Rationale and design of the Canadian Continuous Positive Airway Pressure Trial for Congestive Heart Failure patients with Central Sleep Apnea--CANPAP.
Bibliographic record
Abstract
BACKGROUND: Cheyne-Stokes respiration with central sleep apnea (CSR-CSA) is commonly observed in patients with congestive heart failure (CHF), in which it is an independent risk factor for death. Treating CSR-CSA may, therefore, improve outcomes in patients with CHF. OBJECTIVE: The Canadian Continuous Positive Airway Pressure Trial for Congestive Heart Failure Patients with Central Sleep Apnea (CANPAP) is a multicentre, randomized, controlled clinical trial designed to test the hypothesis that treating CSR-CSA with continuous positive airway pressure (CPAP) will reduce the combined rate of all-cause mortality and cardiac transplantation in patients with CHF. Secondary outcomes include the severity of CSR-CSA, left ventricular volumes and function, submaximal exercise capacity, quality of life and hospital admissions. PATIENTS AND METHODS: The aim is to enroll 408 patients with CHF (New York Heart Association class II to IV and left ventricular ejection fraction of less than 40%) and CSR-CSA over a five-year period. Patients are randomly assigned to either standard medical therapy for CHF or standard medical therapy plus CPAP. The trial has 80% power to detect a 35% between-group treatment difference for the all-cause mortality-cardiac transplantation rate. Substudies will assess the role of oximetry as a screening tool for detecting CSR-CSA in patients with CHF, and the effects of CPAP on cardiac arrhythmias and plasma concentrations of natriuretic peptides and catecholamines. CONCLUSIONS: The CANPAP trial will help to define the role of CPAP better as a nonpharmacological intervention for the treatment of patients with CHF who have CSR-CSA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.029 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".