The inflammatory and nutritional status in patients with dilated cardiomyopathy: Different impact for distinct phenogroups?
Bibliographic record
Abstract
Dilated cardiomyopathy Phenogroups InflammationThis editorial refers to 'Prognostic value of preoperative highsensitivity C-reactive protein to albumin ratio in patients with dilated cardiomyopathy receiving pacemaker therapy: A retrospective twocenter study in China', by Pan et al [1].Dilated cardiomyopathy (DCM) is the most common non-ischemic cardiomyopathy and the most frequent cause of heart failure in patients under 40 years of age [2].While clinical presentation and aetiological landscape of DCM is manifold, current treatment options focus on general heart failure management only.The first European Society of Cardiology guidelines for the management of cardiomyopathies were published in 2023 and provide specific diagnostic definitions in DCM, further including the new 'non-dilated left ventricular cardiomyopathy' (NDLVC) phenotype [3].While an individualized treatment approach is forwarded, current pharmacological and device-based treatment recommendations for DCM still align with the general heart failure recommendations, mainly guided on left ventricular ejection fraction (LVEF) [4].Recommendations still fail to consider genetics, epigenetics, inflammation, haematopoiesis and extended functional parameters including diastolic heterogeneity, amongst others.An adequate consideration of the underlying pathophysiological heterogeneity in DCM would require novel diagnostic frameworks, targeted research and adapted treatment approaches to bridge the gap in individualized care.Thus, there remains a vast, yet untapped potential for advancing both therapeutic and diagnostic strategies for DCM patients.Recently, a two-hit hypothesis proposed that DCM develops due to the coexistence of an underlying genetic abnormality and additional driving factors (e.g., myocarditis, clonal haematopoiesis and others) rather than by monogenetic variants alone (Fig. 1) [2,5].Various driving factors have been identified that, often in conjunction with a pathogenic background, culminate in clinically manifest DCM.However, the complex genotype-phenotype patterns are still incompletely understood.Currently pragmatic and non-individualized treatment regimens are
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".