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Lower serum BDNF as a predictor of post-stroke cognitive impairment in acute ischemic stroke patients

2024· preprint· en· W4392601077 on OpenAlexaboutno aff
Ismail Setyopranoto, Astuti Prodjohardjono, Sri Sutarni, Noor Alia Susianti, Muhammad Hardhantyo, Amelia Nur Vidyanti

Bibliographic record

VenueF1000Research · 2024
Typepreprint
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsOpen peer reviewPlant biologyMedicineStroke (engine)Ischemic strokeCognitive impairmentNeurologyInternal medicineCardiologyNeurosciencePsychiatryIschemiaPsychologyDiseaseBiology

Abstract

fetched live from OpenAlex

<ns3:p>Background Reduced level of serum brain-derived neurotrophic factor (BDNF) in acute stroke patients is associated with poor outcomes. We aimed to identify the role of serum BDNF level as a predictor for post-stroke cognitive impairment (PSCI). Methods This was a prospective study. We recruited acute ischemic stroke patients in Dr. Sardjito General Hospital Yogyakarta, Indonesia followed them up for 90 days (3 months). Serum BDNF was collected at day 5 and day 30 of stroke onset and measured by enzyme-linked immunosorbent assay (ELISA). Montreal Cognitive Assessment (MoCA) was used to measure the cognitive function at 90 days of follow up. Receiver operating characteristic (ROC) curve was conducted to measure the cut-off point of the BDNF level. Factors independently associated with PSCI were analyzed by using stepwise regression. Results Among 89 patients recruited, 60 patients (67.41%) developed PSCI. The mean age of PSCI and non-PSCI patients was 62.7 ± 9.5 and 57.5 ± 8.7, respectively (p = 0.01). Patients with dyslipidemia were less likely to develop PSCI (OR 0.10, 95%CI 0.02-0.51, p &lt; 0.05). In addition, patients with day 5-serum BDNF level &lt; 23.29 ng/mL were five times more likely to develop PSCI compared with their counterparts (OR 5.15, 95%CI 1.26-21.09, p &lt; 0.05). Conclusions Among acute ischemic stroke patients, those with serum BDNF &lt;23.29 ng/mL had a higher risk of developing PSCI. This study suggests that BDNF could be a predictor of PSCI, allowing for earlier detection and better preventive strategies.</ns3:p>

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.004
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.028
GPT teacher head0.325
Teacher spread0.297 · 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

Labeled directly by 2 models reading the full record.

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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