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Browsing by Subject "Long COVID"
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Item A machine learning-based phenotype for long COVID in children: an EHR-based study from the RECOVER program(Cold Spring Harbor Laboratory, 2022-12-26) Lorman, Vitaly; Razzaghi, Hanieh; Song, Xing; Morse, Keith; Utidjian, Levon; Allen, Andrea J.; Rao, Suchitra; Rogerson, Colin; Bennett, Tellen D.; Morizono, Hiroki; Eckrich, Daniel; Jhaveri, Ravi; Huang, Yungui; Ranade, Daksha; Pajor, Nathan; Lee, Grace M.; Forrest, Christopher B.; Bailey, L. Charles; Pediatrics, School of MedicineBackground: As clinical understanding of pediatric Post-Acute Sequelae of SARS CoV-2 (PASC) develops, and hence the clinical definition evolves, it is desirable to have a method to reliably identify patients who are likely to have post-acute sequelae of SARS CoV-2 (PASC) in health systems data. Methods and findings: In this study, we developed and validated a machine learning algorithm to classify which patients have PASC (distinguishing between Multisystem Inflammatory Syndrome in Children (MIS-C) and non-MIS-C variants) from a cohort of patients with positive SARS-CoV-2 test results in pediatric health systems within the PEDSnet EHR network. Patient features included in the model were selected from conditions, procedures, performance of diagnostic testing, and medications using a tree-based scan statistic approach. We used an XGboost model, with hyperparameters selected through cross-validated grid search, and model performance was assessed using 5-fold cross-validation. Model predictions and feature importance were evaluated using Shapley Additive exPlanation (SHAP) values. Conclusions: The model provides a tool for identifying patients with PASC and an approach to characterizing PASC using diagnosis, medication, laboratory, and procedure features in health systems data. Using appropriate threshold settings, the model can be used to identify PASC patients in health systems data at higher precision for inclusion in studies or at higher recall in screening for clinical trials, especially in settings where PASC diagnosis codes are used less frequently or less reliably. Analysis of how specific features contribute to the classification process may assist in gaining a better understanding of features that are associated with PASC diagnoses.Item A Study on the Nature of SARS-CoV-2 Using the Shell Disorder Models: Reproducibility, Evolution, Spread, and Attenuation(MDPI, 2022-09-23) Goh, Gerard Kian-Meng; Dunker, A. Keith; Foster, James A.; Uversky, Vladimir N.; Biochemistry and Molecular Biology, School of MedicineThe basic tenets of the shell disorder model (SDM) as applied to COVID-19 are that the harder outer shell of the virus shell (lower PID-percentage of intrinsic disorder-of the membrane protein M, PIDM) and higher flexibility of the inner shell (higher PID of the nucleocapsid protein N, PIDN) are correlated with the contagiousness and virulence, respectively. M protects the virion from the anti-microbial enzymes in the saliva and mucus. N disorder is associated with the rapid replication of the virus. SDM predictions are supported by two experimental observations. The first observation demonstrated lesser and greater presence of the Omicron particles in the lungs and bronchial tissues, respectively, as there is a greater level of mucus in the bronchi. The other observation revealed that there are lower viral loads in 2017-pangolin-CoV, which is predicted to have similarly low PIDN as Omicron. The abnormally hard M, which is very rarely seen in coronaviruses, arose from the fecal-oral behaviors of pangolins via exposure to buried feces. Pangolins provide an environment for coronavirus (CoV) attenuation, which is seen in Omicron. Phylogenetic study using M shows that COVID-19-related bat-CoVs from Laos and Omicron are clustered in close proximity to pangolin-CoVs, which suggests the recurrence of interspecies transmissions. Hard M may have implications for long COVID-19, with immune systems having difficulty degrading viral proteins/particles.Item Characteristics of Chemosensory Perception in Long COVID and COVID Reinfection(MDPI, 2023-05-22) Jaramillo, Mikki; Thyvalikakath, Thankam P.; Eckert, George; Srinivasan, Mythily; Oral Pathology, Medicine and Radiology, School of DentistryEmerging data suggest an increasing prevalence of persistent symptoms in individuals affected by coronavirus