Stroke

Previous observational studies reported that a lower serum 25-hydroxyvitamin D [25(OH)D] concentration is associated with a higher burden of cerebral small vessel disease (cSVD). The causality of this association is uncertain, but it would be clinically important, given that 25(OH)D can be a target for intervention. We tried to examine the causal effect of 25(OH)D concentration on cSVD-related phenotypes using a Mendelian randomization approach. Genetic instruments for each serum 25(OH)D concentration and cSVD-related phenotypes (lacunar stroke, white matter hyperintensity, cerebral microbleeds, and perivascular spaces) were derived from large-scale genome-wide association studies. We performed 2-sample Mendelian randomization analyses with multiple post hoc sensitivity analyses. A bidirectional Mendelian randomization approach was also used to explore the possibility of reverse causation. We failed to find any significant causal effect of 25(OH)D concentration on cSVD-related phenotypes (odds ratio [95% CI], 1.00 [0.87-1.16], 1.01 [0.96-1.07], 1.06 [0.85-1.33], 1.00 [0.97-1.03], 1.02 [0.99-1.04], 1.01 [0.99-1.04] for lacunar stroke, white matter hyperintensity, cerebral microbleeds, and white matter, basal ganglia, hippocampal perivascular spaces, respectively). These results were reproduced in the sensitivity analyses accounting for genetic pleiotropy. Conversely, when we examined the effects of cSVD phenotypes on 25(OH)D concentration, cerebral microbleeds were negatively associated with 25(OH)D concentration (0.94 [0.92-0.96]). Given the adequate statistical power (>0.8) of the analyses, our findings suggest that the previously reported association between 25(OH)D concentration and cSVD phenotypes might not be causal and partly attributed to reverse causation

Phenological Response in the Trophic Levels to Climate Change in Korea

The response of the phenological events of individual species to climate change is not isolated, but is connected through interaction with other species at the same or adjacent trophic level. Using long-term phenological data observed since 1976 in Korea, whose temperature has risen more steeply than the average global temperature, this study conducted phenological analysis (differ-ences in the phenology of groups, differences in phenological shifts due to climate change, differ-ences in phenological sensitivity to climate by groups, and the change of phenological day differ-ences among interacting groups). The phenological shift of the producer group (plants) was found to be negative in all researched species, which means that it blooms quickly over the years. The regression slope of consumers (primary consumers and secondary consumers) was generally posi-tive which means that the phenological events of these species tended to be later during the study period. The inter-regional deviation of phenological events was not large for any plant except for plum tree and Black locust. In addition, regional variations in high trophic levels of secondary consumers tended to be greater than that of producers and primary consumers. Among the studied species, plum was the most sensitive to temperature, and when the temperature rose by 1 °C, the flowering time of plum decreased by 7.20 days. As a result of checking the day differences in the phenological events of the interacting species, the phenological events of species were reversed, and butterflies have appeared earlier than plum, Korean forsythia, and Korean rosebay since 1990. Using long-term data from Korea, this study investigated differences in phenological reactions among trophic groups. There is a possibility of a phenological mismatch between trophic groups in the future if global warming continues due to differences in sensitivity to climate and phenological shifts between trophic levels

The Association between Parkinson’s Disease and Congestive Heart Failure in Korea: A Nationwide Longitudinal Cohort Study

The purpose of this nationwide longitudinal follow-up study is to investigate the relationship between Parkinson’s disease (PD) and congestive heart failure (CHF) patients in Korea. Patient data were collected using the National Health Insurance Service (NHIS) Health Screening (HEALS) cohort. The International Classification of Diseases 10-CM code G-20 distinguished 6475 PD patients who were enrolled in the PD group. After removing 1039 patients who were not hospitalized or attended an outpatient clinic less than twice, the total number of participants was reduced to 5436 individuals. Then, 177 patients diagnosed before 1 January 2004 were removed for relevancy, leaving us with 5259 PD patients. After case–control matching was completed using 1:5 age- and gender-coordinated matching, 26,295 people were chosen as part of the control group. The Cox proportional hazards regression analysis and the Kaplan–Meier technique were used to assess the risk of CHF in patients with Parkinson’s disease. After controlling for age and gender, the hazard ratio of CHF in the PD group was 5.607 (95% confidence interval (CI), 4.496–6.993). After that, the hazard ratio of CHF in the PD group was modified against for comorbid medical disorders, resulting in a value of 5.696 (95% CI, 4.566–7.107). In subgroup analysis, CHF incidence rates were significantly increased in the PD group compared to the control group (males and females; aged ≥ 65 and <65; the non-diabetes and diabetes, hypertension and non-hypertension, and dyslipidemia and non-dyslipidemia subgroups). This nationwide longitudinal study shows a higher incidence rate of CHF in PD patients

