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Record W3106566169 · doi:10.1016/j.ekir.2020.11.010

Risk of Kidney Failure, Death, and Cardiovascular Events After Lower Limb Complications in Patients With CKD

2020· article· en· W3106566169 on OpenAlexafffundabout
Kevin Li, Thomas W. Ferguson, John M. Embil, Claudio Rigatto, Paul Komenda, Navdeep Tangri

Bibliographic record

VenueKidney International Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicPeripheral Artery Disease Management
Canadian institutionsUniversity of ManitobaSeven Oaks General Hospital
FundersMax Rady College of Medicine, University of ManitobaAgency for Healthcare Research and QualityWinnipeg Regional Health AuthorityManitoba Centre for Health Policy, University of ManitobaDiagnostic Services Manitoba
KeywordsMedicineHazard ratioKidney diseaseInternal medicineCohortCohort studyRetrospective cohort studyHeart failureConfidence intervalSurgery

Abstract

fetched live from OpenAlex

ObjectiveLower limb complications are major adverse events in patients with peripheral artery disease (PAD) and chronic kidney disease (CKD). These complications can lead to morbidity, disability, reduced quality of life, and higher health care costs. We sought to determine how interim lower limb complications modify the subsequent risk of progression to kidney failure, all-cause mortality before kidney failure, and cardiovascular (CV) events in a cohort of patients with CKD stages G3 to G5.MethodsWe performed a retrospective cohort study using patient-level data obtained by linking several administrative databases from Manitoba, Canada. We used Fine and Gray regression models for the primary outcomes of (1) kidney failure adjusted for the competing risk of all-cause mortality, (2) death before kidney failure, and (3) cardiovascular-related hospitalization with the competing risk of non-CV death.ResultsA total of 92,618 patients were included in the final cohort, with a median follow-up time of 2.56 years. Compared with patients who did not experience an interim lower limb complication, there was a higher risk of kidney failure (adjusted hazard ratio [HR] 2.51, 95% confidence interval [CI] 2.10–3.00), all-cause mortality before kidney failure (adjusted HR 2.73, 95% CI 2.55–2.92), and CV events (adjusted HR 2.12, 95% CI 1.90–2.38).ConclusionsInterim lower limb complications are associated with an increased risk of kidney failure, all-cause mortality before kidney failure, and cardiovascular-related hospitalization. Clinical trials of screening and treatment strategies for patients with CKD at risk for lower limb complications may help determine optimal strategies to manage this risk. Lower limb complications are major adverse events in patients with peripheral artery disease (PAD) and chronic kidney disease (CKD). These complications can lead to morbidity, disability, reduced quality of life, and higher health care costs. We sought to determine how interim lower limb complications modify the subsequent risk of progression to kidney failure, all-cause mortality before kidney failure, and cardiovascular (CV) events in a cohort of patients with CKD stages G3 to G5. We performed a retrospective cohort study using patient-level data obtained by linking several administrative databases from Manitoba, Canada. We used Fine and Gray regression models for the primary outcomes of (1) kidney failure adjusted for the competing risk of all-cause mortality, (2) death before kidney failure, and (3) cardiovascular-related hospitalization with the competing risk of non-CV death. A total of 92,618 patients were included in the final cohort, with a median follow-up time of 2.56 years. Compared with patients who did not experience an interim lower limb complication, there was a higher risk of kidney failure (adjusted hazard ratio [HR] 2.51, 95% confidence interval [CI] 2.10–3.00), all-cause mortality before kidney failure (adjusted HR 2.73, 95% CI 2.55–2.92), and CV events (adjusted HR 2.12, 95% CI 1.90–2.38). Interim lower limb complications are associated with an increased risk of kidney failure, all-cause mortality before kidney failure, and cardiovascular-related hospitalization. Clinical trials of screening and treatment strategies for patients with CKD at risk for lower limb complications may help determine optimal strategies to manage this risk.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.046
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.217
Teacher spread0.210 · 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 teacher head, 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

Citations12
Published2020
Admission routes3
Has abstractyes

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