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Record W2795243421 · doi:10.1161/circ.137.suppl_1.p341

Abstract P341: Poor Sleep Patterns Are Associated With Decreased Performance on the Montreal Cognitive Assessment in Both Younger and Older Women

2018· article· en· W2795243421 on OpenAlexaboutno aff
Brooke Aggarwal, Adam M. Brickman, Ming Liao, Molly E. Zimmerman

Bibliographic record

VenueCirculation · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Risk Factors
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMontreal Cognitive AssessmentPittsburgh Sleep Quality IndexInsomniaPopulationObstructive sleep apneaCognitionPolysomnographySleep apneaSleep onset latencyPhysical therapyGerontologySleep (system call)Sleep medicineSleep disorderInternal medicinePsychiatryCognitive impairmentApneaSleep quality

Abstract

fetched live from OpenAlex

Introduction: Poor cardiovascular health has been linked to an increased likelihood of cognitive impairment in older adults. Cognitive impairment has also been identified as an emerging co-morbidity of obstructive sleep apnea, a highly prevalent sleep disorder, particularly in patients with neurological conditions. Whether other aspects of sleep, including sleep duration, sleep quality, sleep onset latency, and insomnia are associated with cognition is not established. Objective: The aim of this study was to evaluate whether specific sleep patterns were associated with cognitive function in a diverse population of both younger and older, neurologically healthy women, and to determine whether this association is mediated by cardiovascular disease (CVD) risk factors. Methods: This was a baseline analysis of 392 women (59% racial/ethnic minority, mean age=39±16.53y, range 20-76y) participating in the ongoing American Heart Association Go Red for Women Strategically Focused Research Network population-based study at Columbia University Medical Center (CUMC). Cognitive function was assessed by the validated Montreal Cognitive Assessment (MoCA) screening instrument. Sleep duration, sleep quality, and time to sleep onset were assessed using the Pittsburgh Sleep Quality Index; insomnia was assessed using the Insomnia Severity Index. Blood lipids and glucose were measured in the biomarker core laboratory at CUMC. Multivariable linear regression models were used to evaluate associations between sleep, CVD risk factors, and MoCA scores, adjusted for age, race/ethnicity, education, health insurance, and tested for interactions between age and sleep. Results: The prevalence of abnormal MoCA (score <26) was 38%; mean scores were lower in adults ≥55y vs. <55y (p<0.0001), and racial/ethnic minorities vs. whites (p<0.0001). Average nightly sleep duration was 6.75±1.29 h, and 50% of women had poor sleep quality. In multivariable models testing for interactions, lower MoCA scores were associated with shorter sleep duration (p=0.007), worse quality sleep (p=0.0005), and higher insomnia level (p=0.04). In stratified analyses, associations between MoCA scores and sleep duration, sleep quality, and insomnia persisted among both younger (<55y) and older (≥55y) groups. Lower MoCA scores were also associated with higher triglycerides (p=0.0001) and lower HDL-cholesterol (p=0.0006); formal tests of mediation suggested that the relation between cognition and insomnia was mediated by triglyceride level. Conclusions: Poor sleep patterns were highly prevalent and associated with lower cognitive function, even in younger women in this diverse population. Sleep patterns should be further investigated as a potential mechanism to identify individuals at risk of cognitive decline. Whether the relation is causal or mediated through traditional CVD risk factors deserves further study.

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)0.000
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 score0.009
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.014
GPT teacher head0.261
Teacher spread0.246 · 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".

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Citations1
Published2018
Admission routes1
Has abstractyes

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