Mechanical Circulatory Support as a Bridge to Transplant Candidacy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: The use of mechanical circulatory support (MCS) in nontransplant eligible candidates remains controversial. Our decision to offer MCS for nontransplant candidates has led to their reevaluation after a period of left ventricular assist device (LVAD) support. METHODS: From 2001 to September 2009, we had 37 patients who received an implantable LVAD, 22 (59%) were not deemed to be transplant eligible at the time of LVAD insertion (bridge to candidacy, BTC group). RESULTS: Fifteen (41%) patients were considered transplant eligible (bridge to transplant, BTT group) at the time of device insertion and received a HeartMate XVE (n = 7), HeartMate 2 (n = 7), or a Novacor LVAS (n = 1). In the BTC group, patients received the HeartMate XVE device (n = 11), HeartMate 2 (n = 5), or the Novacor LVAS (n = 6). The primary criterion for transplant ineligibility was refractory pulmonary hypertension (PH) in 18 patients, 3 patients did not meet our body mass index criteria (>35 kg/m(2)), and 2 patients were dialysis-dependent. Six (27%) BTC patients died on support. Overall, 16/22 patients (73%) were subsequently listed for transplantation, with one listed for combined heart-lung due to refractory PH. Twelve patients (75%) underwent successful heart transplantation. Three patients died during their transplant. Overall posttransplant survival at one year shows lower survival in the BTC group compared to the BTT group (67% vs. 100%, p = 0.05). At two years and three years the survival was lower, but not statistically different (BTC vs. BTT: 67% vs. 90% and 64% vs. 87%, respectively, p = NS). CONCLUSIONS: MCS can successfully convert a large proportion of transplant-ineligible patients into acceptable candidates.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it