MétaCan
Menu
Back to cohort
Record W2807872429 · doi:10.1177/2054358118778568

End-Stage Kidney Disease in Patients With Autosomal Dominant Polycystic Kidney Disease: A 12-Year Study Based on the Canadian Organ Replacement Registry

2018· article· en· W2807872429 on OpenAlexaffabout
Brandon Budhram, Ayub Akbari, Pierre Antoine Brown, Mohan Biyani, Greg Knoll, Deborah Zimmerman, Cedric Edwards, Brendan McCormick, Ann Bugeja, Manish M. Sood

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsInstitute for Clinical Evaluative SciencesOttawa HospitalUniversity of Ottawa
FundersOtsuka Pharmaceutical
KeywordsMedicineAutosomal dominant polycystic kidney diseaseRenal replacement therapyDialysisKidney transplantationKidney diseaseNephrologyTransplantationInternal medicineOdds ratioPopulationHome hemodialysisPeritoneal dialysisHazard ratioPolycystic kidney diseaseHemodialysisKidneyConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease, with afflicted patients often progressing to end-stage kidney disease (ESKD) requiring renal replacement therapy (RRT). As the timelines to ESKD are predictable over decades, it follows that ADPKD patients should be optimized regarding kidney transplantation, home dialysis therapies, and vascular access. OBJECTIVES: To examine the association of kidney transplantation, dialysis modalities, and vascular access in ADPKD patients compared with a matched, non-ADPKD cohort. SETTING: Canadian patients from 2001-2012 excluding Quebec. PATIENTS: All adult incident ESKD patients who received dialysis or a kidney transplant. MEASUREMENTS: ADPKD as defined by the treating physician. METHODS: ADPKD and non-ADPKD patients were propensity score (PS) matched (1:4) using demographics, comorbidities, and lab values. Conditional logistic regression and Cox proportional hazards models were used to examine associations with kidney transplantation (preemptive or any), dialysis modality (peritoneal, short daily, home, or in-center hemodialysis [HD]), vascular access (arteriovenous fistula [AVF], permanent or temporary central venous catheter [CVC]), and dialysis survival. RESULTS: We matched 2120 ADPKD (99.9%) with 8283 non-ADPKD with no significant imbalances between the groups. ADPKD was significantly associated with preemptive kidney transplantation (odds ratio [OR] = 7.13, 95% confidence interval [CI] = 5.74-8.87), any kidney transplant (OR = 2.37, 95% CI = 2.14-2.63), and initial therapy of nocturnal daily HD (OR = 2.74, 95% CI = 1.38-5.44), whereas in-center intermittent HD was significantly less likely in the ADPKD population (OR = 0.59, 95% CI = 0.54-0.65). There was no difference in peritoneal dialysis (PD) as initial RRT but lower use of any PD among the ADPKD group (OR = 0.85, 95% CI = 0.77-0.95). ADPKD patients were significantly more likely to have an AVF (OR = 3.25, 95% CI = 2.79-3.79) and less likely to have either a permanent (OR 0.68, 95% CI 0.59-0.78) or temporary (OR = 0.49, 95% CI = 0.41-0.59) CVC as compared with the non-ADPKD cohort. Survival on either in-center HD or PD was better for ADPKD patients (HD: hazard ratio [HR] 0.48, 95% CI 0.44-0.53; PD: HR 0.73, 95% CI 0.60-0.88). LIMITATIONS: Conservative care patients were not captured; despite PS matching, the possibility of residual confounding remains. CONCLUSIONS: ADPKD patients were more likely to receive a kidney transplant, use home HD, dialyze with an AVF, and have better survival relative to non-ADPKD patients. Conversely, they were less likely to receive PD either as initial therapy or anytime during ESKD. This may be attributed to higher transplantation or clinical decision-making processes susceptible to education and intervention.

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 score0.054
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.006
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.007
GPT teacher head0.230
Teacher spread0.223 · 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

Citations12
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Kidney Health and DiseaseSame topicGenetic and Kidney Cyst DiseasesFrench-language works237,207