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Record W4213281001 · doi:10.1038/s41581-022-00542-7

Epidemiology of haemodialysis outcomes

2022· review· en· W4213281001 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNature Reviews Nephrology · 2022
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of Alberta
FundersNational Health and Medical Research CouncilMedical Research CouncilUniversity of Alberta
KeywordsMedicineEpidemiologyRenal replacement therapyIntensive care medicineDialysisKidney diseaseQuality of life (healthcare)DiseaseHemodialysisMEDLINEPublic healthInternal medicinePathology

Abstract

fetched live from OpenAlex

Haemodialysis (HD) is the commonest form of kidney replacement therapy in the world, accounting for approximately 69% of all kidney replacement therapy and 89% of all dialysis. Over the last six decades since the inception of HD, dialysis technology and patient access to the therapy have advanced considerably, particularly in high-income countries. However, HD availability, accessibility, cost and outcomes vary widely across the world and, overall, the rates of impaired quality of life, morbidity and mortality are high. Cardiovascular disease affects more than two-thirds of people receiving HD, is the major cause of morbidity and accounts for almost 50% of mortality. In addition, patients on HD have high symptom loads and are often under considerable financial strain. Despite the many advances in HD technology and delivery systems that have been achieved since the treatment was first developed, poor outcomes among patients receiving HD remain a major public health concern. Understanding the epidemiology of HD outcomes, why they might vary across different populations and how they might be improved is therefore crucial, although this goal is hampered by the considerable heterogeneity in the monitoring and reporting of these outcomes across settings. This Review examines the epidemiology of haemodialysis outcomes — clinical, patient-reported and surrogate outcomes — across world regions and populations, including vulnerable individuals. The authors also discuss the current status of monitoring and reporting of haemodialysis outcomes and potential strategies for improvement.

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.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.960
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0140.006
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.108
GPT teacher head0.424
Teacher spread0.316 · 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