EF according to short-term functional outcome (A), 90 days mortality (B), and mRS in CES patients (C).

<p>ns: not significant, ***: p-value <0.01. Abbreviations: ns: not significant, EF, Ejection fraction.mRS: modified Rankin Scale, CES: Cardioembolic stroke.</p

Cardiac Function and Outcome in Patients with Cardio-Embolic Stroke

<div><p>Background</p><p>The relationship between whole spectrum of Ejection fraction (EF) and cardioembolic stroke (CES) outcome has not been fully described yet. Notably, it remains unclear whether borderline EF (41∼49%) is related with poor outcome after CES. We sought to evaluate whether lower ejection fraction and borderline EF could predict the outcome in patients with CES.</p><p>Method and Results</p><p>We evaluated the relationship between EF and functional outcome in 437 consecutive patients with CES. EF was introduced as continuous and categorical (EF≤40%, EF 41∼49%, EF≥50%) variable. Patients with CES and the subgroup with AF were evaluated separately. Poor short-term outcome (modified Rankin Score≥3at discharge or death within 90 days after stroke onset) and long-term mortality were evaluated. A total of 165 patients (37.8%) had poor short-term outcomes. EF tends to be lower in patients with poor short-term outcome (56.8±11.0 vs. 54.8±12.0, p-value 0.086). Overall cumulative death was136 (31.1%) in all CES patients and 106 (31.7%) in the AF subgroup. In a multivariable model adjusted for possible covariates, the hazard ratio for mortality significantly decreased by 3% for every 1% increase in ejection fraction in CES patients and 2% for every 1% increase in the AF subgroup. Reduced EF (EF≤40%) showed higher mortality (HR 2.61), and those with borderline EF (41∼49%) had a tendency of higher mortality (HR 1.65, p-value 0.067)compared with those with normal EF.</p><p>Conclusion</p><p>We found a strong association between lower EF and CES outcome. Echocardiographic evaluation helps to better determine the prognosis in CES patients, even in subgroup of patients with AF.</p></div

Distribution of EF in included CES patients.

<p>Abbreviations: EF:Ejection fraction, CES: Cardioembolic stroke.</p

Flow chart of patient enrollment.

<p>Abbreviations: SNUHSR: Seoul National University Hospital Stroke Registry, CES: Cardio-embolic stroke, TIA: Transient ischemic attack, EF: Ejection Fraction.</p

Kaplan-Meier curves of long-term mortality by EF groups in CES patients (A) and AF subgroup (B).

<p>Abbreviations: EF, Ejection fraction. CES: Cardioembolic stroke, AF: Atrial fibrillation.</p

Basic demographics.

<p>Values are mean±SD or number of patients (percentage).</p><p>AF: Atrial fibrillation, NIHSS: National Institutes of Health Stroke Scale, IV: Intravenous, IA: Intraarterial,</p

Multivariable model hazard ratios for long-term outcomes by EF compared with normal values.

<p>Adjusted for age, sex, history of stroke, hypertension, diabetes, dyslipidemia, smoking,</p><p>Admission NIHSS (<7, 7–14, >14), IV or IA thrombolysis,discharge warfarin, hemorrhagic transformation.</p><p>EF: Ejection Fraction, CES: cardioembolic stroke, AF: Atrial fibrillation, NIHSS: National Institutes of Health Stroke Scale,</p><p>IV: Intra-venous, IA: Intra-arterial.</p

Additional file 1 of Risk of encephalitis and meningitis after COVID-19 vaccination in South Korea: a self-controlled case series analysis

Additional file 1: Table S1. Diagnostic and procedure codes for encephalitis and meningitis in the national health insurance system database. Table S2. Subgroup analysis on the risk of encephalitis after COVID-19 vaccination according to the selected characteristics. Table S3. Sensitivity analysis on the risk of encephalitis after COVID-19 vaccination by varying the risk window lengths. Table S4. Sensitivity analysis on the risk of encephalitis after COVID-19 vaccination by varying the case definition.Table S5. Sensitivity analysis on the risk of encephalitis after COVID-19 vaccination in the modified study population. Table S6. Subgroup analysis on the risk of meningitis after COVID-19 vaccination according to the selected characteristics. Table S7.Sensitivity analysis on the risk of meningitis after COVID-19 vaccination by varying the risk window lengths. Table S8. Sensitivity analysis on the risk of meningitis after COVID-19 vaccination by varying the case definition. Table S9. Sensitivity analysis on the risk of meningitis after COVID-19 vaccination in the modified study population

