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Record W2017597420 · doi:10.1111/jgs.12904

Cognitive Impairment Is Associated with High Coated‐Platelet Levels in Individuals with Carotid Atherosclerosis

2014· letter· en· W2017597420 on OpenAlexaboutno aff
Angelia Kirkpatrick, Andrea S. Vincent, George L. Dale, Călin I. Prodan

Bibliographic record

VenueJournal of the American Geriatrics Society · 2014
Typeletter
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMontreal Cognitive AssessmentStroke (engine)Internal medicineDementiaPlateletDepression (economics)Platelet activationCardiologyAnesthesiaDisease

Abstract

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Coated-platelets are a subpopulation of procoagulant platelets observed upon dual agonist stimulation with thrombin and collagen.1 Individuals with nonlacunar ischemic stroke have higher coated-platelet levels than individuals without stroke or with lacunar stroke.2 Higher coated-platelet levels in symptomatic individuals with 50% or more carotid stenosis are associated with early stroke recurrence.3 Carotid disease is a risk factor for cognitive impairment, thought to be due to cerebral emboli or hypoperfusion with or without silent brain infarctions.4 A pilot study was undertaken to test the hypothesis that high coated-platelet levels are associated with cognitive impairment in individuals with carotid atherosclerosis. Consecutive outpatients referred for carotid Doppler evaluation were screened for cognitive impairment using the Montreal Cognitive Assessment (MoCA) test5 and for depression using the Beck Depression Inventory-II (BDI-II).6 Exclusion criteria included stroke or transient ischemic attack (TIA) within the previous 6 months, known dementia, use of anticoagulants, prolonged coagulation tests (prothrombin time, partial thromboplastin time, international normalized ratio), severe depression (BDI-II score ≥33),6 or intake of sedating substances within 2 hours before screening. Electronic medical records were reviewed for evidence of stroke and TIA within the previous 6 months or prior diagnosis of memory loss. After informed consent, 5 mL of blood was drawn, and coated-platelet levels were determined as described previously.2, 3 Levels are reported as percentage of cells converted to coated-platelets.2 Repeated measurements of coated-platelet levels were also available for a subset of participants (n = 14). Descriptive statistics were determined and independent-sample t tests, and chi-square tests were performed. Covariates were determined using correlations between potential covariates and coated-platelet levels, as well as group differences in relevant variables, and included as needed. The stability of coated-platelet levels at 6-month intervals within groups was examined using a mixed-effects general linear model. All analyses were generated using SAS version 9.2 (SAS Institute, Inc., Cary, NC), with significance set at P < .05. Seventy-nine patients were screened. Nineteen were excluded for severe depression (n = 6), refusing the BDI-II screen (n = 1), intake of sedating medications before evaluation (n = 3), previous dementia diagnosis (n = 2), or evidence of stroke or TIA within 6 months before enrollment (n = 7). Table 1 lists demographic characteristics, risk factors, and medications that may influence coated-platelet levels.7 All participants were military veterans, resulting in an overrepresentation of men. Fifty-seven percent (34/60) of patients had evidence of cognitive impairment (MoCA score <26, range 17–25). Of these, 32 (94%) had a MoCA score of 19 or greater, suggestive of mild cognitive impairment.5 There were no significant differences between participants with (n = 34) and without (n = 26) cognitive impairment in demographic characteristics, risk factors, or medications, although there was a trend toward older age (P = .06) and a greater proportion of subjects with 50% or more carotid stenosis in participants with cognitive impairment than of those without cognitive impairment (50% vs 31%, P = .13). There was also a correlation approaching significance between coated-platelet levels and hypertension (P = .05). Mean coated-platelet levels ± standard deviation were higher in participants with cognitive impairment (42.7 ± 11.5%) than in those without (34.1 ± 12.3%) (P = .007), even after adjusting for carotid stenosis severity, age, and hypertension (adjusted mean (standard error of the mean) 42.5 (2.0%) vs 34.4 (2.3%), P = .01). Repeat coated-platelet levels showed no significant change over approximately 6 months (P = .42, n = 14). These results demonstrate the presence of higher coated-platelet levels in individuals with carotid atherosclerosis and cognitive impairment than in those without cognitive impairment. The levels observed here in individuals with cognitive impairment are almost identical to those found previously in individuals with large-artery symptomatic stroke.3 Unlike single-agonist activated platelets, coated-platelets retain high levels of several procoagulant proteins on the cell surface.1, 8 The combination of bound procoagulant proteins and exposed phosphatidylserine results in a robust prothrombinase activity.1, 8 Because thrombin generation is central to coagulation, coated-platelets are considered to be prothrombotic.1 The presence of high coated-platelet production, and by extrapolation high prothrombinase activity, in individuals with asymptomatic carotid atherosclerosis and cognitive impairment lend partial support to the proposed role of microembolism in the development of early vascular cognitive impairment in these individuals. These data also confirm previous reports that a significant percentage of individuals with carotid atherosclerosis have cognitive impairment, with the range of MoCA values observed suggesting mild cognitive impairment.5, 9, 10 Limitations of this study include small sample size and underrepresentation of women and minorities. Nevertheless, these results suggest that further study of coated-platelets in populations at risk for carotid disease4 is warranted. We thank Leslie Guthery and Paul Friese for their assistance. Conflict of Interest: Supported by the Department of Veterans Affairs (2011 Veterans Integrated Support Network 16 (Angelia C. Kirkpatrick) and Merit Award 1I01CX000340 (Calin I. Prodan)). Author Contributions: All authors: study concept and design, data acquisition, analysis and interpretation, and manuscript preparation. Sponsor's Role: None.

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)0.003
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.239
Teacher spread0.224 · 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".

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Citations2
Published2014
Admission routes1
Has abstractyes

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Same venueJournal of the American Geriatrics Society→Same topicCerebrovascular and Carotid Artery Diseases→French-language works237,207→