How Accurately Does the Information on Motor Development Collected During Health Checkups for Infants Predict the Diagnosis of Neurodevelopmental Disorders? – A Bayesian Network Model-Based Study

Abstract

Yuhei Hatakenaka,1– 3 Koutaro Hachiya,4 Shino Ikezoe,5 Jakob Åsberg Johnels,2 Christopher Gillberg2 1Facuty of Humanities and Social Sciences, University of the Ryukyus, Nishihara, Okinawa, Japan; 2Gillberg Neuropsychiatry Centre, Sahlgrenska Academy, Gothenburg, Sweden; 3Kochi Gillberg Neuropsychiatry Centre, Kochi, Japan; 4Graduate School of Environmental Informatics, Teikyo Heisei University, Tokyo, Japan; 5Faculity of Nursing, University of Kochi, Kochi, JapanCorrespondence: Yuhei Hatakenaka, Faculty of Humanities and Social Sciences, University of the Ryukyus, 1, Senbaru, Nishihara, Nakagami-gun, Okinawa, 903-0213, Japan, Tel [phone], Email [email protected]: We investigated to what extent early motor development problems predict a future diagnosis of neurodevelopmental disorders (NDDs)/Early Symptomatic Syndromes Eliciting Neurodevelopmental Examinations (ESSENCE) by using a Bayesian network model (BN).Subjects and methods: Subjects were the children who had participated in the 18- and 36-month checkups in two cities in Japan between April 2014 and March 2015. Their motor development data at the 4-, 10- and 18-month-checkups were collected with ethical consideration. The diagnosis was confirmed at the age of six, after regular assessment in all developmental areas at a neurodevelopmental clinic. The accuracy of prediction of NDD based on posterior probabilities determined using the BN was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). The posterior probability (the optimal cut-off value) yielding the maximum Youden Index (sensitivity + specificity – 1) is determined with the ROC curve, and the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and utility index (UI) were computed.Results: BN models showed associations between early motor items and developmental coordination disorders, borderline intelligence/intellectual disability, and speech and language disorder. The ROC curve for any NDD had an AUC of 0.735. The posterior probability with the maximal Youden Index was 0.138; at the optimal cut-off value, the sensitivity, specificity, PPV, NPV, UI+, and UI- were 0.619, 0.761, 0.250, 0.940, 0.155 and 0.715, respectively.Conclusion: We utilized a novel approach in detailing the associations between certain early motor problems and specific NDDs. We showed that the presence of motor development problems early in development increases the probability of a future diagnosis of any NDD. Still, the sensitivity of early motor development problems as a screening tool was not high enough to be the sole instrument for detecting NDDs. The need for a broad, holistic ESSENCE perspective when looking at the course of motor development problems was stressed.Keywords: early symptomatic syndromes eliciting neurodevelopmental clinical examinations, early screening, child health checkups, receiver operating characteristic, area under the curve, posterior probability

Keywords

• early symptomatic syndromes eliciting neurodevelopmental clinical examinations
• early screening
• child health checkups
• receiver operating characteristic
• area under the curve
• posterior probability