Effects of cigarette smoking on older chinese men treated with clopidogrel monotherapy or aspirin monotherapy: a prospective study

Impact of Stroke Severity on the Smoking Paradox in Patients Treated with Intravenous Thrombolysis

OBJECTIVE

To our knowledge, no previous studies have investigated the impact of stroke severity on the smoking paradox after intravenous thrombolysis (IVT). We aimed to explore the contribution of stroke severity to the association between smoking and stroke prognosis after IVT.

METHODS

We enrolled consecutive patients who received IVT within 4.5 hours from stroke onset. A logistic regression model was used to estimate the unadjusted and adjusted odds ratios (ORs) with their 95% confidence intervals (CIs) for poor functional outcome and mortality at 3 months.

RESULTS

Among patients with moderate stroke, smokers experienced a lower risk of 3-month poor outcomes than non-smokers (33.0% vs. 44.4%, unadjusted OR: 0.616; 95% CI: 0.402-0.945). However, among those with severe stroke, smokers had a higher risk of 3-month poor outcomes than non-smokers (81.6% vs. 55.9%, unadjusted OR: 3.496; 95% CI: 1.207-10.127). After adjustment, the negative correlation between smoking and 3-month poor outcome following IVT lost statistical significance in patients with moderate stroke (OR: 0.677 [95% CI: 0.418-1.097]). However, smoking remained a risk factor for 3-month poor outcomes in patients with severe stroke (OR: 4.216 [95% CI: 1.236-14.385]). We also observed a significant interaction between smoking and stroke severity with regard to the risk of poor functional outcomes (p=0.023). However, no such interaction influenced mortality (p=0.901).

CONCLUSION

Stroke severity affects the association between smoking and 3-month clinical functional outcomes following IVT.

A Novel Clinical Nomogram to Predict Transient Symptomatic Associated with Infarction: The ABCD3-SLOPE Score

Background

It is hard to differentiate transient symptoms associated with infarction (TSI) from transient ischemic stroke (TIA) without MRI in the early onset. However, they have distinct clinical outcomes and respond differently to therapeutics. Therefore, we aimed to develop a risk prediction model based on the clinical features to identify TSI.

Methods

We enrolled 230 consecutive patients with transient neurologic deficit in the Department of Neurology, Tongji University Affiliated Tenth People's Hospital from March 2014 to October 2019. All the patients were assigned into TIA group (DWI-negative) or TSI group (DWI-positive) based on MRI conducted within five days of onset. We summarized the clinical characteristics of TSI by univariate and multivariate analyses. And then, we developed and validated a nomogram to identify TSI by the logistic regression equation.

Results

Of the 230 patients, 41.3% were diagnosed with TSI. According to the multivariate analysis, four independent risk factors, including smoking history, low-density lipoprotein cholesterol, brain natriuretic peptide precursor, and ABCD3 score, were incorporated into a nomogram. We developed a predictive model named ABCD3-SLOPE. The calibration curve showed good agreement between nomogram prediction and observation. The concordance index (C-index) of the nomogram for TSI prediction was 0.77 (95% confidence interval, 0.70-0.83), and it was well-calibrated.

Conclusions

Smoking history, low-density lipoprotein cholesterol, brain natriuretic peptide precursor, and ABCD3 score were reliable risk factors for TSI. ABCD3-SLOPE was a potential tool to quantify the likelihood of TSI.