Great debate: pre-diabetes is not an evidence-based treatment target for cardiovascular risk reduction
Bibliographic record
Abstract
With the increasing burden of diabetes as a cause of macro- and microvascular disease linked to the epidemics of obesity, attention is being paid to dysglycaemic states that predict and precede the development of type 2 diabetes. Such conditions, termed pre-diabetes, are characterized by fasting plasma glucose, or plasma glucose levels on an oral glucose tolerance test, or values of glycated haemoglobin intermediate between 'normal' values and those characterizing diabetes. These last are by definition associated, in epidemiological terms, with a higher incidence of microvascular disease-mostly retinopathy. Pre-diabetes overlaps with the components of the 'metabolic syndrome'-among which are excess visceral adiposity; hypertension; hypertriglyceridaemia; high levels of small, dense low-density lipoproteins; and metabolic-associated fatty liver disease. There is little doubt that pre-diabetes has important prognostic implications, especially for the occurrence of myocardial infarction, ischaemic stroke, and peripheral arterial disease. It is disputed, however, whether pre-diabetes is itself an actionable disease entity, in addition to the risk factors characterizing it. Because of this uncertainty, the latest European Society of Cardiology guidelines chose not to include pre-diabetes as a treatment target for atherosclerotic cardiovascular disease, at variance from the three previous editions of such guidelines. This is spurring a debate, the Pro and Contra arguments featured in the present debate article.
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 | 0.056 | 0.126 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.027 | 0.057 |
| Insufficient payload (model declined to judge) | 0.007 | 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".