MétaCan
Menu
Back to cohort
Record W2025246651 · doi:10.1159/000186769

A Disease-Specific Questionnaire for Assessing Quality of Life in Patients on Hemodialysis

2008· article· en· W2025246651 on OpenAlexaff
Andreas Laupacis, Norman Muirhead, Paul Keown, Cindy J. Wong

Bibliographic record

Venue˜The œNephron journals/Nephron journals · 2008
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsRobarts Clinical TrialsUniversity of British ColumbiaWestern University
Fundersnot available
KeywordsMedicineQuality of life (healthcare)HemodialysisPhysical therapyPlaceboDiseaseDepression (economics)Psychological interventionRandomized controlled trialConstruct validityInternal medicineIntensive care medicinePsychometricsAlternative medicineClinical psychologyPsychiatryNursingPathology

Abstract

fetched live from OpenAlex

A disease-specific questionnaire was developed for patients receiving chronic hemodialysis by interviewing patients to determine which aspects of their quality of life were adversely affected by their disease. The final questionnaire contained 26 questions in five dimensions (physical symptoms, fatigue, depression, relationships with others, frustration). The questionnaire demonstrated construct validity when compared with the Sickness Impact Profile, time trade-off technique and an exercise stress test. It was reproducible in stable, placebo-treated patients (correlation coefficient 0.85-0.98 for the 5 dimensions). It was more responsive than other measures in detecting an improvement with erythropoietin therapy in a randomized, placebo-controlled trial. This questionnaire should be useful for the assessment of the effect of various interventions upon the quality of life of hemodialysis 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)0.003
metaresearch head score (Gemma)0.006
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 score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.076
GPT teacher head0.338
Teacher spread0.262 · 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

Citations166
Published2008
Admission routes1
Has abstractyes

Explore more

Same venue˜The œNephron journals/Nephron journalsSame topicDialysis and Renal Disease ManagementFrench-language works237,207