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Record W1489637646 · doi:10.1111/chf.12007

Elevated Levels of Interleukin 6 and C‐Reactive Protein Associated With Cognitive Impairment in Heart Failure

2012· article· en· W1489637646 on OpenAlexaboutno aff
Ponrathi Athilingam, Jan A. Moynihan, Leway Chen, Rita D’Aoust, Maureen Groër, Kevin E. Kip

Bibliographic record

VenueCongestive Heart Failure · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsnot available
FundersNational Institute on Aging
KeywordsMedicineCognitive impairmentHeart failureC-reactive proteinInterleukin 6InterleukinCognitionInternal medicineCardiologyInflammationPsychiatryCytokine

Abstract

fetched live from OpenAlex

There is abundant evidence on inflammatory mechanisms in heart failure (HF) that are used for prognostication of the disease; however, data are lacking regarding the association between elevated cytokines, C-reactive protein (CRP), and cognition in HF. A cross-sectional pilot study of 38 patients with HF, aged 62 years (standard deviation± 9 years), predominantly men (68%) and Caucasian (79%) were screened for cognitive function using the Montreal Cognitive Assessment (MoCA). The study aimed to examine cognitive scores on MoCA with cytokines, interleukin 6 [IL-6] and tumor necrosis factor α [TNF-α], and CRP as indicators of early cognitive changes in HF. The result showed no direct correlation between cardiac variables and the MoCA score. The MoCA score, however, was inversely associated with IL-6 (r=-0.53, P=.001) and CRP (r=-0.34, P=.04), with no association to TNF-α. Regression analysis on the MoCA score and log-transformed IL-6 accounted for an additional 11% variation and remained statistically significant (P=.008) after controlling for covariates of education, living arrangements, and loneliness. The large effect size (R(2) =0.87) found in this pilot study provides rationale for a larger exploratory study to examine associations between cognitive function, cytokines, and CRP levels and help design future intervention studies.

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 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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.031
GPT teacher head0.264
Teacher spread0.233 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations70
Published2012
Admission routes1
Has abstractyes

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