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Record W1983414436 · doi:10.1042/cs20080207

Salt and high blood pressure

2009· review· en· W1983414436 on OpenAlexaff
Sailesh Mohan, Norm R.C. Campbell

Bibliographic record

VenueClinical Science · 2009
Typereview
Languageen
FieldNursing
TopicSodium Intake and Health
Canadian institutionsUniversity of Calgary
FundersWorld Health Organization
KeywordsMedicineEnvironmental healthBlood pressurePopulationDiseaseDietary saltIntervention (counseling)EpidemiologyInternal medicine

Abstract

fetched live from OpenAlex

HBP (high blood pressure) is the leading risk of death in the world. Unfortunately around the world, blood pressure levels are predicted to become even higher, especially in developing countries. High dietary salt is an important contributor to increased blood pressure. The present review evaluates the association between excess dietary salt intake and the importance of a population-based strategy to lower dietary salt, and also highlights some salt-reduction strategies from selected countries. Evidence from diverse sources spanning animal, epidemiology and human intervention studies demonstrate the association between salt intake and HBP. Furthermore, animal studies indicate that short-term interventions in humans may underestimate the health risks associated with high dietary sodium. Recent intervention studies have found decreases in cardiovascular events following reductions in dietary sodium. Salt intake is high in most countries and, therefore, strategies to lower salt intake could be an effective means to reduce the increasing burden of HBP and the associated cardiovascular disease. Effective collaborative partnerships between governments, the food industry, scientific organizations and healthcare organizations are essential to achieve the WHO (World Health Organization)-recommended population-wide decrease in salt consumption to less than 5 g/day. In the milieu of increasing cardiovascular disease worldwide, particularly in resource-constrained low- and middle-income countries, salt reduction is one of the most cost-effective strategies to combat the epidemic of HBP, associated cardiovascular disease and improve population health.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.165
GPT teacher head0.496
Teacher spread0.331 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations107
Published2009
Admission routes1
Has abstractyes

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