Study design and setting
This longitudinal study utilized a cohort of Indonesian post-COVID-19 patients recruited since September 2021 and extracted in January 2023. Participants with a history of COVID-19 were followed up for residual symptoms. We assessed cognitive function 6months after diagnosis and their first symptoms through an online submission system, and this platform was disseminated to the entire country through social media, health care providers, and survivor groups.
Subjects with previous COVID-19 infection (at least thirty days from the onset or diagnosis) were diagnosed using either Indonesian Food and Drug Administration-approved antigen test for the anterior nasal sample (sensitivity over 80%)11 or real-time polymerase chain reaction (RT-PCR) of the nasopharyngeal, nasal, or pooled samples12. These procedures were performed by trained staff, as the self-administered antigen test was not recognized during the study period. This study covered all types of patients, from asymptomatic to hospitalized. After the provision of consent given by the participants, a follow-up cognitive assessment was made, and those without responses of expected outcomes were omitted. Aside from having self-reported mental illness and stroke, there is no other exclusion or limit for those with specific morbidities, age, and digital literacy. Moreover, the snowball sampling approach recruited more individuals to this cohort.
Demographic characteristics, health behaviour, chronic diseases, and other comorbidities were the baseline information covered in the questionnaire. Additionally, this study recorded the latest COVID-19 episode, including date and diagnostic methods, duration of symptoms, type of medication, vaccination status, type of vaccine, and time between doses. Investigators also identified the date from vaccination to infection and the type of care received (home isolation, hospitalization, or both). These variables may interact with each other and affect the relationship between COVID-19 and cognitive failure.
This study cited the definition of cognitive failure as a cognitive mistake made while performing a task that a person would typically complete successfully in daily life. Problems with memory, perception, and focus are signs of cognitive failure13.
This study measured the cognitive failure 6months after the COVID-19 infection. Investigators implemented the assessment using a questionnaire that is in proximity to clinical cognitive assessment, the Cognitive Failures Questionnaire (CFQ)(14), consisting of 25 5-Likert scale questions. The responses range from 0 to 4, where a higher number indicates frequent cognitive failure events. The Indonesian version of this questionnaire was derived from a study with a Cronbach alpha value of 0.94214. Furthermore, one study disclosed three domains in the questionnaire which are forgetfulness (related to something known or planned), distractibility (alteration of attention and focus), and false triggering15.
Investigators assessed other residual COVID-19 symptoms and neuropsychiatry conditions to identify the possible contribution of these symptoms to cognitive failure. Investigators evaluated any presence of residual symptoms after the first onset or diagnosis using a set of measurement tools such as the Fatigue Severity Scale (FSS)16 over the past 6months, Generalised-Anxiety Disorder (GAD-7) to screen for recent anxiety and a 10-Likert scale question to identify its incidence over the past two weeks.
Investigators admit that the quality of baseline data was heavily affected by recall bias. Therefore, participants were required to provide the answers based on the observation chart, written source (such as medical records summary), and through the PeduliLindungi application (for data related to testing, vaccinations, and individual information).
Participants might experience reinfection. Hence, only the last episode of COVID-19 should be provided as the response. By applying this approach, the investigators could not examine in detail the previous infection and, possibly, its latent impact on cognitive function.
Investigators knew that robust cognitive assessments such as Cambridge Neuropsychological Test Automated Battery (CANTAB) could provide objective cognitive results. However, the investigators considered the survey exhaustion and other factors affecting the response, such as internet connection and adaptation to the measurement tools. The questionnaire was deemed sufficient to represent the domains tested by these standardized clinical tests.
There is limited information on long-term cognitive situations after COVID-19. However, a study of CFQ application to neurosarcoidosis (a subset of sarcoidosis, a multi-inflammatory systemic disorder) shows a mean score of 45.620.713. Therefore, investigators assumed that the variance of cognitive failure values of COVID-19 survivors is approximately 20.7. Using the equivalence formula from the assumed score, with 5% type 1 error, 90% power of the study, the absolute mean difference between the assumpted mean and sample means of 1, a 5% equivalence limit, and 10% listwise deletion of incomplete response, a total of 5653 participants should be drawn from the cohort.
Several data were presented as discrete variables, including the duration of symptoms and administration of drugs. Moreover, to assume the possible variant, the investigators matched the date of diagnosis with the variant surveillance reports issued by the Ministry of Health according to surveillance week and region. Other continuous data were kept at their original values. Each type of vaccine possesses different efficacy17. Hence an ordinal level of this variable was made, where a higher ordinal level of vaccination means worse vaccination status (unvaccinated) (Supplementary Data 1).
The analysis involved participants with complete responses; hence no imputation and other missing data analysis were undertaken. Descriptive statistics and bivariate analysis of variables were conducted before the final analysis. We performed the structural equation model. First, the whole model was built (Fig.1) and simplified by the trimming approach. The structure of the model consists of exogenous variables, latent variables, and CFQ score as endogenous factors. The assumption was that vaccination, medication, virus variant, and comorbidity might affect the severity of COVID-19 and, eventually, cognitive failure. Aside from COVID-19, demography, chronic fatigue over the past 6months, recent headaches, and anxiety may affect the cognitive situation. The investigators constructed latent variables with confirmatory factor analysis. The selection of the explanatory factors was based on bivariate analysis and model fitting assessed using the Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Standardized Root Mean Square Residual (SRMR), and Root Square Mean Error of Approximation (RMSEA). The Lavaan library in R performed the analysis and produced the final plot.
Proposed Model of Cognitive Failure post-COVID-19. This model comprises four exogenous latent variables (circle variables), and one variable acts as both an exogenous and endogenous latent variable (severity). The final endogenous factor is cognitive failure. Factor loadings of the latent variable are presented with diverging arrows from the latent variable (Recent Headache with six elements. Demography with three factors. Vaccination with two factors. Severity with three factors, and comorbidities with four factors). Converging arrows indicate the impact of the exogenous variable on the endogenous factor.
This study was authorized by the Hasanuddin University Research Ethics Review Committee for Research Involving Human Research Participants (full-board review number 758/UN4.6.4.5.31/PP36/2021). We confirm that all procedures, particularly the clinical data collection, were performed following relevant guidelines and regulations. Informed consent was obtained from all participants when they provided information to the cohort. We appropriately de-identified, stored, and used the data while respecting confidentiality. Any circumstances that needed immediate action were directed to a professional. This research is a subset of a clinical trial with the identifier NCT05060562 on clinicaltrials.gov.
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