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Record W4416869912 · doi:10.1681/asn.20257fewm8d7

Bridging the Gaps and Mapping Strategies for Optimal Indigenous Kidney Health at Global Scale

2025· article· en· W4416869912 on OpenAlexaffabout
Somkanya Tungsanga, Aminu K. Bello, Vallabh O. Shah

Bibliographic record

VenueJournal of the American Society of Nephrology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBridging (networking)IndigenousScale (ratio)Kidney diseasePublic health

Abstract

fetched live from OpenAlex

Background: Approximately 480M individuals constituting 6% of the global population are Indigenous Peoples. Despite the richness and diversity of their cultures, the shared legacy of colonization has profoundly influenced their health outcomes and socioeconomic status. Indigenous Peoples experience disproportionately high rates of CKD, yet often encounter substantial barriers in access to and quality of care. These challenges are further compounded by geographic isolation, inadequate healthcare infrastructure, environmental exposures, and socioeconomic disadvantage. Methods: Achieving ASN vision “A World Without Kidney Diseases” requires urgent attention to the needs of high-risk populations of Indigenous Peoples. We have reviewed the current status of Indigenous kidney health across regions (Africa, Asia, Australia, Canada, Latin America, New Zealand, the Pacific Islands, and US), highlighting the variability in CKD burden (Figure) and determinants, and outlining culturally safe and responsive strategies that improve care delivery and outcomes. Results: We are presenting epidemiological and contextual analyses to provide a comprehensive global overview of Indigenous kidney health, examining how intersecting factors: colonial histories, social determinants of health, and systemic exclusion—drive poor outcomes. In particular, we explored how limited access to early intervention, culturally competent care, and sustainable kidney replacement therapy options contributes to elevated morbidity and mortality. Conclusion: By promoting culturally responsive practices and addressing systemic barriers, this new information contributes to a broader understanding of how to bridge persistent gaps in care. It also aims to empower healthcare professionals to better support Indigenous communities through respectful, informed, and inclusive approaches to treatment and prevention. Funding: Government Support – Non-U.S.Global map summarizing the prevalence (%) of chronic kidney disease in Indigenous populations

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)0.018
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0040.004
Scholarly communication0.0060.011
Open science0.0040.013
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.014
GPT teacher head0.322
Teacher spread0.308 · 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 designQualitative
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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the American Society of Nephrology→Same topicIndigenous Health, Education, and Rights→French-language works237,207→