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Record W4206363852 · doi:10.1007/s44200-021-00010-w

Lower Extremity Artery Disease and Cognitive Impairment

2022· article· en· W4206363852 on OpenAlexaboutno aff
Agnieszka Turowicz, Alina Czapiga, Maciej Malinowski, T Dorobisz, Bartłomiej Czapla, Dariusz Janczak

Bibliographic record

VenueArtery Research · 2022
Typearticle
Languageen
FieldMedicine
TopicPeripheral Artery Disease Management
Canadian institutionsnot available
FundersUniwersytet Medyczny im. Piastów Slaskich we Wroclawiu
KeywordsMedicineMontreal Cognitive AssessmentNeuropsychologyCognitionCognitive impairmentCardiologyInternal medicineDiseasePsychiatry

Abstract

fetched live from OpenAlex

Abstract Background The association between cerebrovascular disease and cognitive impairment is well known, but the impact of lower extremity arterial disease (LEAD) on neuropsychological performance is less established. Objectives The aim of this study was to investigate the influence of LEAD on cognitive impairment. Materials and Methods A total of 20 patients with LEAD, classified by Fountain’s stage IIB, qualified for revascularization surgery has been included in this prospective study. Neuropsychological assessments have been done using MoCA and CANTAB test. Fifteen patients qualified for hernia surgery, without peripheral artery disease served as a control group. Linear regression model has been applied to assess the connection between LEAD and cognitive impairment. Results Differences between the study groups reach significance in both MoCA and CANTAB test. In MoCA test, patients with LEAD had lower levels of performance in attention ( p = 0.0254), visuospatial/executive ( p = 0.0343) and delayed recall ( p = 0.0032). The mean MoCA score was below 26 points. In CANTAB test, patients with LEAD performed worse in visual memory and learning. After adjusted for common cerebrovascular risk factors, LEAD was significantly correlated with cognitive impairment defined as MoCA score < 26 points. Conclusions Lower extremity artery disease is associated with cognitive impairment independently of cerebrovascular risk factors.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.054
GPT teacher head0.351
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.

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

Citations1
Published2022
Admission routes1
Has abstractyes

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