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Record W4404057638 · doi:10.1371/journal.pone.0312735

Oxygen supplementation and cognitive function in long-COVID

2024· article· en· W4404057638 on OpenAlexaffabout
Christine Gagnon, Thomas Vincent, Louis Bherer, Mathieu Gayda, Simon-Olivier Cloutier, Anna Nozza, Marie‐Claude Guertin, Isabelle Cloutier, Stanislav Glezer, André Denault, Jean‐Claude Tardif

Bibliographic record

VenuePLoS ONE · 2024
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsMontreal Cognitive AssessmentMedicineMemory spanCognitionDigit symbol substitution testVerbal fluency testCrossover studyPhysical therapyAudiologyEffects of sleep deprivation on cognitive performanceInternal medicinePhysical medicine and rehabilitationWorking memoryPlaceboPsychiatryCognitive impairmentNeuropsychologyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Patients can experience persistent cognitive complaints and deficits in long-COVID. Inflammation and capillary damage may contribute to symptoms by interfering with tissue oxygenation. METHODS: This was an exploratory pilot crossover study designed to describe the effects of supplemental oxygen (portable oxygen concentrator, POC) on cognitive performance and peripheral and cerebral oxygen saturation at rest and exercise. Participants with long-COVID (n = 21) were randomized 1:1 to: 1) POC (3h/day) for 2 weeks followed by standard of care (Control) for 2 weeks or 2) Control for 2 weeks then POC (3h/day) for 2 weeks, with a 1-week washout. Cognitive assessment (global cognition [Montreal Cognitive Assessment, MoCA], episodic memory [Hopkins], working memory [Digit Span], executive function [Verbal fluency]) was performed at baseline and after each treatment period. Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder-7 were completed. Peripheral and cerebral oxygen saturation were measured at rest and exercise (treadmill) at baseline and after each treatment period. Statistical analyses were descriptive without formal testing. RESULTS: MoCA scores were similar under POC (26.45±2.31) and Control (26.37±2.85); overall POC-Control difference was -0.090 (95% CI [-1.031, 0.850]). Because of a learning effect, post-hoc analyses were performed for Period 1, where the MoCA score difference was 1.705 [0.140, 3.271]. MoCA subscores suggested better performance with POC for Visuospatial/executive (0.618 [-0.106, 1.342]) and Attention (0.975 [0.207, 1.743]). POC trended to have better scores on Digit Span backward (difference: 0.822 [-0.067, 1.711]) and self-reported depressive symptoms (difference: -1.335 [-3.166, 0.495]). For specific PHQ-9 items, POC tended to have lower (better) scores for Q1 (Little interest/pleasure) and Q7 (Trouble concentrating). Cerebral oxygen saturations at end of exercise showed no difference between POC and Control. Peripheral saturations during exercise were similar under POC and Control (difference: 0.519% [-1.675, 2.714]). CONCLUSION: An advantage of POC over Control was observed for global cognition, attention, visuospatial/executive performance and depressive symptoms. Results need to be validated in a larger study.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.029
GPT teacher head0.302
Teacher spread0.273 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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