Bibliographic record
Abstract
We read, with great interest, the audit of carotid endarterectomy by Findlay et al. 1 We agree with the authors that the current evidence suggests that the risk of stroke among individuals with asymptomatic carotid artery stenosis is relatively low and at present there are no proven criterion to identify a subgroup that will derive benefit from carotid endarterectomy.Henceforth, there is a general agreement among physicians that most of the asymptomatic patients should be managed conservatively and the most important step to prevent future strokes in these individuals is to detect and treat the vascular risk factors.In this regard, we would like to bring attention to another important observation by Inzitari et al (North A m e r i c a n Symptomatic Carotid Endarterectomy Trial collaborators).2 In their study, the authors concluded that not all the future strokes in the asymptomatic individuals will originate from stenosed internal carotid artery.Their findings suggested that almost half the strokes in the territory of an asymptomatic carotid artery are caused by lacunar and cardioembolic disease and are not of large artery origin.In this study, the investigators excluded the patients with cardiac diseases which can cause emboli.Consequently the number of cardioembolic strokes among patients with asymptomatic carotid artery stenosis was perhaps underestimated.This observation has two important clinical implications: 1) The decisions about carotid endarterectomy in asymptomatic patients should take into account the probable causes of future strokes as endarterectomy will not prevent the strokes of cardioembolic origin and lacunar strokes are less likely to be of large artery origin.2) In patients with asymptomatic carotid artery disease, the physicians should carefully look for and treat the potential cardiac embolic source, alongside management of vascular risk factors and patient education as advised by Findlay et al.
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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 | 0.002 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.023 | 0.018 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".