Bibliographic record
Abstract
Introduction: Prophylactic implantation of a cardioverter/ defibrillator (ICD) has been shown to reduce mortality in patients with chronic myocardial infarction (CMI) and an increased risk for life threatening ventricular arrhythmia (VA). The use of ICDs in this large patient population is still limited by high costs and possible adverse events including inappropriate discharges and progression of heart failure. VA is related to infarct size and seems to be related to infarct morphology. Contrast enhanced cardiovascular magnetic resonance imaging (ceCMR) can detect and quantify myocardial fibrosis in the setting of CMI and might therefore be a valuable tool for a more accurate risk stratification in this setting. Hypothesis: ceCMR can identify the subgroup developing VA in patients with prophylactic ICD implantation following MADIT criteria. Methods: We prospectively enrolled 52 patients (49 males, age 69 10 years) with CMI and clinical indication for ICD therapy following MADIT criteria. Prior to implantation (36 78 days) patients were investigated on a 1.5 T clinical scanner (Siemens Avanto , Germany) to assess left ventricular function (LVEF), LV end-diastolic volume (LVEDV) and LV mass (sequence parameters: GRE SSFP, matrix 256 192, short axis stack; full LV coverage, no gap; slice thickness 6 mm). For quantitative assessment of infarct morphology late gadolinium enhancement (LGE) was performed including measurement of total and relative infarct mass (related to LV mass) and the degree of transmurality (DT) as defined by the percentage of transmurality in each scar. (sequence parameters: inversion recovery gradient echo; matrix 256 148, imaging 10 min after 0.2 g/kg gadolinium DTPA; slice orientation equal to SSFP). MRI images were analysed using dedicated software (MASS , Medis, Netherlands). LGE was defined as myocardial areas with signal intensity above the average plus 5 SD of the remote myocardium. After implantation, patients were followed up including ICD readout after 3 and than every 6 months for a mean of 945 344 days. ICD data were evaluated by an experienced electrophysiologist. Primary endpoint was the occurrence of an appropriate discharge (DC), antitachycard pacing (ATP) or death from cardiac cause. Results: The endpoint occurred in 10 patients (3 DC, 6 ATP, 1 death). These patients had a higher relative infarct mass (28 7% vs. 22 11%, p = 0.03) as well as high degree of transmurality (64 22% vs. 44 25%, p = 0.05). Their LVEF (29 8% vs. 30 4%, p = 0.75), LV mass (148 29 g vs. 154 42 g, p = 0.60), LVEDV (270 133 ml vs. 275 83 ml, p = 0.90) or total infarct mass (43 19 g vs. 37 21 g, p = 0.43) were however not significant from the group with no events. In a cox proportional hazards regression model including LVEF, LVEDV, LV mass, DT and age, only degree of transmurality and relative infarct mass emerged as independent predictors of the primary end point (p = 0.009).
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.584 | 0.420 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".