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Record W4406209247 · doi:10.1002/alz.091969

Brain Glucose Metabolism Changes in Long‐COVID: A Brazilian Cohort Study

2024· article· en· W4406209247 on OpenAlexaff
Maiele Dornelles Silveira, Luiza Santos Machado, João Pedro Ferrari‐Souza, Marco Antônio De Bastiani, Guilherme Povala, Wyllians Vendramini Borelli, Joana Emilia Senger, Ana Paula Bornes da Silva, Guilherme Arantes Mello, João Pedro Uglione da Ros, Arthur Viana Jotz, Matheus Fakhri Kadan, Tharick A. Pascoal, Pedro Rosa‐Neto, Artur Francisco Schumacher Schuh, Cristina Sebastião Matushita, Graciane Radaelli, Mychael V. Lourenco, Ricardo Bernardi Soder, Artur Martins Coutinho, Daniele de Paula Faria, Jaderson Costa da Costa, Diogo O. Souza, Débora Guerini de Souza, Eduardo R. Zimmer

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsMcGill University
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)CohortCarbohydrate metabolismCohort studySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MedicineMetabolism2019-20 coronavirus outbreakInternal medicinePhysiologyVirologyDiseaseOutbreak

Abstract

fetched live from OpenAlex

Abstract Background The COVID‐19 pandemic is a public health crisis, and its lasting consequences are not yet fully understood. Epidemiological data suggest that low‐ and middle‐income countries, such as Brazil, will bear a considerable burden of COVID‐19‐related comorbidities. Individuals who have survived COVID‐19 often report persistent symptoms, including neurological manifestations such as brain fog. However, the underlying brain biological changes behind the neurological symptoms remain undefined. Here, our goal was to assess the influence of long‐COVID on brain metabolism in adults from a Brazilian cohort. Method Brazilian individuals (n=49) were recruited, examined through clinical and neuropsychological assessments, and divided into Control and Long‐COVID groups. Then, they underwent a brain [18F]FDG‐PET scan. Images were normalized by the global mean. Differences between groups were assessed through a [18F]FDG‐PET voxel‐wise linear regression accounting for age, sex and years of education (Table 1). The analysis was corrected for multiple comparisons using the cluster‐wise random field theory method (significant t < ‐3.28 and t > 3.28). Result Long‐COVID group exhibited recurring symptoms such as fatigue, memory complaints and lack of concentration (Table 1). They also exhibited hypometabolic clusters in the left superior parietal lobe (tmax=‐4.03; p < 0.001) and right insular cortex (tmax=‐3.31; p < 0.001) (Figure 1). Hypermetabolic clusters were found in the left whole cerebellum (tmax=4.92; p < 0.0001), right dorsolateral prefrontal cortex (tmax=3.83; p < 0.001), and right postcentral gyrus (tmax=4.24; p < 0.001) (Figure 2). Conclusion Our preliminary results demonstrate region‐dependent dual response on brain metabolism due to Long‐Covid. More specifically, glucose hypometabolism was found in regions associated with cognitive domains and affective modulation. By contrast, glucose hypermetabolism was observed in brain areas associated with motor coordination and sensory processing. Metabolic changes in these regions should be further evaluated to advance in the understanding of the pathophysiological mechanisms associated with persistent neurological manifestations seen in individuals presenting with Long COVID.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.320
Teacher spread0.303 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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