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Record W4383905405 · doi:10.1186/s12882-023-03264-5

Home hemodialysis technique survival: insights and challenges

2023· review· en· W4383905405 on OpenAlexaff
Estelle Tran, Oliver Karadjian, Christopher T. Chan, Emilie Trinh

Bibliographic record

VenueBMC Nephrology · 2023
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsMcGill UniversityUniversity Health NetworkMcGill University Health Centre
Fundersnot available
KeywordsMedicineDiscontinuationIntensive care medicineHemodialysisHome hemodialysisAttritionNephrologyQuality of life (healthcare)ModalitiesTreatment modalityDiseaseInternal medicineNursing

Abstract

fetched live from OpenAlex

Home hemodialysis (HHD) offers several clinical, quality of life and cost-saving benefits for patients with end-stage kidney disease. While uptake of this modality has increased in recent years, its prevalence remains low and high rates of discontinuation remain a challenge. This comprehensive narrative review aims to better understand what is currently known about technique survival in HHD patients, elucidate the clinical factors that contribute to attrition and expand on possible strategies to prevent discontinuation. With increasing efforts to encourage home modalities, it is imperative to better understand technique survival and find strategies to help maintain patients on the home therapy of their choosing. It is crucial to better target high-risk patients, examine ideal training practices and identify practices that are potentially modifiable to improve technique survival.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.112
GPT teacher head0.336
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 teacher head, not a consensus.

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

Citations23
Published2023
Admission routes1
Has abstractyes

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