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Record W4317786865 · doi:10.1016/j.bbih.2023.100595

Neurocognitive and psychiatric symptoms following infection with COVID-19: Evidence from laboratory and population studies

2023· article· en· W4317786865 on OpenAlexafffund
Peter A. Hall, Hasan Ayaz, Gang Meng, Anna Hudson, Mohammad Nazmus Sakib, Anne C K Quah, Thomas K Agar, Jessica Lee, Christian Boudreau, Geoffrey T. Fong

Bibliographic record

VenueBrain Behavior & Immunity - Health · 2023
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsOntario Institute for Cancer ResearchUniversity of Waterloo
FundersInstitute of Population and Public HealthCanadian Institutes of Health Research
KeywordsNeurocognitivePopulationAnxietyMedicineCognitionClinical psychologyPsychiatryPsychology

Abstract

fetched live from OpenAlex

The objective of the current investigation was to examine associations between symptomatic COVID-19 history, neurocognitive function, and psychiatric symptoms using cognitive task performance, functional brain imaging, and a prospective population survey. Study 1 was a laboratory study conducted between 3 May 2022 and 16 Nov 2022 involving 120 fully vaccinated community dwelling adults between 18 and 84 years of age (Mage = 31.96 (SD = 20.71), 63.3% female). In this cross-sectional study we examined the association between symptomatic COVID-19 infection history and performance on three computer tasks assessing cognitive function (Flanker interference, delay discounting and simple reaction time) and measured oxygen saturation within the prefrontal cortex using functional near infrared spectroscopy (fNIRS). Study 2 was a 2-wave population survey undertaken between 28 September 2021 and 21 March 2022, examining the prospective relationship between symptomatic COVID-19 and self-reported symptoms of cognitive dysfunction, depressive symptoms, anxiety symptoms, and agitation at 6-month follow up. The sample (N = 2,002, Mage = 37.0, SD = 10.4; 60.8% female) was collected using a quota process to ensure equal numbers of vaccinated and unvaccinated individuals. Structural equation modelling with latent variables was performed on the population-level data, evaluating the fit of the proposed mediational model of symptomatic COVID-19 to psychiatric symptoms through cognitive dysfunction. Findings from Study 1 revealed significant effects of symptomatic COVID-19 history on Flanker interference and delay discounting. Effects on flanker performance were significantly stronger among older adult women (effect: 9.603, SE = 4.452, t = 2.157, p = .033), and were accompanied by task-related changes cerebral oxygenation at the right superior frontal gyrus (F (1, 143.1) = 4.729, p = .031). Additionally, those with a symptomatic COVID-19 infection history showed evidence of amplified delay discounting (coefficient = 0.4554, SE = 0.2208, t = 2.0629, p = .041). In Study 2, baseline symptomatic COVID-19 history was associated with self-reported cognitive dysfunction and a latent variable reflecting psychiatric symptoms of anxiety, depression and agitation at follow-up. Mediational analyses revealed evidence of cognitive mediation of clinically significant psychiatric outcomes: depression (indirect effect = 0.077, SE = 0.026, p = .003) and generalized anxiety (indirect effect = 0.060, SE = 0.021, p = .004). Converging findings from laboratory and population survey data support the conclusion that symptomatic COVID-19 infection is associated with task-related, functional imaging and self-reported indices of cognitive dysfunction as well as psychiatric symptoms. In some cases, these findings appear to be more amplified among women than men, and among older women than younger.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.408
Teacher spread0.357 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2023
Admission routes2
Has abstractyes

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