Browsing by Author "Dahanayake, D. M. A."

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Open Access
Diagnosing autism in low‐income countries: Clinical record‐based analysis in Sri Lanka
(Wily, 2022-06-16) Samarasinghe, P; Wickramarachchi, C; Peiris, H; Vance, P; Dahanayake, D. M. A.; Kulasekara, V; Nadeeshani, M
Use of autism diagnosing standards in low-income countries (LICs) are restricted due to the high price and unavailability of trained health professionals. Furthermore, these standards are heavily skewed towards developed countries and LICs are underrepresented. Due to such constraints, many LICs use their own ways of assessing autism. This is the first retrospective study to analyze such local practices in Sri Lanka. The study was conducted at Ward 19B of Lady Ridgeway Hospital (LRH) using the clinical forms filled for diagnosing ASD. In this study, 356 records were analyzed, from which 79.5% were boys and the median age was 33 months. For each child, the clinical form together with the Childhood Autism Rating Scale (CARS) value were recorded. In this study, a Clinically Derived Autism Score (CDAS) is obtained from the clinical forms. Scatter plot and Pearson product moment correlation coefficient were used to benchmark CDAS with CARS, and it was found CDAS to be positively and moderately correlated with CARS. In identifying the significant variables, a logistic regression model was built based on clinically observed data and it evidenced that “Eye Contact,” “Interaction with Others,” “Pointing,” “Flapping of Hands,” “Request for Needs,” “Rotate Wheels,” and “Line up Things” variables as the most significant variables in diagnosing autism. Based on these significant predictors, the classification tree was built. The pruned tree depicts a set of rules, which could be used in similar clinical environments to screen for autism.