The effect of dim light at night on cerebral hemodynamic oscillations during sleep: A near-infrared spectroscopy study

<p>Recent studies have reported that dim light at night (dLAN) is associated with risks of cardiovascular complications, such as hypertension and carotid atherosclerosis; however, little is known about the underlying mechanism. Here, we evaluated the effect of dLAN on the cerebrovascular system by analyzing cerebral hemodynamic oscillations using near-infrared spectroscopy (NIRS). Fourteen healthy male subjects underwent polysomnography coupled with cerebral NIRS. The data collected during sleep with dim light (10 lux) were compared with those collected during sleep under the control dark conditions for the sleep structure, cerebral hemodynamic oscillations, heart rate variability (HRV), and their electroencephalographic (EEG) power spectrum. Power spectral analysis was applied to oxy-hemoglobin concentrations calculated from the NIRS signal. Spectral densities over endothelial very-low-frequency oscillations (VLFOs) (0.003–0.02 Hz), neurogenic VLFOs (0.02–0.04 Hz), myogenic low-frequency oscillations (LFOs) (0.04–0.15 Hz), and total LFOs (0.003–0.15 Hz) were obtained for each sleep stage. The polysomnographic data revealed an increase in the N2 stage under the dLAN conditions. The spectral analysis of cerebral hemodynamics showed that the total LFOs increased significantly during slow-wave sleep (SWS) and decreased during rapid eye movement (REM) sleep. Specifically, endothelial (median of normalized value, 0.46 vs. 0.72, <i>p</i> = 0.019) and neurogenic (median, 0.58 vs. 0.84, <i>p</i> = 0.019) VLFOs were enhanced during SWS, whereas endothelial VLFOs (median, 1.93 vs. 1.47, <i>p</i> = 0.030) were attenuated during REM sleep. HRV analysis exhibited altered spectral densities during SWS induced by dLAN, including an increase in very-low-frequency and decreases in low-frequency and high-frequency ranges. In the EEG power spectral analysis, no significant difference was detected between the control and dLAN conditions. In conclusion, dLAN can disturb cerebral hemodynamics via the endothelial and autonomic systems without cortical involvement, predominantly during SWS, which might represent an underlying mechanism of the increased cerebrovascular risk associated with light exposure during sleep.</p

Association of blood pressure variability with orthostatic intolerance symptoms

<div><p>The short-term blood pressure variability (BPV) reflects autonomic regulatory mechanisms. However, the influence of BPV in orthostatic intolerance (OI) is unknown. Herein, we assessed BPV profiles in patients with OI and determined their association with orthostatic symptoms. In this cross-sectional study, we prospectively enrolled 126 patients presenting with OI at the Seoul National University Hospital from December 2014 to August 2016. Among them, those with other neurological diseases (n = 8) and insufficient BP measurements (n = 15) were excluded. The degree of OI symptoms were measured using the self-administered orthostatic intolerance questionnaire (OIQ). All patients underwent ambulatory BP monitoring and we calculated the standard deviation and coefficient of variation as a measure of BPV. The mean age was 48.6 years and the average of the total OIQ score was 11.6. The severe OI group had higher BPV values than the mild group, although mean BP profiles did not differ significantly. Correlation analysis demonstrated that the orthostatic symptoms were positively correlated with diastolic BPV for the total and awake periods. Multiple linear regression analysis revealed that diastolic BPV (<i>B</i> = 0.46, p = 0.031) and current smoking (<i>B</i> = 4.687, p = 0.018) were independent factors for higher OI symptom scores after adjusting for covariates. The results of the current study demonstrated that a positive correlation exists between BPV and OI symptoms. Further studies are required to confirm the present findings and understand the neural mechanisms contributing to the excessive BPV in patients with OI.</p></div