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Record W4402525672 · doi:10.1111/cpf.12902

‘Effects of dehydration on central blood pressure in young healthy adults’

2024· article· en· W4402525672 on OpenAlexfundno aff
M. Giddings, Jacob P. Auringer, Nathan F. Meier, Elizabeth C. Schroeder, Chong Wang, Lindsay Kane‐Barnese

Bibliographic record

VenueClinical Physiology and Functional Imaging · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsnot available
FundersConcordia University
KeywordsMedicinePulse wave velocityBlood pressureGold standard (test)CardiologyInternal medicineCardiovascular healthArterial stiffnessPulse Wave AnalysisDisease

Abstract

fetched live from OpenAlex

PURPOSE: Brachial blood pressure (BP) is the current gold standard for BP assessment; however, measures of pulse wave velocity (PWV) and central blood pressure (CBP) may contribute uniquely to assessment of cardiovascular health status. As of yet, standards for assessment of CBP and PWV have not addressed the impact of hydration status on proper measurement. To understand the impact of hydration, PWV and CBP should be measured in a euhydrated and hypohydrated state. METHODS: Forty-three young, healthy participants (21 ± 2 years) completed a dehydration protocol utilizing moderate aerobic activity until they lost 1%-2% of their body weight. PWV and CBP were measured before and following the dehydration protocol. Linear regression was utilized to assess change in hydration status and change in PWV and CBP. RESULTS: No significant relationships were observed between the change in hydration status (% body weight lost) and PWV (β = 0.05, p = 0.78) or central diastolic BP (β = -3.8, p = 0.10), however, a significant relationship was observed with central systolic BP (β = -5.0, p = 0.03). DISCUSSION: In conclusion, the assessment of hydration status before measurement of CBP or PWV may not be necessary in young, healthy individuals.

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)0.001
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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)0.0010.000

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 head0.013
GPT teacher head0.322
Teacher spread0.309 · 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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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