis, which was taken as the gold standard, children were later grouped into ASD (Group 1) and non-ASD developmental disorders (Group 2). Mothers of a control sample of typically developing children also completed PAAS (Group 3). RESULTS: A total of 105 children (Group 1-45, Group 2-30, Group 3-30) participated in the study. Mean age of Group 1 and Group 2 were 36 and 40 mo respectively. Majority were male in all 3 groups. Performance of PAAS in discriminating between ASD and non-ASD developmental disorders was sensitivity 88.8%, specificity 60.7%, positive predictive value (PPV) 78.4%, negative predictive value (NPV) 77.2%, likelihood ratio (LR+) 2.26, and LR- 0.18. Performance of PAAS in discriminating between ASD and typical development was sensitivity 88.0%, specificity 93.3%, PPV 95.2%, NPV 84.0%, LR+ 13.3 and LR- 0.12. The results indicated that that a positive result from PAAS was 2.26 times more likely to be found in a child with ASD than in a child with non-ASD developmental disorder. A positive result from PAAS was 13.3 times more likely to be found in a child with ASD than in a child with typical development. CONCLUSION: PAAS is an effective tool in screening for ASD. Further study is indicated to evaluate the feasibility of using this instrument for community screening for ASD.

Antipsychotic-associated weight gain: management strategies and impact on treatment adherence.

Antipsychotic-induced weight gain is a major management problem for clinicians. It has been shown that weight gain and obesity lead to increased cardiovascular and cerebrovascular morbidity and mortality, reduced quality of life and poor drug compliance. This narrative review discusses the propensity of various antipsychotics to cause weight gain, the pharmacologic and nonpharmacologic interventions available to counteract this effect and its impact on adherence. Most antipsychotics cause weight gain. The risk appears to be highest with olanzapine and clozapine. Weight increases rapidly in the initial period after starting antipsychotics. Patients continue to gain weight in the long term. Children appear to be particularly vulnerable to antipsychotic-induced weight gain. Tailoring antipsychotics according to the needs of the individual and close monitoring of weight and other metabolic parameters are the best preventive strategies at the outset. Switching to an agent with lesser tendency to cause weight gain is an option, but carries the risk of relapse of the illness. Nonpharmacologic interventions of dietary counseling, exercise programs and cognitive and behavioral strategies appear to be equally effective in individual and group therapy formats. Both nonpharmacologic prevention and intervention strategies have shown modest effects on weight. Multiple compounds have been investigated as add-on medications to cause weight loss. Metformin has the best evidence in this respect. Burden of side effects needs to be considered when prescribing weight loss medications. There is no strong evidence to recommend routine prescription of add-on medication for weight reduction. Heterogeneity of study methodologies and other confounders such as lifestyle, genetic and illness factors make interpretation of data difficult.

Outcome of Home-Based Early Intervention for Autism in Sri Lanka: Follow-Up of a Cohort and Comparison with a Nonintervention Group.

This paper presents the outcome of a home-based autism intervention program (HBAIP) in 18- to 40-month-old children newly diagnosed and treatment naïve. Intervention was exclusively implemented at home. Outcome was measured at 3 months and 6 months after intervention and compared with a group of newly diagnosed children with autism who were >40 months at intake but had not received any autism specific clinical management. Aim was also to estimate whether natural development would contribute to gain in skills and compare with the effect of intervention. Five selected parameters of behavior representing social interaction and social communication were used to assess outcome. Results showed a statistically significant improvement between preintervention and postintervention in all the measured parameters. The effect size was large when compared to preintervention and gains were indicated by changes in mean scores and p values within a narrow confidence interval. Highest gains were in first 3 months of postintervention which continued up to 6 months. Although the comparison group was more advanced in the measured skills at intake, they were significantly below the level reached by experimental group at 3 months and 6 months after intervention. This study was registered in the Sri Lanka Clinical Trials Registry (SLCTR/2009/011).

Combined ω3 and ω6 supplementation in children with attention-deficit hyperactivity disorder (ADHD) refractory to methylphenidate treatment: a double-blind, placebo-controlled study.

Children (6-12 years) with attention-deficit hyperactivity disorder (ADHD) being treated with methylphenidate and standard behavior therapy for more than 6 months, whose parents reported no improvement in behavior and academic learning, were randomly assigned to receive supplementation with a combined ω3 and ω6 preparation or a placebo. Outcome was measured at 3 and 6 months after treatment using a self-assessment checklist completed by the parents. Statistically significant improvement was found in the treatment group compared with the placebo group (P < .01) in the following measures: restlessness, aggressiveness, completing work, and academic performance. Statistically significant improvement was not found at 3 months of treatment between groups but was evident at 6 months of treatment (P < .05) with inattention, impulsiveness, and cooperation with parents and teachers. Distractibility failed to show improvement. Effect sizes ranged from 0.3 to 1.1 at 3 months and 0.2 to 1.4 at 6 months for individual symptom variables.