Position paper ANMCO: Cardiomiopatia ipertrofica: dalla diagnosi al trattamento
Bibliographic record
Abstract
Hypertrophic cardiomyopathy (HCM) is a non-rare genetic cardiomyopathy, with an estimated prevalence of 1:500, characterized by an increase in the left ventricular wall thickness in absence of increased loading conditions. The hypertrophy is mostly asymmetric and predominantly affects the basal septum and anterior wall. Left ventricular outflow tract obstruction, at rest or after provocative tests, is detected in many patients and represents the primary cause of reduced functional capacity, as well as an independent predictor of sudden cardiac death and advanced heart failure. Until about 1 year ago, symptomatic patients despite maximal therapy with beta-blockers or calcium channel blockers, with or without disopyramide, had only basal septal reduction therapy via myectomy or alcohol septal ablation as additional therapeutic options. Today, a new class of drugs that inhibit cardiac myosin activity is available for patients with obstructive HCM.In light of the new treatment perspectives, the correct clinical-therapeutic classification of affected patients becomes of fundamental importance for the cardiologist. The aim of this position paper is to increase the knowledge of cardiologists in the field of HCM, defining its epidemiological, genetic and pathological characteristics, identifying the diagnostic criteria and instrumental methods capable of stratifying the risk profile, with the aim of an optimal therapy tailored on the single patient.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.010 |
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".