RT Journal Article
SR Electronic
T1 Predictive Modelling of The Dynamic Patterns of Thinking in Attention-Deficit/Hyperactivity Disorder: Diagnostic Accuracy of Spatiotemporal Fractal Measures
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 420513
DO 10.1101/420513
A1 F. Labra-Spröhnle
A1 G. Smith
A1 H. Ahammer
A1 C. Postlethwaite
A1 I. Liu
A1 P. Teesdale-Spittle
A1 M. Frean
YR 2018
UL http://biorxiv.org/content/early/2018/09/20/420513.abstract
AB Background Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental condition characterized by executive function (EF) dynamics disturbances. Notwithstanding, current advances in translational neuroscience, no ADHD objective, clinically useful, diagnostic marker is available to date.Objectives Using a customized definition of EF and a new clinical paradigm, we performed a prospective diagnostic accuracy trial to assess the diagnostic value of several fractal measures from the thinking processes or inferences in a cohort of ADHD children and typically developing controls.Method We included children from age five to twelve diagnosed with a reference standard based on case history, physical and neurological examination, Conners 3rd Edition, and DSM-V™. The index test consisted of a computer-based inference task with a set of eight different instances of the “Battleships” game to be solved. A consecutive series of 18 cases and 18 controls (n = 36) recruited at the primary paediatrics service from the Nelson Marlborough Health in New Zealand underwent the reference standard and the index test. Several fractal measures were obtained from the inference task to produce supervised classification models.Results Notably, the summarized logistic regression’s predicted probabilities from the eight games played by each children yielded a 100% classification accuracy, sensitivity and specificity in both a training and an independent testing/validating cohort.Conclusions From a translational vantage point the expeditious method and the robust results make this technique a promising candidate to develop a screening, diagnostic and monitoring system for ADHD, and may serve to assess other EF disturbances.