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Record W4390675329 · doi:10.2215/cjn.0000000000000413

The Burden of Home Dialysis

2024· review· en· W4390675329 on OpenAlexaff
Emilie Trinh, Karine Manera, Nicole Scholes‐Robertson, Jenny I. Shen

Bibliographic record

VenueClinical Journal of the American Society of Nephrology · 2024
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicinePsychosocialDialysisQuality of life (healthcare)Home dialysisIntensive care medicineCaregiver burdenBurnoutNursingDiseasePsychiatry

Abstract

fetched live from OpenAlex

Home dialysis offers several clinical and quality-of-life benefits for patients with kidney failure. However, it is important to recognize that home dialysis may place an increased burden on patients and their care partners. Sources of burden may include concerns about the ability to adequately and safely perform dialysis at home, physical symptoms, impairment of life participation, psychosocial challenges, and care partner burnout. Overlooking or failing to address these issues may lead to adverse events that negatively affect health and quality of life and reduce longevity of home dialysis. This study will explore aspects of home dialysis associated with burden, emphasize the need for increased awareness of potential challenges, and elaborate on strategies to overcome sources of burden. Future research should actively involve patients and care partners to better understand their motivation, experiences, and needs to better inform support strategies.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.065
GPT teacher head0.420
Teacher spread0.354 · 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 designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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