Impacts of metabolic disruption, body mass index and inflammation on cognitive function in post-COVID-19 condition: a randomized controlled trial on vortioxetine
Bibliographic record
Abstract
BACKGROUND: Post-COVID-19 Condition (PCC), as defined by the World Health Organization (WHO), currently lacks any regulatory-approved treatments and is characterized by persistent and debilitating cognitive impairment and mood symptoms. Additionally, metabolic dysfunction, chronic inflammation and the associated risks of elevated body mass index (BMI) have been reported. In this study, we aim to investigate the efficacy of vortioxetine in improving cognitive deficits in individuals with PCC, accounting for the interaction of metabolic dysfunction, elevated inflammation and BMI. METHODS: This is a post-hoc analysis of an 8-week randomized, double-blind, placebo-controlled trial that was conducted among adults aged 18 years and older living in Canada who were experiencing WHO-defined PCC symptoms. The recruitment of participants began in November 2021 and concluded in January 2023. A total of 200 individuals were enrolled, where 147 were randomized in a 1:1 ratio to receive either vortioxetine (5-20 mg, n = 73) or placebo (n = 74) for daily treatment under double-blind conditions. The primary outcome measure was the change in the Digit Symbol Substitution Test (DSST) score from baseline to endpoint. RESULTS: = 11.967, p = 0.018) on cognitive function. Moreover, the between-group analysis showed a significant improvement with vortioxetine at endpoint (mean difference = 0.621, SEM = 0.313, p = 0.047). CONCLUSION: Overall, vortioxetine demonstrated significant improvements in cognitive deficits among individuals with baseline markers of metabolic dysfunction, elevated inflammation and higher BMI at endpoint as compared to placebo. TRIAL REGISTRATION: NCT05047952 (ClinicalTrials.gov; Registration Date: September 17, 2021).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".