These changes include structural and functional brain changes as well as connectivity alterations ( Douaud et al., 2022 Planchuelo-Gómez et al., 2022 Voruz et al., 2022). Overall, knowledge of long COVID headache is limited however, interestingly, specific patterns of neuroimaging findings using a mass-univariate approach are continuously being reported in COVID patients. Headache is one of the most disabling symptoms of long COVID, however, there is limited knowledge and currently no consensus about the definition of the syndrome known as long COVID ( Tana et al., 2022). Moreover, some people who recover from acute COVID-19 still exhibit a spectrum of symptoms persisting for weeks and even months, so-called long COVID ( Tana et al., 2022). In addition to respiratory symptoms, headache is one of the most frequent features accompanying COVID-19 and is described by approximately a quarter of patients ( Planchuelo-Gómez et al., 2022). The 2020–2022 period was marked by a severe pandemic due to a novel coronavirus, namely, COVID-19. The identified features suggest that the distinct gray matter changes in the orbitofrontal and medial temporal lobes occurring after COVID, as well as altered thalamic connectivity, are predictive of headache etiology. The edges that classified long COVID patients from primary headache were mainly comprising thalamic connections.Ĭonclusion: The results suggest the potential value of structural MRI-based features for classifying long COVID headaches from primary headaches. The CPM using the structural covariance network achieved an area under the curve of 0.81 (accuracy = 69.5% permutation p = 0.005). The discriminating GM patterns exhibited lower classification weights for long COVID in the orbitofrontal and medial temporal lobes. Results: MVPA correctly classified long COVID patients from primary headache patients, with an area under the curve of 0.73 (accuracy = 63.4% permutation p = 0.001). In addition, connectome-based predictive modeling (CPM) was also performed using a structural covariance network. Multivoxel pattern analysis (MVPA) was applied for disorder-specific predictions of headache etiology based on individual brain structural MRI. Methods: Twenty-three adolescents with long COVID headaches with the persistence of headache for at least 3 months and 23 age- and sex-matched adolescents with primary headaches (migraine, new daily persistent headache, and tension-type headache) were enrolled. In this study, we applied machine learning to assess whether individual adolescents with long COVID can be accurately distinguished from those with primary headaches. Although distinct brain changes have been reported in patients with long COVID, such reported brain changes have not been used for predictions and interpretations in a multivariate manner. Objective: Headache is among the most frequent symptoms after coronavirus disease 2019 (COVID-19), so-called long COVID syndrome. 3Chonnam National University Medical School, Gwangju, Republic of Korea.2Department of Radiology, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Republic of Korea.1Department of Computer Convergence Software, Korea University, Sejong, Republic of Korea.Minhoe Kim 1† Sunkyung Sim 2† Jaeseok Yang 3 Minchul Kim 2*
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