Incidence and Prognostic Implication of Unrecognized Myocardial Scar Characterized by Cardiac Magnetic Resonance in Diabetic Patients Without Clinical Evidence of Myocardial Infarction
Bibliographic record
Abstract
BACKGROUND: Silent myocardial infarctions (MIs) are prevalent among diabetic patients and inflict significant morbidity and mortality. Although late gadolinium enhancement (LGE) imaging by cardiac magnetic resonance (CMR) can provide sensitive characterization of myocardial scar, its prognostic significance in diabetic patients without any clinical evidence of MI is unknown. METHODS AND RESULTS: We performed clinically indicated CMR imaging in 187 diabetic patients who were grouped by the absence (study group, n=109) or presence (control group, n=78) of clinical evidence of MI (clinical history of MI or Q waves on ECG). CMR imaging and follow-up were successful in 107 study patients (98%) and 74 control patients (95%). Cox regression analyses were performed to associate LGE with major adverse cardiovascular events (MACE), including death, acute MI, new congestive heart failure or unstable angina, stroke, and significant ventricular arrhythmias. LGE by CMR was present in 30 of 107 study patients (28%). At a median follow-up of 17 months, 38 of 107 patients (36%) experienced MACE, which included 18 deaths. Presence of LGE was associated with a >3-fold hazards increase for MACE and for death (hazard ratio, 3.71 and 3.61; P<0.001 and P=0.007, respectively). Adjusted to a model that combines patient age, sex, ST or T changes on ECG, and left ventricular end-systolic volume index, LGE maintained a >4-fold hazards increase for MACE (adjusted hazard ratio, 4.13; 95% confidence interval, 1.74 to 9.79; P=0.001). In addition, LGE provided significant prognostic value with MACE and with death adjusted to a diabetic-specific risk model for 5-year events. The presence of LGE was the strongest multivariable predictor of MACE and death by stepwise selection in the study patients. CONCLUSIONS: CMR imaging can characterize occult myocardial scar consistent with MI in diabetic patients without clinical evidence of MI. This imaging finding demonstrates strong association with MACE and mortality hazards that is incremental to clinical, ECG, and left ventricular function combined.
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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".