MétaCan
Menu
← Back to cohort
Record W3207702179

The Significance of Interleukin-6 and Tumor Necrosis Factor-Alpha Levels in Cognitive Impairment among First-Ever Acute Ischaemic Stroke Patients.

2021· article· en· W3207702179 on OpenAlexaboutno aff
Nataša Loga-Andrijić, Novica T Petrović, Snežana Filipović-Danić, Snežana Marjanović, Vekoslav Mitrović, Svjetlana Loga-Zec

Bibliographic record

VenuePubMed · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMontreal Cognitive AssessmentStroke (engine)NeurologyInternal medicineCognitionCognitive impairmentPhysical therapyPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Acute ischemic stroke (AIS) frequently results in the development of cognitive impairment, which quite often persists. The pathophysiological mechanisms involved in the development of cognitive impairment are only partially elucidated. The aim of this study was to evaluate the correlation between interleukin 6 (IL-6) and tumor necrosis factor-alpha (TNF-α) serum levels with cognitive impairment in AIS patients. SUBJECTS AND METHODS: day of hospitalization. RESULTS: Female stroke patients with cognitive impairment had significantly higher baseline levels of IL-6 (p<0.017), and TNF-α (p<0.017) than those without cognitive impairment. In the control measurement, a significant difference in IL-6 levels (p=0.037) in male and TNF-α levels (p=0.042) in female stroke patients with cognitive impairment was observed. CONCLUSIONS: These findings indicate that pro-inflammatory cytokines are probably implicated in the pathogenesis of cognitive decline in AIS patients.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.035
GPT teacher head0.240
Teacher spread0.205 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

Explore more

Same venuePubMed→Same topicNeuroinflammation and Neurodegeneration Mechanisms→French-language works237,207→