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Record W146265137 · doi:10.1093/sleep/34.3.335

Sleep Deprivation Increases Blood Pressure in Healthy Normotensive Elderly and Attenuates the Blood Pressure Response to Orthostatic Challenge

2011· article· en· W146265137 on OpenAlexafffund
Rébecca Robillard, Paola A. Lanfranchi, François Prince, Daniel Filipini, Julie Carrier

Bibliographic record

VenueSLEEP · 2011
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsInstitut Universitaire de Gériatrie de MontréalCanadian Sleep & Circadian NetworkUniversité de MontréalHôpital du Sacré-Cœur de Montréal
FundersCanadian Institutes of Health ResearchInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsBlood pressureSleep deprivationMedicineOrthostatic vital signsSleep (system call)Heart rateInternal medicineCardiologyAnesthesiaCircadian rhythm

Abstract

fetched live from OpenAlex

STUDY OBJECTIVES: To determine how aging affects the impact of sleep deprivation on blood pressure at rest and under orthostatic challenge. DESIGN: Subjects underwent a night of sleep and 24.5 h of sleep deprivation in a crossover counterbalanced design. SETTING: Sleep laboratory. PARTICIPANTS: Sixteen healthy normotensive men and women: 8 young adults (mean 24 years [SD 3.1], range 20-28 years) and 8 elderly adults (mean 64.1 years [SD 3.4], range 60-69 years). INTERVENTIONS: Sleep deprivation. MEASUREMENTS AND RESULTS: Brachial cuff arterial blood pressure and heart rate were measured in semi-recumbent and upright positions. These measurements were compared across homeostatic sleep pressure conditions and age groups. Sleep deprivation induced a significant increase in systolic and diastolic blood pressure in elderly but not young adults. Moreover, sleep deprivation attenuated the systolic blood pressure orthostatic response in both age groups. CONCLUSIONS: Our results suggest that sleep deprivation alters the regulatory mechanisms of blood pressure and might increase the risk of hypertension in healthy normotensive elderly.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.892

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 studies0.0000.000
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 head0.018
GPT teacher head0.263
Teacher spread0.245 · 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

Citations70
Published2011
Admission routes2
Has abstractyes

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