A prospective study of dobutamine stress echocardiography for the assessment of cardiac allograft vasculopathy in pediatric heart transplant recipients
Bibliographic record
Abstract
Transplant CAV is the leading cause of graft loss beyond one yr post-heart transplant. Diagnosis can be challenging and the previous "gold standard," coronary ANG, tends to underestimate disease. The purpose of this study was to relate DSE to ANG for the diagnosis of CAV. Prospective annual DSE at a single centre on all heart transplant patients (1999-2006) were compared with results from routine coronary angiograms. Progression of CAV over time as determined by DSE and ANG and associated factors were sought through logistic regression models adjusted for repeated measures. There were 102 heart transplant patients (54 males) transplanted between 1989 and 2006. Median age at transplant was 17 months (0-16.6 yr). The initial DSE was at a median of 10-months post-transplantation. There was a high correlation between an abnormal DSE and an abnormality on ANG (p = 0.002). There was an increased probability of an abnormal DSE with increasing grade of CAV as assessed by ANG (p < 0.001). Factors associated with an abnormal DSE included older age at transplant (p = 0.04), higher grade of rejection (p = 0.002), higher total cholesterol (p = 0.04), higher LDL (p < 0.05), and older age at the time of DSE (p = 0.002). DSE result was not related to HDL, triglyceride or homocysteine levels, or to steroid or statin use. The probability of an abnormal DSE result increases with increasing angiographic grade of CAV, and thus DSE may be used for initial screening for CAV with ANG reserved for confirmation and grading. Patients transplanted at an older age and those with a greater history of rejection were at higher risk of a positive DSE and may require increased surveillance for CAV.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".