AUTHOR=Alim-Marvasti Ali , Ciocca Matteo , Kuleindiren Narayan , Lin Aaron , Selim Hamzah , Mahmud Mohammad 

TITLE=Subjective brain fog: a four-dimensional characterization in 25,796 participants

JOURNAL=Frontiers in Human Neuroscience

VOLUME=18

YEAR=2024

URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2024.1409250

DOI=10.3389/fnhum.2024.1409250

ISSN=1662-5161

ABSTRACT=<sec id="sec1"><title>Importance</title><p>Brain fog is associated with significant morbidity and reduced productivity and gained increasing attention after COVID-19. However, this subjective state has not been systematically characterised.</p></sec><sec id="sec2"><title>Objective</title><p>To characterise self-reported brain fog.</p></sec><sec id="sec3"><title>Design</title><p>We systematically studied the cross-sectional associations between 29 <italic>a priori</italic> variables with the presence of “brain fog.” The variables were grouped into four categories: demographics, symptoms and functional impairments, comorbidities and potential risk factors (including lifestyle factors), and cognitive score. Univariate methods determined the correlates of brain fog, with long-COVID and non-long-COVID subgroups. XGBoost machine learning model retrospectively characterised subjective brain fog. Bonferroni-corrected statistical significance was set at 5%.</p></sec><sec id="sec4"><title>Setting</title><p>Digital application for remote data collection.</p></sec><sec id="sec5"><title>Participants</title><p>25,796 individuals over the age of 18 who downloaded and completed the application.</p></sec><sec id="sec6"><title>Results</title><p>7,280 of 25,796 individuals (28.2%) reported experiencing brain fog, who were generally older (mean brain fog 35.7 ± 11.9 years vs. 32.8 ± 11.6 years, <italic>p</italic> &lt; 0.0001) and more likely to be female (OR = 1.2, <italic>p</italic> &lt; 0.001). Associated symptoms and functional impairments included d<italic>ifficulty focusing or concentrating</italic> (OR = 3.3), <italic>feeling irritable</italic> (OR = 1.6), <italic>difficulty relaxing</italic> (OR = 1.2, all <italic>p</italic> &lt; 0.0001), <italic>difficulty following conversations</italic> (OR = 2.2), <italic>remembering appointments</italic> (OR = 1.9), <italic>completing paperwork</italic> and performing <italic>mental arithmetic</italic> (ORs = 1.8, all <italic>p</italic> &lt; 0.0001). Comorbidities included long-COVID-19 (OR = 3.8, <italic>p</italic> &lt; 0.0001), concussions (OR = 2.4, <italic>p</italic> &lt; 0.0001), and higher migraine disability assessment scores (MIDAS) (+34.1%, all <italic>p</italic> &lt; 0.0001). Cognitive scores were marginally lower with brain fog (−0.1 std., <italic>p</italic> &lt; 0.001). XGBoost achieved a training accuracy of 85% with cross-validated accuracy of 74%, and the features most predictive of brain fog in the model were difficulty focusing and following conversations, long-COVID, and severity of migraines.</p></sec><sec id="sec7"><title>Conclusions and relevance</title><p>This is the largest study characterising subjective brain fog as an impairment of concentration associated with functional impairments in activities of daily living. Brain fog was particularly associated with a history of long-COVID-19, migraines, concussion, and with 0.1 standard deviations lower cognitive scores, especially on modified Stroop testing, suggesting impairments in the ability to inhibit cognitive interference. Further prospective studies in unselected brain fog sufferers should explore the full spectrum of brain fog symptoms to differentiate it from its associated conditions.</p></sec>