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Record W3159074659 · doi:10.1016/j.nephro.2020.02.008

Survival comparisons in home hemodialysis: Understanding the present and looking to the future

2021· review· en· W3159074659 on OpenAlexaff
Karthik Tennankore, Annie‐Claire Nadeau‐Fredette, Amanda J. Vinson

Bibliographic record

VenueNéphrologie & Thérapeutique · 2021
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsHôpital Maisonneuve-RosemontNova Scotia Health AuthorityDalhousie University
Fundersnot available
KeywordsHemodialysisHome hemodialysisObservational studyMedicineConfoundingRandomized controlled trialIntensive care medicineDialysisPeritoneal dialysisModalitiesTransplantationRenal replacement therapyInternal medicine

Abstract

fetched live from OpenAlex

A number of studies have compared relative survival for home hemodialysis patients (including longer hours/more frequent schedules) and other forms of renal replacement therapy. While informative, many of these studies have been limited by issues pertaining to their observational design including selection bias and residual confounding. Furthermore the few randomized controlled trials that have been conducted have been underpowered to detect a survival difference. Finally, in the face of a growing recognition of the value of patient-important outcomes beyond survival, the focus of comparisons between dialysis modalities may be changing. In this review, we will discuss the determinants of survival for patients receiving home hemodialysis and address the various studies that have compared relative survival for differing home hemodialysis schedules to each of in-center hemodialysis, peritoneal dialysis and transplantation. We will conclude this review by discussing whether there is an ongoing role for survival analyses in home hemodialysis.

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)0.019
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.038
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0030.006
Science and technology studies0.0000.002
Scholarly communication0.0020.005
Open science0.0020.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.101
GPT teacher head0.358
Teacher spread0.257 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations5
Published2021
Admission routes1
Has abstractyes

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