Background. SARS-CoV-2 infected patients are suggested to have a higher incidence of thrombotic events such as acute ischemic strokes (AIS). This study aimed at exploring vascular comorbidity patterns among SARS-CoV-2 infected patients with subsequent stroke. We also investigated whether the comorbidities and their frequencies under each subclass of TOAST criteria were similar to the AIS population studies prior to the pandemic. Methods. This is a report from the Multinational COVID-19 Stroke Study Group. We present an original dataset of SASR-CoV-2 infected patients who had a subsequent stroke recorded through our multicenter prospective study. In addition, we built a dataset of previously reported patients by conducting a systematic literature review. We demonstrated distinct subgroups by clinical risk scoring models and unsupervised machine learning algorithms, including hierarchical K-Means (ML-K) and Spectral clustering (ML-S). Results. This study included 323 AIS patients from 71 centers in 17 countries from the original dataset and 145 patients reported in the literature. The unsupervised clustering methods suggest a distinct cohort of patients (ML-K: 36% and ML-S: 42%) with no or few comorbidities. These patients were more than 6 years younger than other subgroups and more likely were men (ML-K: 59% and ML-S: 60%). The majority of patients in this subgroup suffered from an embolic-appearing stroke on imaging (ML-K: 83% and ML-S: 85%) and had about 50% risk of large vessel occlusions (ML-K: 50% and ML-S: 53%). In addition, there were two cohorts of patients with large-artery atherosclerosis (ML-K: 30% and ML-S: 43% of patients) and cardioembolic strokes (ML-K: 34% and ML-S: 15%) with consistent comorbidity and imaging patterns. Binominal logistic regression demonstrated that ischemic heart disease (odds ratio (OR), 4.9; 95% confidence interval (CI), 1.6–14.7), atrial fibrillation (OR, 14.0; 95% CI, 4.8–40.8), and active neoplasm (OR, 7.1; 95% CI, 1.4–36.2) were associated with cardioembolic stroke. Conclusions. Although a cohort of young and healthy men with cardioembolic and large vessel occlusions can be distinguished using both clinical sub-grouping and unsupervised clustering, stroke in other patients may be explained based on the existing comorbidities.

Introduction: The rise of ischemic stroke among young adults has stressed the need to understand their risk profiles and outcomes better. This study aimed to examine the five-year ischemic stroke recurrence and survival probability among young patients in rural Pennsylvania. Methods: This retrospective cohort study included first-time ischemic stroke patients from the Geisinger Health System between September 2003 and May 2014. The outcomes included all-cause mortality and ischemic stroke recurrence at five years. Kaplan-Meier estimator, cumulative incidence function, Cox proportional hazards model, and Cause-specific hazard model were used to examine the association of independent variables with the outcomes. Results: A total of 4459 first-time ischemic stroke patients were included in the study, with 664 (14.9%) patients in the 18–55 age group and 3795 (85.1%) patients in the >55 age group. In the 18–55 age group, the five-year survival probability was 87.2%, and the cumulative incidence of recurrence was 8%. Patients in the 18–55 age group had significantly lower hazard for all-cause mortality (HR = 0.37, 95% CI 0.29–0.46, p < 0.001), and non-significant hazard for five-year recurrence (HR = 0.81, 95% CI 0.58–1.12, p = 0.193) compared to the >55 age group. Chronic kidney disease was found to be associated with increased mortality in the 18–55 age group. Conclusion: In our rural population, younger ischemic stroke patients were at the same risk of long-term ischemic stroke recurrence as the older ischemic stroke patients. Identifying the factors and optimizing adequate long-term secondary prevention may reduce the risk of poor outcomes among younger ischemic stroke patients.

The opioid epidemic escalated to an all-time high this past decade. States have searched for the right harm reduction and overdose prevention policies to no avail. Due to its controversial history, marijuana has not been regarded as an analgesic therapy. However, recent investigations have shown promising data highlighting the efficacy of marijuana as an analgesic and the use of marijuana for pain reduction could decrease opioid usage for pain mitigation. The distribution of codeine, fentanyl, hydrocodone, morphine, and oxycodone was examined per capita and by zip codes for the years 2014 to 2018 in California, which legalized recreational marijuana in 2016, and was compared to Texas, where medicinal and recreational marijuana is prohibited. Drug weights were obtained from the U.S Automation of Reports and Consolidated Orders System (ARCOS) and converted to their oral morphine milligram equivalent (MME) to facilitate analyses. Heat maps were constructed from distribution by zip code data to compare gross changes from 2014 to 2018. Opioid distribution per 100K people was analyzed to observe trends accounting for population differences. Both California and Texas showed statistically significant reductions in opioid distribution from 2014 to 2018, but a 43.7% decrease was seen in California versus 27.3% in Texas. Opioid distribution per 100K people in California decreased 38.9% over this time while distribution in Texas also decreased by 26.4%. Analyses showed that during this time period, opioid distribution decreased in larger areas of California than in Texas. The evidence supports marijuana legalization as a mitigating factor to the opioid epidemic. Furthermore, it highlights the idea that various legislative measures may help alleviate this crisis and a resolution to this issue is attainable. Continued studies on safer pain management alternatives will help identify measures that have a positive impact on the opioid epidemic and can be further developed to eradicate this issue.

The opioid epidemic has risen to an all-time high. Harm reduction and prevention policies have not alleviated this crisis. Recent investigations have highlighted the efficacy and safety of marijuana-based products for pain management. Providing alternative pain treatment options may help mitigate the opioid epidemic. The distribution of codeine, fentanyl, hydrocodone, morphine, and oxycodone per 100K people and by 3-digit zip codes and overdose rates from 2014 to 2018 in California, which legalized recreational marijuana in 2016, were compared to Texas, where marijuana is functionally prohibited. Drug weights were obtained from the Automation of Reports and Consolidated Orders System and converted to oral morphine milligram equivalents. Overdose data was retrieved from the Centers for Disease Control’s WONDER database. California (−43.7%) and Texas (−27.3%) showed significant reductions in cumulative opioid distribution from 2014 to 2018. Opioid distribution per 100K people decreased −38.9% in California relative to −26.4% in Texas. Opioid and heroin overdoses increased between 1999 and 2019 by +11.6% in California but +272.7% in Texas. This evidence supports marijuana legalization as a mitigating factor to the opioid epidemic. Continued studies on safer pain management alternatives and policies will help identify measures that help combat the opioid epidemic.