Utility of the INTERMACS profile at the time of assessment for heart transplant
Bibliographic record
Abstract
The Interagency Registry of Mechanically Assisted Circulatory Support (INTERMACS) profiles are associated with mortality in heart failure patients undergoing ventricular assist device (VAD) implantation and heart transplantation (HTx). We assessed the prognostic value of the INTERMACS profile at the time of assessment for HTx or durable VAD implantation as bridge to candidacy (BTC). A total of 503 consecutive patients considered for HTx or VAD between 2006 and 2016 were included. The associations between INTERMACS profile and (a) waitlist mortality or delisting, (b) probability of HTx, and (c) overall mortality or delisting were evaluated using multivariable analysis. Median follow-up time was 2.9 years (IQR: 0.9-5.5) during which 184 received VAD, 347 received HTx, and 73 died (27 waitlist, 46 post-transplant). INTERMACS I-II profile was associated with higher waitlist mortality or delisting (HR: 3.83, 95% CI: 1.22-12.03), and this risk was reversed by VAD implantation (HR: 0.12, 95% CI: 0.03-0.50). INTERMACS III-IV profile was associated with a higher probability of HTx (HR: 1.82, 95% CI: 1.37-2.40). INTERMACS profile was not associated with the composite outcome of overall mortality or delisting. These results emphasize the prognostic utility of INTERMACS at time of decision for advanced therapies and its potential value in selecting patients for different interventions.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".