Paradoxical Association of Smoking With In‐Hospital Mortality Among Patients Admitted With Acute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND: Compared to those who never smoked, a paradoxical effect of smoking on reducing mortality in patients admitted with myocardial ischemia has been reported. We sought to determine if this effect was present in patients hospitalized with ischemic stroke. METHODS AND RESULTS: Using the local Get with the Guidelines-Stroke registry, we analyzed 4305 consecutively admitted ischemic stroke patients (March 2002-December 2011). The sample was divided into smokers versus nonsmokers. The main outcome of interest was the overall inpatient mortality. Compared to nonsmokers, tobacco smokers were younger, more frequently male and presented with fewer stroke risk factors such as hypertension, hyperlipidemia, diabetes, coronary artery disease, and atrial fibrillation. Smokers also had a lower average NIH Stroke Scale (NIHSS) and fewer received tissue plasminogen activator (tPA). Patients in both groups had similar adherence to early antithrombotics, dysphagia screening prior to oral intake, and deep vein thrombosis (DVT) prophylaxis. Smoking was associated with lower all-cause in-hospital mortality (6.6% versus 12.4%; unadjusted OR 0.46; CI [0.34 to 0.63]; P<0.001). In multivariable analysis, adjusted for age, gender, ethnicity, hypertension, diabetes mellitus, hyperlipidemia, CAD, atrial fibrillation, NIHSS, and tPA, smoking remained independently associated with lower mortality (adjusted OR 0.64; CI [0.42 to 0.96]; P=0.03). CONCLUSIONS: Similar to myocardial ischemia, smoking was independently associated with lower inpatient mortality in acute ischemic stroke. This effect may be due to tobacco-induced changes in cerebrovascular vasoreactivity, or may be due in part to residual confounding. Larger, multicenter studies are needed to confirm the finding and the effect on 30-day and 1-year mortality.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".