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Record W2953939771 · doi:10.1111/jch.13611

Science of Salt: A regularly updated systematic review of salt and health outcomes studies (April to October 2018)

2019· review· en· W2953939771 on OpenAlexaff
Rachael McLean, Kristina Petersen, JoAnne Arcand, Daniela Malta, Sarah Rae, Sudhir Raj Thout, Kathy Trieu, Claire Johnson, Norman R.C. Campbell

Bibliographic record

VenueJournal of Clinical Hypertension · 2019
Typereview
Languageen
FieldNursing
TopicSodium Intake and Health
Canadian institutionsLibin Cardiovascular Institute of AlbertaToronto Metropolitan UniversityUniversity of CalgaryOntario Tech University
Fundersnot available
KeywordsMedicineCritical appraisalCohort studyDashCohortRandomized controlled trialProspective cohort studyEnvironmental healthDiseaseDietary saltMeta-analysisIntensive care medicineBlood pressureInternal medicineAlternative medicinePathology

Abstract

fetched live from OpenAlex

The Science of Salt reviews identify, summarize, and critically appraise published studies on dietary salt and health outcomes according to pre-specified methods. This review covers the period April 3 to October 30, 2018. Here, nineteen studies that fit pre-specified criteria for review and summary are included. Three of these, one prospective cohort study, one randomized controlled trial, and a post hoc analysis of the Dietary Approaches to Stop Hypertension (DASH) sodium trial fulfilled the quality criteria for detailed critical appraisal, including risk of bias assessment, and commentary. Two trials demonstrated a positive association between salt intake and blood pressure. In a cohort of older Italians, increased risk of total mortality was observed with salt intake less than ~16 g/d (6300 mg sodium/d) at baseline; no association existed for incident cardiovascular disease (CVD) or CVD mortality. The paucity of published studies which met our criteria for methodological quality is of concern.

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)0.020
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.050
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0150.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.402
GPT teacher head0.545
Teacher spread0.143 · 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 designSystematic review
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

Citations10
Published2019
Admission routes1
Has abstractyes

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