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Record W7036408695

Clinical trials for symptoms in patients receiving dialysis

2021· dissertation· en· W7036408695 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2021
Typedissertation
Languageen
FieldMedicine
TopicRestless Legs Syndrome Research
Canadian institutionsnot available
Fundersnot available
KeywordsClinical trialRandomized controlled trialKidney diseaseDialysisPlaceboNephrologyHemodialysisDisease
DOInot available

Abstract

fetched live from OpenAlex

Symptoms in patients receiving dialysis are common and associated with impaired quality of life. Symptoms are a top research priority because effective therapies are lacking and even with appropriate diagnosis and treatment, residual symptoms often persist. Clinical trials in the setting of kidney disease are challenging to conduct and as a result, nephrology lags behind other specialties regarding the degree to which clinical trials inform the care of patients with kidney disease, including those receiving dialysis. The studies in this thesis inform the design of randomized controlled trials with regards to run-in periods and the treatment of symptoms in patients with kidney disease. Chapter 2 describes a meta-epidemiologic study of the frequency, setting and purposes of run-in periods in parallel randomized controlled trials of self-administered medications for chronic diseases in adults. Chapter 3 is a study within a trial of an international randomized controlled trial that compares spironolactone to placebo for the prevention of cardiovascular morbidity and mortality in dialysis. It compares the ability of a 3-week study visit in addition to a 7-week study visit during an active-run-in period to identify and exclude participants with non-adherence. Chapter 4 is a protocol for a randomized placebo controlled crossover trial of low fixed dose pharmacologic therapy for restless legs syndrome in hemodialysis that includes a placebo run-in period for adherence and tolerability. Chapter 5 is a survey of Canadian nephrologists regarding the use of cannabinoids for symptom management in patients with kidney disease and support for their use in clinical trials.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.771
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0310.000

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 head0.084
GPT teacher head0.372
Teacher spread0.288 · 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 designObservational
Domainnot available
GenreOther

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
Published2021
Admission routes1
Has abstractyes

Explore more

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