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Record W2576753219 · doi:10.1186/s40885-016-0058-5

Association between central blood pressure, arterial stiffness, and mild cognitive impairment

2017· article· en· W2576753219 on OpenAlexafffundabout
Raheem Suleman, Raj Padwal, Peter Hamilton, A. Senthilselvan, Kannayiram Alagiakrishnan

Bibliographic record

VenueClinical Hypertension · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsUniversity of Alberta HospitalUniversity of Alberta
FundersCanadian Institutes of Health ResearchUniversity Hospital FoundationUniversity of Alberta
KeywordsMontreal Cognitive AssessmentArterial stiffnessBlood pressureAngiologyMedicineInternal medicineCognitionCardiologyPulse pressureCognitive impairmentDiseasePsychiatry

Abstract

fetched live from OpenAlex

To determine the relationship between central blood pressure (CBP) indices and mild cognitive impairment (MCI) in adults over the age of 50. A cross-sectional study conducted using a non-invasive SphygmoCor XCEL device. CBP indices and brachial blood pressure were measured in 50 inpatients and outpatients. MCI was assessed using the Montreal Cognitive Assessment (MoCA) instrument and by the European Consortium Criteria (ECC). Seventy-six percent of subjects had hypertension, and 52% were diagnosed as having MCI using the ECC. No significant association was found between any of the measured blood pressure variables and global cognition. A significant relationship was observed between augmentation index (AI) and abnormal clock-drawing (p = 0.04) and language (p = 0.02), and between pulse pressure amplification (PPA) and language (p = 0.03). CBP indices like AI and PPA, which are markers of vascular stiffness, are associated with poor executive function and language cognitive domain deficits.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.042
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.058
GPT teacher head0.356
Teacher spread0.298 · 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.

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

Citations22
Published2017
Admission routes3
Has abstractyes

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