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Record W4397043956 · doi:10.1681/asn.20233411s1180b

The Effect of Implementing a Dialysis Start Unit on Modality Decision Among Patients with Urgent Start Kidney Replacement Therapy

2023· article· en· W4397043956 on OpenAlexaffabout
Shira Goldman, Joanne M. Bargman, Charmaine E. Lok, Anna Goździk, Jeffrey Perl, Christopher T. Chan

Bibliographic record

VenueJournal of the American Society of Nephrology · 2023
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsSt. Michael's HospitalToronto General HospitalUniversity of Toronto
Fundersnot available
KeywordsRenal replacement therapyMedicineModality (human–computer interaction)DialysisIntensive care medicineDialysis TherapyUnit (ring theory)NephrologyTreatment modalityPeritoneal dialysisKidney diseaseUrologyInternal medicinePsychologyComputer science

Abstract

fetched live from OpenAlex

Background: Many individuals start dialysis in an acute setting with suboptimal pre-dialysis education. The dialysis start unit (DSU) is a program performing in-center hemodialysis (HD) in a separate space while providing support and education on chronic kidney disease and treatment options in the initial weeks of kidney replacement therapy. We aimed to assess the uptake of home dialysis therapies between 2013-2021 among patients who started acute inpatient HD at University Health Network, Toronto and underwent dialysis at the DSU. Methods: This is a retrospective observational cohort study based on prospectively collected data. Patients’ demographics were obtained from electronic charts. In the DSU, all patients received dialysis modality education by a nurse educator, dedicated home dialysis nurses, and the allied health care team. Results: During 2013-2021, 122 patients were dialyzed in the DSU and included in the study. Among those patients, 68 patients ultimately chose home dialysis (57 peritoneal dialysis and 11 home HD). Fifty-four patients continued in-center HD. Patients adopting home dialysis were less likely to have diabetes and hypertension as the etiology of kidney failure and more likely to have glomerulonephritis or vasculitis. Conclusions: Dialysis modality education is implementable in advanced chronic kidney disease. Individualized education and care after urgent start dialysis can potentially enhance home dialysis choice and utilization. - Home dialysis (n=68) In center hemodialysis (n=54) Mean age at start of dialysis, years 52.9+/-23.5 56.7+/-17.8 Gender, male 36 (53%) 33 (61%) Etiology of Kidney failure Diabetes / hypertension 12 (18%) 16 (30%) Failed kidney transplant 9 (13%) 11 (20%) Glomerulonephritis / vasculitis 21 (31%) 8(15%) Other 18 (26%) 12 (22%) Unknown 8 (12%) 7 (13%) Followed by nephrologist before admission No 27 (40%) 22 (41%) General nephrology 12 (18%) 11 (20%) Pre-dialysis clinic 25 (37%) 15 (28%) Transplant clinic* 4 (6%) 6 (11%) *as the only nephrology follow-up Patients demographics and comorbiditiesModality selection among DSU patients

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)0.010
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 score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.013
GPT teacher head0.286
Teacher spread0.273 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

Explore more

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