MétaCan
Menu
Back to cohort
Record W4362691907 · doi:10.1161/strokeaha.122.041965

Plasma Inflammatory Biomarkers Are Associated With Poststroke Cognitive Impairment: The Nor-COAST Study

2023· article· en· W4362691907 on OpenAlexaboutno aff
Heidi Vihovde Sandvig, Stina Aam, Katinka Nordheim Alme, Torunn Askim, Mona K. Beyer, Hanne Ellekjær, Hege Ihle‐Hansen, Stian Lydersen, Tom Eirik Mollnes, Ragnhild Munthe‐Kaas, Halvor Næss, Ingvild Saltvedt, Yngve Müller Seljeseth, Pernille Thingstad, Torgeir Wethal, Anne‐Brita Knapskog

Bibliographic record

VenueStroke · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsnot available
FundersSt. Olavs Hospital Universitetssykehuset i TrondheimHaukeland UniversitetssjukehusNorges ForskningsrådNasjonalforeningen for FolkehelsenNorges Teknisk-Naturvitenskapelige Universitet
KeywordsMedicineMontreal Cognitive AssessmentInternal medicineBiomarkerStroke (engine)Prospective cohort studyCohort studyCohortInflammationCognitive impairmentPhysical therapyDisease

Abstract

fetched live from OpenAlex

Background: Inflammation is proposed to be involved in the pathogenesis of poststroke cognitive impairment. The aim of this study was to investigate associations between concentrations of systemic inflammatory biomarkers after ischemic stroke and poststroke cognitive impairment. Methods: The Nor-COAST study (Norwegian Cognitive Impairment After Stroke) is a prospective observational multicenter cohort study, including patients hospitalized with acute stroke between 2015 and 2017. Inflammatory biomarkers, including the TCC (terminal C5b-9 complement complex) and 20 cytokines, were analyzed in plasma, collected at baseline, 3-, and 18 months poststroke, using ELISA and a multiplex assay. Global cognitive outcome was assessed with the Montreal Cognitive Assessment (MoCA) scale. We investigated the associations between plasma inflammatory biomarkers at baseline and MoCA score at 3-, 18-, and 36-month follow-ups; the associations between inflammatory biomarkers at 3 months and MoCA score at 18- and 36-month follow-ups; and the association between these biomarkers at 18 months and MoCA score at 36-month follow-up. We used mixed linear regression adjusted for age and sex. Results: We included 455 survivors of ischemic stroke. Higher concentrations of 7 baseline biomarkers were significantly associated with lower MoCA score at 36 months; TCC, IL (interleukin)-6, and MIP (macrophage inflammatory protein)-1α were associated with MoCA at 3, 18, and 36 months ( P <0.01). No biomarker at 3 months was significantly associated with MoCA score at either 18 or 36 months, whereas higher concentrations of 3 biomarkers at 18 months were associated with lower MoCA score at 36 months ( P <0.01). TCC at baseline and IL-6 and MIP-1α measured both at baseline and 18 months were particularly strongly associated with MoCA ( P <0.01). Conclusions: Higher concentrations of plasma inflammatory biomarkers were associated with lower MoCA scores up to 36 months poststroke. This was most pronounced for inflammatory biomarkers measured in the acute phase following stroke. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02650531.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.027
GPT teacher head0.253
Teacher spread0.226 · 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

Citations37
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueStrokeSame topicNeuroinflammation and Neurodegeneration MechanismsFrench-language works237,207