Italian Association of Hospital Cardiologists position paper—obesity in adults: a clinical primer
Bibliographic record
Abstract
Obesity is a chronic and relapsing disease characterized by the interaction between individual predispositions and an obesogenic environment. Recent advances in understanding the mechanisms of energetic homoeostasis paved the way to more effective therapeutic approaches compared with traditional treatments. Since obesity is a complex disease, it necessitates a multi-disciplinary approach whose implementation remains challenging. Nonetheless, emerging pharmacological interventions appear promising. Currently, therapeutic success is discreet in the short term but often fails to maintain long-term weight loss due to a high likelihood of weight regain. Cardiologists play a key role in managing patients with obesity, yet often lack familiarity with its comprehensive management. The aim of this document is to summarize knowledge to consolidate essential knowledge for clinicians to effectively treat patients living with obesity. The paper emphasizes the pivotal role of a strong patient-clinician relationship in navigating successful treatment. We analyse the criteria commonly used to diagnose obesity and point out the strengths and limitations of different criteria. Furthermore, we discuss the role of obesiologists and the contributions of cardiologists. In addition, we detail key components of effective therapeutic strategies, including educational aspects and pharmacological options.
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 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".