A trial for destination therapy - investigation of non-transplant-eligible patients who are inotrope dependant (INTRePID)
Bibliographic record
Abstract
The INTrEPID (Investigation of Non-Transplant-Eligible Patients who are Inotrope Dependant) trial is designed to determine if continuous support with a left ventricular assist system (Novacor LVAS, World Heart Corporation) can reduce mortality and. improve quality of life in end-stage heart failure patients who are dependent on I.V. inotropes and who are ineligible for transplantation. The INTrEPID trial is a FDA approved, prospective, multi-centre, non-randomized controlled trial. The trial consists of two arms, the Device Group (those who receive the Novacor LVAS), and the Control Group (made up of patients meeting all of the entry criteria, but who either, refuse LVAS implantation, do not have access to a device, or have a mechanical aortic valve). The primary endpoint is all cause mortality at 6 months, with secondary endpoints of cardiac mortality at 6 months and health related quality of life assessments. Target enrollment is 110 subjects (55 Device and 55 Control) at 20 Centres. The trial's feasibility phase (approved for 55 subjects at 10 Centres) is currently underway. To date 42 subjects (14 control group patients and 28 device group patients) have been enrolled. In conclusion, the trial design, target population, inclusion and exclusion criteria, treatment plans and end-points will be discussed.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".