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Record W4400987713 · doi:10.1161/strokeaha.123.046117

Plasma Brain-Derived Tau in Prognosis of Large Vessel Occlusion Ischemic Stroke

2024· article· en· W4400987713 on OpenAlexaboutno aff
Ricardo Varela, Fernando González‐Ortiz, Alexandre Dias, Nicoló Luca Knuth, Joana Fonte, Beatriz Pinto, Idil Yuksekel, Vasco Sousa Abreu, Isabel Silva, Liliana Igreja, J Lopes, José Sá Silva, Rafael Dias, João Pedro Filipe, Maria João Malaquias, Ana Moutinho, Denis Gabriel, Ana Aires, Rui Antunes, José Pedro Rocha, Rui Felgueiras, Ricardo Almendra, Pedro Castro, Henrik Zetterberg, Rui Magalhães, Thomas K. Karikari, Manuel Correia, Kaj Blennow, Luı́s F. Maia

Bibliographic record

VenueStroke · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineStroke (engine)Ischemic strokeCardiologyBrain ischemiaOcclusionIschemiaInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Large vessel occlusion acute ischemic stroke prognosis improved following the 2015 endovascular therapy (EVT) trials. Blood-based biomarkers may improve outcome prediction. We aimed to assess plasma brain-derived tau (BD-Tau) performance in predicting post-EVT large vessel occlusion acute ischemic stroke outcomes. METHODS: We included 2 temporally independent prospective cohorts of anterior circulation in patients with large vessel occlusion acute ischemic stroke who successfully recanalized post-EVT. We measured plasma BD-Tau, GFAP (glial-fibrillary-acidic-protein), NfL (neurofilament-light-chain), and total-Tau upon admission, immediately, 24 hours, and 72 hours post-EVT. Twenty-four-hour neuroimaging and 90-day functional outcomes were independently assessed using the Alberta Stroke Program Early Computed Tomography Score (good outcome: >7 or unchanged) and the modified Rankin Scale (favorable outcome <3 or unchanged), respectively. Based on the first cohort (derivation), we built a multivariable logistic regression model to predict a 90-day functional outcome. Model results were evaluated using the second cohort (evaluation). RESULTS: In the derivation cohort (n=78, mean age=72.9 years, 50% women), 62% of patients had a good 24-hour neuroimaging outcome, and 45% had a favorable 90-day functional outcome. GFAP admission-to-EVT rate-of-change was the best predictor for early neuroimaging outcome but not for 90-day functional outcome. At admission, BD-Tau levels presented the highest discriminative performance for 90-day functional outcomes (area under the curve, 0.76 [95% CI, 0.65–0.87]; P <0.001). The model incorporating age, admission BD-Tau, and 24-hour Alberta Stroke Program Early Computed Tomography Score achieved excellent discrimination of 90-day functional outcome (area under the curve, 0.89 [95% CI, 0.82–0.97]; P <0.001). The score’s predictive performance was maintained in the evaluation cohort (n=66; area under the curve, 0.82 [95% CI, 0.71–0.92]; P <0.001). CONCLUSIONS: Admission plasma BD-Tau accurately predicted 90-day functional outcomes in patients with large vessel occlusion acute ischemic stroke after successful EVT. The proposed model may predict functional outcomes using objective measures, minimizing human-related biases and serving as a simplified prognostic tool for AIS.

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)0.004
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.271
Teacher spread0.260 · 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

Citations15
Published2024
Admission routes1
Has abstractyes

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