Commentary: Effect of aspirin in patients with established asymptomatic carotid atherosclerosis: a systematic review and meta-analysis
Bibliographic record
Abstract
There was a fatal flaw in the review by Hu et al.,(Hu et al., 2022) who reported that aspirin did not slow progression of carotid intima-media thickness (IMT) and did not reduce the risk of cardiovascular events in patients with carotid IMT. They studied IMT, which is biologically, (Spence, 2015) genetically, (Pollex and Hegele, 2006) and pathologically (Finn et al., 2010) distinct from atherosclerosis. (Spence, 2020) The journal Atherosclerosis has established a policy that IMT must not be referred to as "preclinical atherosclerosis". It should be referred to as ""arterial injury" or "arteriopathy", not "atherosclerosis". (Raggi and Stein, 2020) IMT is a much weaker predictor of myocardial infarction (Johnsen et al., 2007) or stroke (Mathiesen et al., 2011) than carotid plaque burden, measured as total plaque area (TPA). Indeed, carotid plaque burden is strongly associated with, (Sillesen et al., 2012) and as predictive of cardiovascular risk (Baber et al., 2015) as a coronary calcium score. IMT is neither. (Sillesen et al., 2012, Baber et al., 2015 Among patients referred for cardiovascular prevention whose TPA was in the top quartile (> 119 mm 2 ), the 5-year risk of stroke, myocardial infarction or vascular death was 19.5%, after adjusting for baseline risk factors. (Spence et al., 2002) It is extremely likely that aspirin would reduce cardiovascular risk in such high-risk patients with true atherosclerosis.
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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 | 0.013 | 0.086 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.010 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".