Abstract 213: The Smoking Paradox in Acute Ischemic Stroke: Findings from Get With The Guidelines - Stroke
Bibliographic record
Abstract
Introduction: Smoking doubles the risk of acute ischemic stroke (AIS) and has been associated with lower in-hospital mortality in patients with myocardial infarction and heart failure. We investigated the association of smoking and mortality in AIS patients in Get With The Guidelines (GWTG)-Stroke. Methods: We analyzed all AIS patients (n=899,295) without a prior history of CAD from 04/2003-10/2012 in GWTG-Stroke. Categorical data were analyzed by Pearson Chi-square and continuous data by Wilcoxon test. Multivariable models with generalized estimating equations for in-hospital clustering were used to estimate odds ratios of in-hospital mortality. All significant predictors on univariate analysis were included in the multivariable model. Results: Among all AIS patients, 20% were current smokers, defined as any cigarette use in the past year. Smokers were substantially younger (13 years), more often male, with fewer vascular risk factors and comorbid conditions. When recorded, median NIHSS was lower. Smokers were more likely to be admitted to large, academic hospitals, and more often in the South and Midwest. Both groups received a similar frequency of evidence based in-hospital interventions. In-hospital mortality was lower amongst smokers (Table 1). The significant univariate mortality difference attenuated dramatically after adjusting for age and other covariates in the multivariable model, OR increased from 0.56 (0.54, 0.58) on univariate analysis to 0.87 (0.84, 0.91) on multivariable model. Other independent predictors of mortality were increasing age [1.10 (1.08, 1.11) per 10 yr], male gender [1.17 (1.14 - 1.20)], white race [1.18 (1.14 - 1.23)], higher initial NIHSS [1.13 (1.12 - 1.13) per point], atrial fibrillation [1.29 (1.25 - 1.33)], PVD [1.15 (1.08 - 1.23)] and DM [1.12 (1.09 - 1.16)]. Conclusion: Smoking continues to be a major risk factor for presenting with acute ischemic stroke at a much younger age and with fewer vascular risk factors. The association with lower in-hospital mortality, even after covariate adjustment, may represent residual confounding due to the marked age differences and unmeasured confounding or it may reflect a protective association. Further research is warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".