Abstract 14106: Prevalence and Respective Predictive Value of Late Gadolinium Enhancement Phenotypes in Patients Referred for Suspected Infiltrative Cardiomyopathy
Bibliographic record
Abstract
Introduction: The respective value of different late gadolinium enhancement (LGE) phenotypes in patients with suspected infiltrative cardiomyopathy remains uncertain. Methods: In a large cohort of patients referred for suspected infiltrative cardiomyopathy, we evaluated respective associations between the dominant LGE phenotype and the composite endpoint of heart failure hospitalization, survived cardiac arrest or death. Kaplan-Meier survival curves were executed for six pre-defined LGE phenotypes. Multivariable analysis was performed to assess their independent association with the composite outcome, adjusted for relevant confounders. Final diagnosis was adjudicated using standardized disease-specific criteria. Results: 588 patients (68% male, median age 70 years, mean LVEF 54.7±12.7%) were studied. Of these patients, 139 (24%) were confirmed to have cardiac amyloidosis (CA) (81 [58%] transthyretin, 54 [39%] light chain and 4 [3%] undifferentiated) by objective non-CMR diagnostic criteria. Any LGE was present in 394 patients (67%) with the dominant phenotype being diffuse in 137 (23%), mid-wall patchy in 118 (20%), ischemic in 55 (9.4%), subepicardial in 18 (3.1%), mid-wall striae in 8 (1.4%), and RV insertion site in 58 (9.9%). The sensitivity and specificity of diffuse LGE for CA was 86% and 96%, respectively. Over a median 855 (IQR 372, 1542) days, 239 (41%) experienced the primary outcome. Unadjusted survival curves for each LGE phenotype are shown in the Figure. Following adjustment, diffuse (HR 2.30, p<0.001), mid-wall patchy (HR 1.52, p=0.040) and ischemic LGE (HR 1.78, p=0.023) remained independently associated (Figure). Conclusions: In patients referred for suspected infiltrative cardiomyopathy, diffuse, mid-wall patchy and ischemic patterns all showed independent prognostic value. We confirm that diffuse LGE pattern reliably identifies CA patients with high sensitivity and specificity while delivering strong prognostic value.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".