Clusters of post-acute COVID-19 symptoms: a latent class analysis across 9 databases and 7 countries (preprint)

Prior evidence has suggested the multisystem symptomatic manifestations of post-acute COVID-19 condition (PCC). Here we conducted a network cluster analysis of 24 WHO proposed symptoms to identify potential latent subclasses of PCC. Individuals with a positive test of or diagnosed with SARS-CoV-2 after 09/2020 and with at least one symptom within ≥ 90 to 365 days following infection were included. Sub-analyses were conducted among people with ≥ 3 different symptoms. Summary characteristics were provided for each cluster. All analyses were conducted separately in 9 databases from 7 countries, including data from primary care, hospitals, national health claims and national health registries, allowing to validate clusters across the different healthcare settings. 787,078 persons with PCC were included. Single-symptom clusters were common across all databases, particularly for joint pain, anxiety, depression and allergy. Complex clusters included anxiety-depression and abdominal-gastrointestinal symptoms. Substantial heterogeneity within and between PCC clusters was seen across healthcare settings. Current definitions of PCC should be critically reviewed to reflect this variety in clinical presentation.

Development of criteria for cognitive dysfunction in post-COVID syndrome: the IC-CoDi-COVID approach (preprint)

Background. We aimed to develop objective criteria for cognitive dysfunction associated with the post-COVID syndrome. Methods. Four hundred and four patients with post-COVID syndrome from two centers were evaluated with comprehensive neuropsychological batteries. The International Classification for Cognitive Disorders in Epilepsy (IC-CoDE) framework was adapted and implemented. A complementary data-driven approach based on unsupervised machine-learning clustering algorithms was also used to evaluate the optimal classification and cutoff points. Results. According to the developed criteria, 41.2% and 17.3% of the sample were classified as having at least one cognitive domain impaired using -1 and -1.5 standard deviations as cutoff points. Attention/processing speed was the most frequently impaired domain. There were no differences in base rates of cognitive impairment between the two centers. Clustering analysis revealed two clusters according to the severity of cognitive impairment, but there was no difference in cognitive profiles. Cognitive impairment was associated with younger age and lower education levels, but not hospitalization. Conclusions. We propose a harmonization of the criteria to define and classify cognitive impairment in the post-COVID syndrome. These criteria may be extrapolated to other neuropsychological batteries and settings, contributing to the diagnosis of cognitive deficits after COVID-19 and facilitating multicenter studies to guide biomarker investigation and therapies.

COVID-19 and Indigenous peoples in Chile: vulnerability to contagion and mortality

This research investigates whether Indigenous Populations are disproportionately vulnerable to COVID-19 infection and deaths in Chile. To answer this question, we use a regression model to analyze data from the Chilean government. Our analysis indicates that municipalities with a higher proportion of Indigenous people evinced higher rates of infection and deaths to COVID-19. Indigenous groups were not only highly affected at the beginning of the coronavirus outbreak;their rate of infection and mortality has increased as the virus has spread to the general population. We argue that the COVID-19 pandemic can have devastating effects on Indigenous communities, mainly because it increases the historically accumulated inequalities and structural racism linked to colonization, neoliberalism, and neo-extractivism in Chile.