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Record W2146678163 · doi:10.1503/cmaj.1031859

Death and renal transplantation among Aboriginal people undergoing dialysis

2004· article· en· W2146678163 on OpenAlexafffundvenueabout
Marcello Tonelli

Bibliographic record

VenueCanadian Medical Association Journal · 2004
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchHealth CanadaFondation pour la Recherche MédicaleKidney Foundation of Canada
KeywordsMedicineDialysisHazard ratioTransplantationProportional hazards modelConfidence intervalKidney transplantationInternal medicineDiabetes mellitusEnd stage renal diseaseHemodialysisDemographyEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: Despite the increase in the number of Aboriginal people with end-stage renal disease around the world, little is known about their health outcomes when undergoing renal replacement therapy. We evaluated differences in survival and rate of renal transplantation among Aboriginal and white patients after initiation of dialysis. METHODS: Adult patients who were Aboriginal or white and who commenced dialysis in Alberta, Saskatchewan or Manitoba between Jan. 1, 1990, and Dec. 31, 2000, were recruited for the study and were followed until death, transplantation, loss to follow-up or the end of the study (Dec. 31, 2001). We used Cox proportional hazards models to examine the effect of race on patient survival and likelihood of transplant, with adjustment for potential confounders. RESULTS: Of the 4333 adults who commenced dialysis during the study period, 15.8% were Aboriginal and 72.4% were white. Unadjusted rates of death per 1000 patient-years during the study period were 158 (95% confidence interval [CI] 144-176) for Aboriginal patients and 146 (95% CI 139-153) for white patients. When follow-up was censored at the time of transplantation, the age-adjusted risk of death after initiation of dialysis was significantly higher among Aboriginal patients than among white patients (hazard ratio [HR] 1.15, 95% CI 1.02-1.30). The greater risk of death associated with Aboriginal race was no longer observed after adjustment for diabetes mellitus and other comorbid conditions (adjusted HR 0.89, 95% CI 0.77-1.02) and did not appear to be associated with socioeconomic status. During the study period, unadjusted transplantation rates per 1000 patient-years were 62 (95% CI 52-75) for Aboriginal patients and 133 (95% CI 125-142) for white patients. Aboriginal patients were significantly less likely to receive a renal transplant after commencing dialysis, even after adjustment for potential confounders (HR 0.43, 95% CI 0.35-0.53). In an additional analysis that included follow-up after transplantation for those who received renal allografts, the age-adjusted risk of death associated with Aboriginal race (HR 1.36, 95% CI 1.21-1.52) was higher than when follow-up after transplantation was not considered, perhaps because of the lower rate of transplantation among Aboriginals. INTERPRETATION: Survival among dialysis patients was similar for Aboriginal and white patients after adjustment for comorbidity. However, despite universal access to health care, Aboriginal people had a significantly lower rate of renal transplantation, which might have adversely affected their survival when receiving renal replacement therapy.

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)0.002
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 score0.918
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.256
Teacher spread0.250 · 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

Citations90
Published2004
Admission routes4
Has abstractyes

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