Abstract T MP98: Guideline-directed LDL Management Prior to Onset of Acute Ischemic Stroke in Patients with and Without Pre-existing Cardiovascular Disease: Findings from GWTG-stroke
Bibliographic record
Abstract
Context: Limited information is available whether high risk patients had achieved guideline-directed LDL goals prior to presenting with an acute ischemic stroke. Objective: To evaluate differences in the attainment of current LDL guidelines, based on admission LDL testing, in patients with acute ischemic stroke. Methods: Observational study, using data from the AHA-Get With The Guidelines Registry including 913,436 patients with an acute ischemic stroke or transient ischemic attack from April 2003 to September 2012. Participants were classified as high risk if they had prior history of TIA, stroke, and/or coronary artery disease (CAD). We used a previously created algorithm to determine the pre-stroke NCEP ATP-III goal. Results: Of the 913,436 patients admitted with an acute stroke or TIA, 283,162 (31.0%) had prior stroke/TIA, and 148,833 (16.3%) had prior CAD. Overall, only 68% of stroke patients were at their pre-admission NCEP III guideline-recommended LDL target on admission testing; 51.3% had LDL <100 mg/dL and only 19.8% had LDL100 mg/dL. Compared to patients with CAD, patients with prior TIA/Stroke were less likely to have LDL <100 mg/dL or <70 mg/dL (Table 1). In multivariable analysis, older age, male, white race, lack of major vascular risk factors, prior use of cholesterol-lowering therapy, and care provided in larger hospitals or West/Midwest hospitals were associated with meeting NCEP III LDL targets on admission testing. Conclusion: Current management of dyslipidemia in high risk patients with pre-existent CAD or stroke continues to be suboptimal. Only one in four patients with prior TIA/Stroke have LDL levels at the strict target <70 mg/dL.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".