MétaCan
Menu
Back to cohort
Record W4304690294 · doi:10.1016/j.xkme.2022.100557

Race and Mortality in Hemodialysis Patients in Brazil

2022· article· en· W4304690294 on OpenAlexfundno aff
Marcelo Barreto Lopes, Márcia Tereza Silveira-Martins, Fernanda Albuquerque da Silva, Luciana Ferreira Silva, Maria Tereza Silva-Martins, Cácia Mendes Matos, Angiolina Campos Kraychete, Keith C. Norris, Sherman A. James, Antônio Alberto Lopes

Bibliographic record

VenueKidney Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsnot available
FundersNational Institutes of HealthConselho Nacional de Desenvolvimento Científico e TecnológicoForskningsrådet för Arbetsliv och SocialvetenskapLaw Foundation of SaskatchewanAmerican Heart Association
KeywordsHemodialysisMedicineDemographyDialysisProspective cohort studyProportional hazards modelConfoundingRace (biology)CohortGerontologyInternal medicine

Abstract

fetched live from OpenAlex

Rationale & Objective: Studies in the United States and United Kingdom generally report better survival for Black than White patients undergoing maintenance hemodialysis, a finding not explained by differences in sociodemographics or comorbid conditions. It is not clear if such findings can be generalized to other countries. We investigated the association between race and mortality among a Black, White, and Mixed-Race sample of maintenance hemodialysis patients in Salvador, Brazil. Study Design: Prospective cohort study. Baseline data collection from July 1, 2005 through December 31, 2010. The follow-up period ended on December 31, 2017. Setting & Participants: The Prospective Study of the Prognosis of Chronic Hemodialysis Patients (PROHEMO) is a cohort of 1,501 patients from 4 dialysis units in Salvador, Brazil. Predictor: Race categorized as White (12.9%), Mixed-Race (62.4%), and Black (24.8%), using White as the reference category. Outcome: Survival. Analytical Approach: Using Cox regression models, we tested the association between race and mortality, with adjustments for age, sex, social factors, laboratory results, and comorbid conditions. Results: The mean age was 49 years for Black and Mixed-Race patients and 55 years for White patients. In a Cox model adjusted for age, mortality did not differ between Black and White patients (HR, 1.10; 95% CI, 0.66-1.83) or between Mixed-Race and White patients (HR, 1.00; 95% CI, 0.65-1.54). Adjustment for sociodemographics and comorbid conditions had minimal impact on these results. Limitations: Potential residual confounding and lack of adjustment for time-varying variables. Conclusions: Contrary to studies in the United States and United Kingdom, we did not find racial difference in mortality among patients in our Brazilian setting who were being treated by maintenance hemodialysis. These results underscore the importance of investigating racial differences in mortality among patients undergoing maintenance hemodialysis in different populations and countries.

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)0.003
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 score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.013
GPT teacher head0.286
Teacher spread0.273 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueKidney MedicineSame topicDialysis and Renal Disease ManagementFrench-language works237,207