Mohammadmersad Ghorbani, Françoise Pousset, Allan Tucker, Stephen Swift, Paola Giunti, Michael Parkinson, David Gilbert, XiaoHui Liu, Annette Payne, Informatics in Medicine Unlocked, 2019, doi:10.1016/j.imu.2019.100266.
This work uses computer aided classification techniques to identify which measures of the disease progression, including accurate determination of the shortest allele repeat length, are the most informative when trying to predict likely disease progression and prognosis. Further we investigate the possibility of a gender difference in the progression of the disease. Our results highlight the importance of accurate determination GAA repeat length in any clinical predictions showing that the number of repeats is the best prognostic tool in FRDA and is strongly linked to the age at onset disease. Further that there are possible gender dependent differences in cardiac measurements recorded from patients of similar age of onset and GAA repeat length.
Thursday, November 21, 2019
Subscribe to:
Posts (Atom)