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Record W2188945950 · doi:10.1177/089686080502500310

Nephrologists Should Voluntarily Divulge Survival Data to Potential Dialysis Patients: A Questionnaire Study

2005· article· en· W2188945950 on OpenAlexaff
Adrian Fine, Bunny Fontaine, Maryann M. Kraushar, Beverly R. Rich

Bibliographic record

VenuePeritoneal Dialysis International · 2005
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicinePeritoneal dialysisDialysisInternal medicineIntensive care medicineFamily medicineEmergency medicine

Abstract

fetched live from OpenAlex

BACKGROUND: For many dialysis patients, survival is no different than with certain cancers. Yet, it appears that most nephrologists do not give detailed information about survival prior to obtaining informed consent for chronic dialysis. There are no published data on whether patients wish to be so informed. OBJECTIVE: To assess whether patients would want voluntary disclosure by their physician of their survival should they need dialysis, and if so, why? METHOD: A questionnaire was completed by 100 general nephrology patients during their first visit to a nephrologist. RESULTS: The vast majority of patients (97%) would want to be given life-expectancy information, and for the physician to do so without having to be prompted. Furthermore, the majority of patients would want as much information as possible, both good and bad. CONCLUSIONS: Virtually all patients want, and therefore should receive from their physician, prognostic information about dialysis to facilitate informed decision-making. This is in accordance with current practice guidelines.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0030.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.219
GPT teacher head0.448
Teacher spread0.229 · 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; both teacher heads agree on what is shown here.

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

Citations83
Published2005
Admission routes1
Has abstractyes

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