Tratamiento de la obesidad: necesidad de centrar la atención en los pacientes de alto riesgo caracterizados por la obesidad abdominal
Bibliographic record
Abstract
Abdominal obesity is associated with metabolic abnormalities, increasing the risk of type 2 diabetes and coronary artery disease (CAD). The Quebec Cardiovascular Survey demonstrated that the atherogenic metabolic triad (AMT) present in abdominally obese (AO) males increases the risk of CAD 20-fold over the course of 5 years. An early detection algorithm was developed to identify individuals presenting these atherogenic abnormalities. It was found that the association of large waist circumference (WC) and moderate hypertriglyceridemia (the "hypertriglyceridemic waist", or HW) could adequately identify a significant portion of individuals with the AMT. It is important to note that even in the absence of classic risk factors, abdominally obese patients can present increased risk of CAD if they have HW. Finally, it has been suggested that the risk of developing an acute coronary syndrome in AO patients is not always related to the degree of coronary stenosis, and the patient s atherothrombotic/inflammatory profile should be taken into account in evaluating risk. Stabilization of the atherosclerotic plaque would become a legitimate therapeutic objective, and more feasible for prevention of CAD, in AO patients.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".