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Record W4390976851 · doi:10.1161/strokeaha.123.044698

High-Serum Brain-Derived Neurotrophic Factor Levels Are Associated With Decreased Risk of Poststroke Cognitive Impairment

2024· article· en· W4390976851 on OpenAlexaboutno aff
Xinyue Chang, Jiaxing You, Pinni Yang, Yu He, Yi Liu, Mengyao Shi, Daoxia Guo, Yanbo Peng, Jing Chen, Aili Wang, Tan Xu, Jiang He, Yonghong Zhang, Zhengbao Zhu

Bibliographic record

VenueStroke · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineConfoundingBrain-derived neurotrophic factorMontreal Cognitive AssessmentMini–Mental State ExaminationOdds ratioStroke (engine)Logistic regressionRisk factorEffects of sleep deprivation on cognitive performanceNeurotrophic factorsCognitionPhysical therapyCognitive impairmentPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: BDNF (brain-derived neurotrophic factor) is widely implicated in the pathophysiological process of stroke, but the effect of BDNF on poststroke cognitive impairment (PSCI) remains unclear. We aimed to investigate the association between baseline serum BDNF and the risk of PSCI at 3 months in a multicenter study based on a preplanned ancillary study of the CATIS trial (China Antihypertensive Trial in Acute Ischemic Stroke). METHODS: We examined serum BDNF levels at baseline and used the Mini-Mental State Examination and Montreal Cognitive Assessment to evaluate cognitive function at 3-month follow-up after ischemic stroke. PSCI was defined as Mini-Mental State Examination score <27 or Montreal Cognitive Assessment score <25. Logistic regression analyses were performed to evaluate the association between serum BDNF and the risk of 3-month PSCI. RESULTS: In this ancillary study, a total of 660 patients with ischemic stroke with hypertension were included, and 593 patients (mean age, 59.90±10.44 years; 410 males and 183 females) were finally included in this analysis. According to mini-mental state examination score, after adjustment for age, sex, education, baseline National Institutes of Health Stroke Scale score, APOE ɛ4 carriers, and other potential confounders, the odds ratio of PSCI for the highest tertile of BDNF was 0.60 ([95% CI, 0.39–0.94]; P =0.024) compared with the lowest tertile. Multiple-adjusted spline regression model showed a linear association of serum BDNF levels with PSCI at 3 months ( P value for linearity=0.010). Adding serum BDNF to conventional prognostic factors slightly improved the risk reclassification of PSCI (net reclassification improvement: 27.46%, P =0.001; integrated discrimination index: 1.02%, P =0.015). Similar significant findings were observed when PSCI was defined by the Montreal Cognitive Assessment score. CONCLUSIONS: Elevated serum BDNF levels were associated with a decreased risk of PSCI at 3 months, suggesting that serum BDNF might be a potential predictive biomarker for PSCI among patients with ischemic stroke with hypertension.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.261
Teacher spread0.235 · 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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