Troponin T and I are not reliable markers of cardiac transplant rejection
Bibliographic record
Abstract
OBJECTIVE: Heart transplant recipients undergo a number of invasive endomyocardial biopsies to screen for rejection. Serum assays of troponin T and/or I may provide a less invasive alternative. The purpose of this study was to evaluate troponin T and I as markers of cardiac transplant rejection. METHODS: We conducted a prospective analysis comparing troponin T and I levels to biopsy results in heart transplant recipients. Plasma was assayed for troponin T and I preoperatively, on the first 3 postoperative days, and with each subsequent biopsy. RESULTS: Twenty-nine patients entered the study. A total of 173 biopsies were performed at a mean follow-up of 129+/-9 days (range: 12-564 days). There were two rejection episodes (> or = grade 3), one in each of two patients. There were no significant relationships between troponin T or I and biopsy-proven rejection (> or = grade 3; P=0.59 and 0.54, respectively). There were also no correlations between troponin T or I levels and biopsy grade (P=0.40 and 0.92, respectively). Troponin T and I levels peaked on postoperative day 1 and fell to baseline over long-term follow-up with no peak in serum markers associated with rejection episodes. Donor ischemic time was significantly correlated to troponin T on postoperative days 1-3 (r=0.58, P=0.005; r=0.61, P=0.004; and r=0.61, P=0.003, respectively). CONCLUSIONS: Troponin T and I are not useful indicators of cardiac rejection, but do correlate with donor heart ischemic injury.
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 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".