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Record W2116888154 · doi:10.1681/asn.2012020164

Lifetime Risk of ESRD

2012· article· en· W2116888154 on OpenAlexafffund
Tanvir Chowdhury Turin, Marcello Tonelli, Braden Manns, Sofia B. Ahmed, Pietro Ravani, Matthew T. James, Brenda R. Hemmelgarn

Bibliographic record

VenueJournal of the American Society of Nephrology · 2012
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsFoothills Medical CentreUniversity of AlbertaUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsMedicineCohortRenal functionPopulationEnd stage renal diseaseCohort studyLifetime riskRisk assessmentKidney diseaseGerontologyDemographyDiseaseInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Lifetime risk is the cumulative risk of experiencing an outcome between a disease-free index age and death. The lifetime risk of ESRD for a middle-aged individual is a relevant and easy to communicate measure of disease burden. We estimated lifetime risk of ESRD in a cohort of 2,895,521 adults without ESRD from 1997 to 2008. To estimate lifetime risk of ESRD by level of baseline kidney function, we analyzed a cohort of participants who had a serum creatinine measurement. We also estimated the sex- and index age-specific lifetime risk of incident ESRD and accounted for the competing risk of death. Among those individuals without ESRD at age 40 years, the lifetime risk of ESRD was 2.66% for men and 1.76% for women. The risk was higher in persons with reduced kidney function: for eGFR=44-59 ml/min per 1.73 m(2), the lifetime risk of ESRD was 7.51% for men and 3.21% for women, whereas men and women with relatively preserved kidney function (eGFR=60-89 ml/min per 1.73 m(2)) had lifetime risks of ESRD of 1.01% and 0.63%, respectively. The lifetime risk of ESRD was consistently higher for men at all ages and eGFR strata compared with women. In conclusion, approximately 1 in 40 men and 1 in 60 women of middle age will develop ESRD during their lifetimes (living into their 90s). These population-based estimates may assist individuals who make decisions regarding public health policy.

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 score0.010
Threshold uncertainty score0.028

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 studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.011
GPT teacher head0.274
Teacher spread0.263 · 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

Citations93
Published2012
Admission routes2
Has abstractyes

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