COVCOG 1: Factors Predicting Physical, Neurological and Cognitive Symptoms in Long COVID in a Community Sample. A First Publication From the COVID and Cognition Study
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Abstract
Since its first emergence in December 2019, coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has evolved into a global pandemic. Whilst often considered a respiratory disease, a large proportion of COVID-19 patients report neurological symptoms, and there is accumulating evidence for neural damage in some individuals, with recent studies suggesting loss of gray matter in multiple regions, particularly in the left hemisphere. There are a number of mechanisms by which COVID-19 infection may lead to neurological symptoms and structural and functional changes in the brain, and it is reasonable to expect that many of these may translate into cognitive problems. Indeed, cognitive problems are one of the most commonly reported symptoms in those experiencing “Long COVID”—the chronic illness following COVID-19 infection that affects between 10 and 25% of patients. The COVID and Cognition Study is a part cross-sectional, part longitudinal, study documenting and aiming to understand the cognitive problems in Long COVID. In this first paper from the study, we document the characteristics of our sample of 181 individuals who had experienced COVID-19 infection, and 185 who had not. We explore which factors may be predictive of ongoing symptoms and their severity, as well as conducting an in-depth analysis of symptom profiles. Finally, we explore which factors predict the presence and severity of cognitive symptoms, both throughout the ongoing illness and at the time of testing. The main finding from this first analysis is that that severity of initial illness is a significant predictor of the presence and severity of ongoing symptoms, and that some symptoms during the initial illness—particularly limb weakness—may be more common in those that have more severe ongoing symptoms. Symptom profiles can be well described in terms of 5 or 6 factors, reflecting the variety of this highly heterogenous condition experienced by the individual. Specifically, we found that neurological/psychiatric and fatigue/mixed symptoms during the initial illness, and that neurological, gastrointestinal, and cardiopulmonary/fatigue symptoms during the ongoing illness, predicted experience of cognitive symptoms.
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SciScore for 10.1101/2021.10.26.21265525: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics Consent: Informed consent to use of anonymized data was obtained prior to starting.
IRB: 2.2 Procedure: The study was reviewed and a favorable ethics opinion was granted by University of Cambridge Department of Psychology ethics committee (PRE.2020.106, 8/9/2020).Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources 2.3 Data Processing and Analysis: Analyses were conducted using IBM SPSS Statistics for Windows, Version 23.0. SPSSsuggested: (SPSS, RRID:SCR_002865)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to …
SciScore for 10.1101/2021.10.26.21265525: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics Consent: Informed consent to use of anonymized data was obtained prior to starting.
IRB: 2.2 Procedure: The study was reviewed and a favorable ethics opinion was granted by University of Cambridge Department of Psychology ethics committee (PRE.2020.106, 8/9/2020).Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources 2.3 Data Processing and Analysis: Analyses were conducted using IBM SPSS Statistics for Windows, Version 23.0. SPSSsuggested: (SPSS, RRID:SCR_002865)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:4.3 Strengths, Limitations and Future Research: While the findings of this study are notable, there are a number of limitations in design and execution which warrant caution in interpreting the results. First, this was an online study. Using online data-collection means that we are less able to maximize data quality by ensuring that participants were in a suitable environment or concentrating properly on the questionnaires. We were also not able to clinically assess participants, nor did we have access to medical records. This means that we were reliant on retrospective self-report for symptoms and diagnoses experienced sometimes months previously. In an attempt to reflect the feedback that we received from support groups during qualitative scoping, we used a slightly different symptom list when individuals were reporting on initial symptoms rather than ongoing symptoms, and the latter also had a greater range of possible values (reflecting both severity and regularity). This made it difficult to directly compare symptom profiles at the different time points, and future studies should consider using the same symptom list and reporting method for all time points, even if some symptoms are unlikely to appear at a given stage of illness. We also used a binary present/absent reporting approach for currently experienced symptoms, which was not able to reflect severity—this should also be addressed in future studies. To look at symptom profiles in terms of current symptoms, we used...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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