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Record W1976973072 · doi:10.1186/1471-2369-15-114

Predictors of progression to chronic dialysis in survivors of severe acute kidney injury: a competing risk study

2014· article· en· W1976973072 on OpenAlexafffundabout
Ziv Harel, Chaim M. Bell, Stephanie N. Dixon, Eric McArthur, Matthew T. James, Amit X. Garg, Shai Har-El, Samuel A. Silver, Ron Wald

Bibliographic record

VenueBMC Nephrology · 2014
Typearticle
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsUniversity of CalgaryInstitute for Clinical Evaluative SciencesMount Sinai HospitalWestern UniversitySt. Michael's HospitalLondon Health Sciences CentreUniversity of Toronto
FundersCanadian Institutes of Health ResearchCanadian Patient Safety Institute
KeywordsMedicineNephrologyDialysisKidney diseaseHazard ratioInternal medicineAcute kidney injuryComorbidityProportional hazards modelRenal functionConfidence intervalRelative riskIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Survivors of acute kidney injury are at an increased risk of developing irreversible deterioration in kidney function and in some cases, the need for chronic dialysis. We aimed to determine predictors of chronic dialysis and death among survivors of dialysis-requiring acute kidney injury. METHODS: We used linked administrative databases in Ontario, Canada, to identify patients who were discharged from hospital after an episode of acute kidney injury requiring dialysis and remained free of further dialysis for at least 90 days after discharge between 1996 and 2009. Follow-up extended until March 31, 2011. The primary outcome was progression to chronic dialysis. Predictors for this outcome were evaluated using cause-specific Cox proportional hazards models, and a competing risk approach was used to calculate absolute risk. RESULTS: We identified 4 383 patients with acute kidney injury requiring temporary in-hospital dialysis who survived to discharge. After a mean follow-up of 2.4 years, 356 (8%) patients initiated chronic dialysis and 1475 (34%) died. The cumulative risk of chronic dialysis was 13.5% by the Kaplan-Meier method, and 10.3% using a competing risk approach. After accounting for the competing risk of death, previous nephrology consultation (subdistribution hazard ratio (sHR) 2.03; 95% confidence interval (CI) 1.61-2.58), a history of chronic kidney disease (sHR3.86; 95% CI 2.99-4.98), a higher Charlson comorbidity index score (sHR 1.10; 95% CI 1.05-1.15/per unit) and pre-existing hypertension (sHR 1.82; 95% CI 1.28-2.58) were significantly associated with an increased risk of progression to chronic dialysis. CONCLUSIONS: Among survivors of dialysis-requiring acute kidney injury who initially become dialysis independent, the subsequent need for chronic dialysis is predicted by pre-existing kidney disease, hypertension and global comorbidity. This information can identify patients at high risk of progressive kidney disease who may benefit from closer surveillance after cessation of the acute phase of illness.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.059
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.014
GPT teacher head0.329
Teacher spread0.315 · 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

Citations48
Published2014
Admission routes3
Has abstractyes

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