Prognostic value of myocardial T2 mapping post reperfused acute myocardial infarction
Bibliographic record
Abstract
Methods Fifty-four patients were enrolled post primary percutaneous coronary intervention (PCI) and underwent CMR on a 1.5T scanner at 48 hours. Myocardial edema was quantified using a T2 mapping technique, while infarct size was assessed via a contrast-enhanced T1-weighted inversion recovery gradient-echo sequence. Information regarding four clinical outcomes: a) mortality, b) repeat myocardial infarction, c) heart failure hospitalization and d) repeat revascularization was collected at 12 months post index primary PCI. Our primary clinical endpoint was a composite of these 4 outcome measures of major adverse cardiovascular events (MACE). The Cox proportional hazards regression model was used to calculate the relative risk of MACE for increased T2 values, adjusted for baseline characteristics related to increased edema (diabetes status, symptom to balloon time, infarct size). Results The mean age was 59.6 ± 8.2 years, 88% were males, 35% were diabetics, 44% were hypertensive. The mean symptom to balloon time was 395 ± 230 minutes and mean door to balloon time was 81.5 ± 39 minutes. The mean T2 value was higher in the infarct segment compared to remote segment (55.1 ± 7.6 ms vs 40.2 ± 2.6 ms, p<0.001). Patients with MACE (n=12) had higher infarct segment T2 values compared to patients that did not (64.4 ± 7.3 ms vs 51.1 ± 5.8 ms, p<0.001). After adjustment for variables associated with increased edema, a T2 value of ≥ 62 ms was associated with a hazard ratio of 1.04 (95% CI:1.01-1.07, p=0.009) for MACE at 12 months (Table 1). Conclusions In reperfused STEMI patients, higher T2 values in the infarct segment are associated with worse prognosis. This suggests the need to develop therapies aimed at reducing myocardial edema post acute myocardial infarction.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".