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Record W4388600056 · doi:10.1093/eurheartj/ehad655.467

Neurofilament light chain (NFL) - a neuron-specific plasma biomarker for evaluating risk of ischemic cerebral events in atrial fibrillation

2023· article· en· W4388600056 on OpenAlexaff
Julia Aulin, Karl Sjölin, Johan Lindbäck, Alexander P. Benz, Stuart J. Connolly, John W. Eikelboom, Ziad Hijazi, Jonas Oldgren, Lars Wallentin, Joachim Burman

Bibliographic record

VenueEuropean Heart Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsMedicineAtrial fibrillationInternal medicineInterquartile rangeStroke (engine)CardiologyHazard ratioBiomarkerConfidence intervalBrain ischemiaIschemia

Abstract

fetched live from OpenAlex

Abstract Background A history of ischemic stroke is one of the strongest risk factors for future stroke in patients with atrial fibrillation (AF). Circulating biomarkers specific for the brain may be used to detect overt and covert cerebral ischemia. Neurofilament light chain (NFL) is a neuron-specific cytoskeleton protein that is released into blood at increased levels when the brain is injured and may be a complement to already established risk factors of AF. Purpose We hypothesized that NFL measured in plasma (pNFL) is an independent and incremental risk indicator of ischemic stroke in patients with AF. Methods pNFL was measured in venous blood samples from 1,056 patients with AF randomised to aspirin in the ACTIVE A trial. Samples were collected at randomisation and the median follow-up duration was 3.6 years. pNFL was analysed with a single molecule array. Associations between pNFL and subsequent clinical outcomes were evaluated by Cox-regression models adjusted for fifteen clinical characteristics and NT-proBNP levels. Results The median concentration of pNFL was 17.3 (interquartile range 10.9-28.3) ng/L. The variables most strongly associated with higher pNFL levels were advanced age, renal dysfunction, lower body mass index, prior stroke/transient ischemic attack and female sex. In multivariable analyses, pNFL was a stronger risk indicator for ischemic stroke than any clinical factor, including previous stroke (Figure 2), and of similar prognostic importance as NT-proBNP. pNFL was independently associated with ischemic stroke (per doubling of pNFL, hazard ratio [HR] 1.23, 95% confidence interval [CI] 1.01-1.50, p=0.038), all-cause death (HR 1.30, 95% CI 1.12-1.51, p<0.001) and heart failure (HR 1.30, 95% CI 1.09-1.54, p=0.003) when adjusting for both clinical characteristics and other biomarkers including NT-proBNP. pNFL improved the discriminatory value (c-index) for ischemic stroke from 0.676 to 0.686 (p=0.038) when added to a fully adjusted model including NT-proBNP. Conclusions In patients with AF, pNFL was associated with an increased risk of ischemic stroke, independent of clinical characteristics and NT-proBNP. pNFL was a stronger risk factor for ischemic stroke than previous stroke and of similar prognostic importance as NT-proBNP. pNFL may be a novel plasma biomarker improving the evaluation of the risk of ischemic cerebral events in patients with AF.Stroke risk by pNFL quartile groupVariable importance for ischemic stroke

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)0.002
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.143
GPT teacher head0.374
Teacher spread0.231 · 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
Published2023
Admission routes1
Has abstractyes

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