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Record W4383424995 · doi:10.1177/11795468231158206

Salt-Sensitive Hypertension: Mediation by Salt-Induced Hypervolemia and Phosphate-Induced Vascular Calcification

2023· article· en· W4383424995 on OpenAlexaff
Ronald B. Brown

Bibliographic record

VenueClinical Medicine Insights Cardiology · 2023
Typearticle
Languageen
FieldNursing
TopicSodium Intake and Health
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsHypervolemiaMedicineCalcificationArterial stiffnessInternal medicineVascular smooth muscleBlood pressurePathogenesisPathophysiology of hypertensionEndocrinologyCardiologyBlood volume

Abstract

fetched live from OpenAlex

Preventing hypertension by restricting dietary salt intake, sodium chloride, is well established in public health policy, but a pathophysiological mechanism has yet to explain the controversial clinical finding that some individuals have a greater risk of hypertension from exposure to salt intake, termed salt-sensitive hypertension. The present perspective paper synthesizes interdisciplinary findings from the research literature and offers novel insights proposing that the pathogenesis of salt-sensitive hypertension is mediated by interaction of salt-induced hypervolemia and phosphate-induced vascular calcification. Arterial stiffness and blood pressure increase as calcification in the vascular media layer reduces arterial elasticity, preventing arteries from expanding to accommodate extracellular fluid overload in hypervolemia related to salt intake. Furthermore, phosphate has been found to be a direct inducer of vascular calcification. Reduction of dietary phosphate may help reduce salt-sensitive hypertension by lowering the prevalence and progression of vascular calcification. Further research should investigate the correlation of vascular calcification with salt-sensitive hypertension, and public health recommendations to prevent hypertension should encourage reductions of both sodium-induced hypervolemia and phosphate-induced vascular calcification.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.092
GPT teacher head0.370
Teacher spread0.278 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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