Optimizing Screening and Management of Asymptomatic Coronary Artery Disease in Patients With Stroke and Patients With Transient Ischemic Attack
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The feasibility of implementing an expert consensus guideline recommending use of a stroke patient's profile to manage undiagnosed coronary artery disease remains unclear. METHODS: Following a guideline-based algorithm, we screened consecutive patients with ischemic stroke and patients with transient ischemic attack for asymptomatic coronary artery disease using the Framingham Heart Study Coronary Risk Score (FCRS) cutoff of high risk (> or = 20%) for experiencing a hard coronary artery disease event over a 10-year period. Patients with high FCRS received dobutamine stress echocardiogram outpatient screening, additional treatment (beta-blocker), or further management (cardiologist referral). RESULTS: From July 2004 to September 2007, among 693 patients, 501 (72%) met study criteria, of which 80 (16%) had FCRS > or = 20%. Elevated serum glucose, nonhigh-density lipoprotein, triglycerides, homocysteine, glycosylated hemoglobin as well as large vessel atherosclerotic stroke mechanism were more frequent in high versus low FCRS patients (P<0.05). Among high FCRS patients, 35 (44%) had dobutamine stress echocardiogram performed. Leading reasons for dobutamine stress echocardiogram nonperformance were patient noncompliance (42%) and primary care physician refusal (33%). CONCLUSIONS: Screening for coronary artery disease risk using FCRS is feasible in hospitalized patients with stroke, but outpatient adherence to stress testing is challenging largely due to patient and primary care physician-related factors.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".