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

Purpose 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.

Diagnostic biomarker panels of osteoarthritis: UPLC-QToF/MS-based serum metabolic profiling

“…In addition, logistic regression analysis was simultaneously carried out to integrate these potential biomarkers. And the optimal AUC, sensitivity and specificity were determined using the maximum of the Youden index, which calculated as follows: Youden’s index = sensitivity + specificity − 1 ( Alfitian et al, 2022 ; Hatakenaka et al, 2022 ; Marty et al, 2013 ).…”

Implications of Early Diagnosis and Intervention in the Management of Neurodevelopmental Delay (NDD) in Children: A Systematic Review and Meta-Analysis

“…The forest plot as shown in Figure 2 below provides a clear interpretation of the findings of this study [14][15][16][17][18][19][20][21][22][23][24][25][26]. The columns indicate the included studies, the intervention group, the control group, the weight, and the outcome effect in the numerical and graphical format [27].…”

“…A study identified an algorithm-based mobile application named Malo to effectively diagnose and recognize NDD and post-natal depression (PND) [ 18 ]. Also, a model-based study proposed using the Bayesian network (BN) model to predict early motor development problems for delayed children [ 19 ]. An essential factor identified in the quest to manage NDD in children is the use of mathematical models and machine learning algorithms to create models and applications that help the children navigate the physical and emotional environment depending on the nature of NDD.…”

“…Figure 3 provides a negative risk difference, meaning that early intervention and diagnosis reduced the risk of severe NDDs in children [14][15][16][17][18][19][20][21][22][23][24][25][26]. In other words, a negative risk difference means that it was easy to manage NDD children following early intervention and diagnosis.…”