Objective: The mismatch negativity (MMN) is considered as a promising biomarker that can inform future therapeutic studies. However, there is a large variability among patients with first episode psychosis (FEP). Also, most studies report a single electrode site and on comparing case-control group differences. Few have taken advantage of the full wealth of multi-channel EEG signals to examine observable patterns. None, to our knowledge, have used machine learning (ML) approaches to investigate neurophysiological derived subgroups with distinct cognitive and functional outcome characteristics. In this study, we applied ML to empirically stratify individuals into homogeneous subgroups based on multi-channel MMN data. We then characterized the functional, cognitive, and clinical profiles of these neurobiologically derived subgroups. We also explored the underlying low frequency range responses (delta, theta, alpha) during MMN. Methods: Clinical, neurocognitive, functioning data of 33 healthy controls and 20 FEP patients were collected. 90% of the patients had 6-month follow-up data. Neurocognition, social cognition, and functioning measures were assessed using the NCCB Cognitive Battery, the Awareness of Social Inference Test, UCSD Performance-Based Skills Assessment, and Multnomah Community Ability Scale. Symptom severity was collected using the PANSS. MMN amplitude and single-trial derived low frequency activity across 24 frontocentral channels were used as main variables in the ML kmeans clustering analyses.

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Less than one year into the COVID-19 pandemic, over 70 million individuals worldwide have been infected and case counts continue to accelerate, yet the long-term sequelae of COVID-19 are unknown. We leverage ‘augmented curation’ to extract symptoms and signs occurring post – COVID as noted in follow up physician’s notes of COVID-19 patients at the Mayo Clinic who were diagnosed with SARS-CoV-2 infection between March and September 2020, or influenza between 2014 and 2019. We compare the chart prevalence of signs/symptoms and diseases in the 3-to-6 month post-diagnosis vs. 1-to-6 month pre-diagnosis period for each disease, and subsequently compare the observed effect size of each symptom across the two diseases. Relative to post-influenza, we observe a significant increase in the chart prevalence of terms including “depression”, “anxiety”, “obesity”, and “bleeding” in COVID-19 patients under the age of 55. Across all age groups, “nodules” and “cysts” were also significantly increased. These findings compel targeted investigations into what may be persistent neuropsychiatric, pulmonary, metabolic, and coagulopathic phenotypes following SARS-CoV2 infection.