disease-19 (COVID-19). The objective of this study was to determine the relative frequency of altered taste and smell in COVID reinfection (multiple COVID positive tests) and long COVID (one COVID positive test). We sent an electronic survey to patients in the Indiana University Health COVID registry with positive COVID test results, querying if they were experiencing symptoms consistent with long COVID including altered chemosensory perceptions. Among the 225 respondents, a greater long COVID burden and COVID reinfection was observed in women. Joint pain was reported as the most common symptom experienced by 18% of individuals in the long COVID cohort. In the COVID reinfection cohort >20% of individuals reported headache, joint pain, and cough. Taste perception worse than pre-COVID was reported by 29% and 42% of individuals in the long COVID and COVID reinfection cohorts, respectively. Smell perception worse than pre-COVID was reported by 37% and 46% of individuals in long COVID and COVID reinfection cohorts, respectively. Further, Chi-square test suggested significant association between pre-COVID severity of taste/smell perception and headache in both cohorts. Our findings highlight the prevalence of persistent chemosensory dysfunction for two years and longer in long COVID and COVID reinfection.Item Prolonged Gastrointestinal Manifestations After Recovery From COVID-19(Elsevier, 2023) Elmunzer, B. Joseph; Palsson, Olafur S.; Forbes , Nauzer; Zakaria , Ali; Davis, Christian; Canakis, Andrew; Qayed, Emad; Bick, Benjamin; Pawa, Swati; Tierney, William M.; McLeod, Caroline G.; Taylor, Jason; Patel, Harsh; Mendelsohn, Robin B.; Bala, Gokul; Sloan, Ian; Merchant, Ambreen A.; Smith, Zachary L.; Sendzischew Shane, Morgan A.; Aroniadis, Olga C.; Ordiah, Collins O.; Ruddy, Johannah M.; Simren, Magnus; Tack, Jan; Drossman, Douglas; Medicine, School of MedicineBackground & Aims Acute enteric infections are well known to result in long-term gastrointestinal (GI) disorders. Although COVID-19 is principally a respiratory illness, it demonstrates significant GI tropism, possibly predisposing to prolonged gut manifestations. We aimed to examine the long-term GI impact of hospitalization with COVID-19. Methods Nested within a large-scale observational cohort study of patients hospitalized with COVID-19 across North America, we performed a follow-up survey of 530 survivors 12–18 months later to assess for persistent GI symptoms and their severity, and for the development of disorders of gut-brain interaction (DGBIs). Eligible patients were identified at the study site level and surveyed electronically. The survey instrument included the Rome IV Diagnostic Questionnaire for DGBI, a rating scale of 24 COVID-related symptoms, the Gastrointestinal Symptoms Rating Scale, and the Impact of Events–Revised trauma symptom questionnaire (a measure of posttraumatic stress associated with the illness experience). A regression analysis was performed to explore the factors associated with GI symptom severity at follow-up. Results Of the 530 invited patients, 116 responded (52.6% females; mean age, 55.2 years), and 73 of those (60.3%) met criteria for 1 or more Rome IV DGBI at follow-up, higher than the prevalence in the US general population (P < .0001). Among patients who experienced COVID-related GI symptoms during the index hospitalization (abdominal pain, nausea, vomiting, or diarrhea), 42.1% retained at least 1 of these symptoms at follow-up; in comparison, 89.8% of respondents retained any (GI or non-GI) COVID-related symptom. The number of moderate or severe GI symptoms experienced during the initial COVID-19 illness by self-report correlated with the development of DGBI and severity of GI symptoms at follow-up. Posttraumatic stress disorder (Impact of Events–Revised score ≥33) related to the COVID-19 illness experience was identified in 41.4% of respondents and those individuals had higher DGBI prevalence and GI symptom severity. Regression analysis revealed that higher psychological trauma score (Impact of Events–Revised) was the strongest predictor of GI symptom severity at follow-up. Conclusions In this follow-up survey of patients 12–18 months after hospitalization with COVID-19, there was a high prevalence of DGBIs and persistent GI symptoms. Prolonged GI manifestations were associated with the severity of GI symptoms during hospitalization and with the degree of psychological trauma related to the illness experience.