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Record W4413009394 · doi:10.1016/j.ekir.2025.07.045

Association of Dietary Sodium and Potassium With Blood Pressure and Proteinuria in Africans With Kidney Disease

2025· article· en· W4413009394 on OpenAlexaff
Titilayo O. Ilori, Manmak Mamven, Yemi Raheem Raji, Edward Kwakyi, Bolanle A. Omotoso, Rotimi Braimoh, Adaobi Solarin, Theophilus Umeizudike, Runqi Zhao, Bryan Kestenbaum, David K. Prince, Nanna Ripiye, Chinwuba Ijeoma, Jessica Slear, Amisu A Mumuni, Fatiu Arogundade, Babatunde Lawal Salako, Rasheed Gbadegesin, Rulan S. Parekh, Josée Dupuis, Dwomoa Adu, Ifeoma Ulasi, C O Amira, Akinlolu Ojo, Cheryl A.M. Anderson, Sushrut S. Waikar

Bibliographic record

VenueKidney International Reports · 2025
Typearticle
Languageen
FieldNursing
TopicSodium Intake and Health
Canadian institutionsMcGill UniversitySickKids FoundationHospital for Sick ChildrenWomen's College HospitalUniversity of Toronto
FundersDivision of Diabetes, Endocrinology, and Metabolic DiseasesNational Institute of Diabetes and Digestive and Kidney DiseasesNateraNational Institutes of HealthVertex PharmaceuticalsBoston Medical CenterAmerican Heart AssociationSanofiPfizerAstraZeneca
KeywordsMedicineProteinuriaPotassiumSodiumKidney diseaseBlood pressureInternal medicineKidneyDiseaseEndocrinology

Abstract

fetched live from OpenAlex

Introduction: ), proxies for dietary intake, with BP and proteinuria in CKD cohorts in West Africa and USA. Methods: ratio. The outcomes were systolic and diastolic BP (SBP and DBP), and 24-hour urine protein at baseline. Using mixed-effect linear regression, we calculated crude and adjusted effect sizes (b coefficients) and 95% confidence intervals. Results: was associated with higher proteinuria in all participants. Conclusion: in African populations require future studies.

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)0.004
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.006
GPT teacher head0.250
Teacher spread0.243 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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