Stroke is a leading cause of death, and air pollution is associated with stroke hospitalization. However, the susceptibility factors are unclear. Retrospective studies from 2014 to 2018 in Kaohsiung, Taiwan, were analyzed. Adult patients (>17 years) admitted to a medical center with stroke diagnosis were enrolled and patient characteristics and comorbidities were recorded. Air pollutant measurements, including those of particulate matter (PM) with aerodynamic diameters < 10 μm (PM₁₀) and < 2.5 μm (PM_2.5), nitrogen dioxide (NO₂), and ozone (O₃), were collected from air quality monitoring stations. During the study period, interquartile range (IQR) increments in PM_2.5 on lag3 and lag4 were 12.3% (95% CI, 1.1–24.7%) and 11.5% (95% CI, 0.3–23.9%) concerning the risk of stroke hospitalization, respectively. Subgroup analysis revealed that the risk of stroke hospitalization after exposure to PM_2.5 was greater for those with advanced age (≥80 years, interaction p = 0.045) and hypertension (interaction p = 0.034), after adjusting for temperature and humidity. A dose-dependent effect of PM_2.5 on stroke hospitalization was evident. This is one of few studies focusing on the health effects of PM_2.5 for patients with risk factors of stroke. We found that patients with risk factors, such as advanced age and hypertension, are more susceptible to PM_2.5 impacts on stroke hospitalization.

Prediction of functional outcome in ischemic stroke patients is useful for clinical decisions. Previous studies mostly elaborate on the prediction of favorable outcomes. Miserable outcomes, which are usually defined as modified Rankin Scale (mRS) 5–6, should be considered as well before further invasive intervention. By using a machine learning algorithm, we aimed to develop a multiclass classification model for outcome prediction in acute ischemic stroke patients requiring reperfusion therapy. This was a retrospective study performed at a stroke medical center in Taiwan. Patients with acute ischemic stroke who visited between January 2016 and December 2019 and who were candidates for reperfusion therapy were included. Clinical outcomes were classified as favorable outcome, intermediate outcome, and miserable outcome. We developed four different multiclass machine learning models (Logistic Regression, Supportive Vector Machine, Random Forest, and Extreme Gradient Boosting) to predict clinical outcomes and compared their performance to the DRAGON score. A sample of 590 patients was included in this study. Of them, 180 (30.5%) had favorable outcomes and 152 (25.8%) had miserable outcomes. All selected machine learning models outperformed the DRAGON score on accuracy of outcome prediction (Logistic Regression: 0.70, Supportive Vector Machine: 0.67, Random Forest: 0.69, and Extreme Gradient Boosting: 0.67, vs. DRAGON: 0.51, p < 0.001). Among all selected models, Logistic Regression also had a better performance than the DRAGON score on positive predictive value, sensitivity, and specificity. Compared with the DRAGON score, the multiclass machine learning approach showed better performance on the prediction of the 3-month functional outcome of acute ischemic stroke patients requiring reperfusion therapy.

Few studies have reported on changes to oxidative stress and mitochondrial DNA copy numbers in patients with Parkinson’s disease (PD), particularly those undergoing long-term dopamine therapy. This study measured mitochondrial copy numbers, thiobarbituric acid reactive substances (TBARS), and thiols in 725 PD patients and 744 controls. The total prescribed dopamine dose was calculated for each PD patient. A decreased mitochondrial copy number and antioxidant thiols level, but an elevated oxidative TBARS level presented in PD patients. Stratification into age subgroups revealed a consistently lower mitochondrial copy number and thiols in all PD subgroups, but increased TBARS levels compared with those of the controls. Further study found an association between lower serum TBARS and dopamine administration. There appears to be an indirect relationship with the mitochondrial copy number, where a decrease in TBARS was found to diminish the effect of pathogenetic and age-related decrease in mitochondrial copy number in PD patients. Follow-up evaluations noted more significant decreases of mitochondrial copy numbers in PD patients over time; meanwhile, dopamine administration was associated with an initial decrease of the TBARS level which attenuated with high-dose and long-term therapy. Our study provides evidence that moderate dopamine dose therapy benefits PD patients through attenuation of oxidative stress and manipulation of the mitochondrial copy number.