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Record W4319592945 · doi:10.1136/bmjopen-2022-065470

Dietary sodium, potassium intake, sodium-to-potassium ratio and risk of hypertension: a protocol for systematic review and dose–response meta-analysis of cohort studies

2023· article· en· W4319592945 on OpenAlexaboutno aff
Yingtian Yang, Qian Wu, Qianyu Lv, Junjia Li, Lanlan Li, Shihan Wang

Bibliographic record

VenueBMJ Open · 2023
Typearticle
Languageen
FieldNursing
TopicSodium Intake and Health
Canadian institutionsnot available
FundersBeijing Municipal Science and Technology CommissionNational Natural Science Foundation of China
KeywordsMedicinePotassiumIncidence (geometry)Meta-analysisSodiumCohort studyInternal medicineConfidence intervalPublication biasCohort

Abstract

fetched live from OpenAlex

INTRODUCTION: Hypertension (HTN) is the leading cause of disease and death on a global scale. Diet's sodium and potassium levels may synergistically affect blood pressure. Currently, the sodium-to-potassium (Na/K) ratio is becoming a more reliable indicator. There has not been a systematic investigation of the dose-response relationship between dietary sodium, potassium, the Na/K ratio and the incidence of HTN based on the same study criteria. This study will conduct a thorough dose-response meta-analysis of cohort studies to estimate the effects of dietary sodium, potassium, and the Na/K ratio on the incidence of HTN to provide the most accurate reference for sodium and potassium intake. METHODS AND ANALYSIS: We will identify all relevant prospective and retrospective cohort studies by searching PubMed, Embase and Web of Science (from inception until December 2022). Exposures are 24 hours urinary excretions, and the outcome is the incidence of HTN. Two researchers will perform the literature selection and data extraction separately. The Newcastle-Ottawa Scale will be used to evaluate the quality of the included studies. We will use both linear and non-linear regression models to investigate the dose-response relationship among different levels (≥3) of sodium, potassium, Na/K ratio intake and the incidence of HTN (OR/RR/HR). Subgroup and sensitivity analyses will be applied to assess the potential heterogeneity sources and examine the stability of the results. We will also evaluate heterogeneity across studies and publication bias. Stata V.15.0 and RevMan V.5.0 will be used for statistical analyses. ETHICS AND DISSEMINATION: According to the Institutional Review Board/Independent Ethics Committee of the Guang'anmen Hospital of the China Academy of Chinese Medical Science, this systematic meta-analysis protocol does not require ethical approval or informed consent. This meta-analysis will be published in a scientific journal with peer reviews. PROSPERO REGISTRATION NUMBER: CRD42022331203.

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)0.009
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.679
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
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 head0.310
GPT teacher head0.471
Teacher spread0.161 · 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 designMeta-analysis
Domainnot available
GenreProtocol

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

Citations6
Published2023
Admission routes1
Has abstractyes

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