Optimal Triage for COVID-19 Patients Under Limited Health Care Resources With a Parsimonious Machine Learning Prediction Model and Threshold Optimization Using Discrete-Event Simulation: Development Study

BackgroundThe COVID-19 pandemic has placed an unprecedented burden on health care systems. ObjectiveWe aimed to effectively triage COVID-19 patients within situations of limited data availability and explore optimal thresholds to minimize mortality rates while maintaining health care system capacity. MethodsA nationwide sample of 5601 patients confirmed with COVID-19 until April 2020 was retrospectively reviewed. Extreme gradient boosting (XGBoost) and logistic regression analysis were used to develop prediction models for the maximum clinical severity during hospitalization, classified according to the World Health Organization Ordinal Scale for Clinical Improvement (OSCI). The recursive feature elimination technique was used to evaluate the maintenance of model performance when clinical and laboratory variables were eliminated. Using populations based on hypothetical patient influx scenarios, discrete-event simulation was performed to find an optimal threshold within limited resource environments that minimizes mortality rates. ResultsThe cross-validated area under the receiver operating characteristic curve (AUROC) of the baseline XGBoost model that utilized all 37 variables was 0.965 for OSCI ≥6. Compared to the baseline model’s performance, the AUROC of the feature-eliminated model that utilized 17 variables was maintained at 0.963 with statistical insignificance. Optimal thresholds were found to minimize mortality rates in a hypothetical patient influx scenario. The benefit of utilizing an optimal triage threshold was clear, reducing mortality up to 18.1%, compared with the conventional Youden index. ConclusionsOur adaptive triage model and its threshold optimization capability revealed that COVID-19 management can be achieved via the cooperation of both the medical and health care management sectors for maximum treatment efficacy. The model is available online for clinical implementation

Association between ischemic stroke and seropositive rheumatoid arthritis in Korea: A nationwide longitudinal cohort study.

The purpose of this longitudinal follow-up study was to investigate the risk of ischemic stroke nationwide in patients with seropositive rheumatoid arthritis (RA) and controls who were matched in age and sex. Patient data were collected from the National Health Insurance Service (NHIS) Health Screening (HEALS) cohort. Using the International Classification of Diseases code M05 (seropositive RA), with a prescription of any disease-modifying anti-rheumatic drug (DMARD), RA was identified. A total of 2,765 patients and 13,825 control subjects were included in our study. The 12-year incidence of ischemic stroke in each group was calculated using the Kaplan-Meier method. The risk ratio of ischemic stroke was estimated using Cox proportional hazards regression. Sixty-four patients (2.31%) in the seropositive RA group and 512 (3.70%) in the control group experienced ischemic stroke (P < 0.001) during the follow-up period. The hazard ratio of ischemic stroke in the seropositive RA group was 1.32 (95% confidence interval (CI), 1.02-1.73) after adjusting for age and sex. The adjusted hazard ratio of ischemic stroke in the seropositive RA group was 1.40 (95% CI, 1.07-1.82) after adjusting for demographics and comorbid medical disorders. According to the subgroup analysis, the hazard ratios of ischemic stroke risks in the female and hypertensive subgroups were 1.44 (95% CI, 1.05-1.97) and 1.66 (95% CI, 1.16-2.38), respectively. In the non-diabetes and non-dyslipidemia subgroups, the corresponding hazard ratios of ischemic stroke were 1.47 (95% CI, 1.11-1.95) and 1.43 (95% CI, 1.07-1.91). Seropositive RA patients have an increased risk of ischemic stroke. In female, hypertension, non-diabetes, and non-dyslipidemia RA subgroups, even without the traditional risk factors for stroke (except for hypertension), increased the risk, which could be potentially attributed to RA