Early myocardial damage assessment in dystrophinopathies using 99Tcm-MIBI gated myocardial perfusion imaging
Bibliographic record
Abstract
BACKGROUND: Early detection of muscular dystrophy (MD)-associated cardiomyopathy is important because early medical treatment may slow cardiac remodeling and attenuate symptoms of cardiac dysfunction; however, no sensitive and standard diagnostic method for MD at an earlier stage has been well-recognized. Thus, the aim of this study was to test the early diagnostic value of technetium 99m-methoxyisobutylisonitrile ((99)Tc(m)-MIBI) gated myocardial perfusion imaging (G-MPI) for MD. METHODS AND RESULTS: Ninety-one patients underwent (99)Tc(m)-MIBI G-MPI examinations when they were diagnosed with Duchenne muscular dystrophy (DMD) (n=77) or Becker muscular dystrophy (BMD; n=14). (99)Tc(m)-MIBI G-MPI examinations were repeated in 43 DMD patients who received steroid treatments for 2 years as a follow-up examination. Myocardial defects were observed in nearly every segment of the left ventricular wall in both DMD and BMD patients compared with controls, especially in the inferior walls and the apices by using (99)Tc(m)-MIBI G-MPI. Cardiac wall movement impairment significantly correlated with age in the DMD and BMD groups (r s=0.534 [P<0.05] and r s=0.784 [P<0.05], respectively). Intermittent intravenous doses of glucocorticoids and continuation with oral steroid treatments significantly improved myocardial function in DMD patients (P<0.05), but not in BMD patients. CONCLUSION: (99)Tc(m)-MIBI G-MPI is a sensitive and safe approach for early evaluation of cardiomyopathy in patients with DMD or BMD, and can serve as a candidate method for the evaluation of progression, prognosis, and assessment of the effect of glucocorticoid treatment in these patients.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".