American Heart Association

Monthly Archives: November 2019

Effect of HRV on the Association Between Obstructive Sleep Apnea and Small Vessel Disease

Kristina Shkirkova, BSc
@KShkirkova

Del Brutto OH, Mera RM, Costa AF, Castillo PR. Effect of Heart Rate Variability on the Association Between the Apnea-Hypopnea Index and Cerebral Small Vessel Disease. Stroke. 2019;50:2486–2491.

Obstructive Sleep Apnea (OSA) is a form of sleep-disordered breathing that has been increasingly implicated in the pathogenesis of cerebral small vessel disease (cSVD). OSA is associated with recurrent episodes of hypoxia, altered cerebral autoregulation, and sympathetic overactivity, which may be contributing triggers for pathophysiology of cSVD. A recent study by Del Brutto et al. used nighttime Heart Rate Variability (HRV) as a measure of sympathetic upregulation to study the association between OSA and cSVD. HRV measures variation in the intervals between heartbeats and is used as a reflection of the balance between sympathetic and parasympathetic tone. Apnea-Hypopnea Index was used to access the degree of OSA and the total cSVD score was chosen to quantify cSVD burden. The study used data from the Atahualpa Project, which included elderly (age above 60) residents of the Atahualpa rural village on the coast of Ecuador. A total of 176 participants who underwent clinical assessment, magnetic resonance imaging (MRI), single-night polysomnography, and 24-hour Holter monitoring were selected for the analysis.

Among study participants, the mean age was 71.8, and 64% were women. The univariate analysis showed that daytime HRV below the 50th percentile was associated with female gender and lower mean percentage of O2 saturation. The nighttime HRV below the 50th percentile was associated with body mass index (BMI) higher than 30 kg/m2. In the generalized linear model analysis, with and without confounding variables, there was a significant association between the cSVD score and AHI (p=0.026). Furthermore, a negative association was observed between sCVD and nighttime HRV, but not daytime HRV (p=0.001). Interaction model analysis showed a significant interaction of nighttime HRV on the relationship between AHI and the cSVD score (P=0.001). The total effect between AHI and the cSVD score mediated by HRV was 30.8%. Additionally, contour plots showed the effect of nighttime HRV on the association between AHI and the cSVD score.

Anxiety Common After Stroke or TIA, Especially in the Young

Elizabeth M. Aradine, DO

Kapoor A, Si K, Yu AYX, Lanctot KL, Herrmann N, Murray BJ, et al. Younger Age and Depressive Symptoms Predict High Risk of Generalized Anxiety After Stroke and Transient Ischemic Attack. Stroke. 2019;50:2359-2363.

Poststroke anxiety is not uncommon and can negatively affect quality of life. The relationship between stroke and anxiety has been demonstrated, but few studies have included young patients. Furthermore, the presence of premorbid depression is a predictor of poststroke anxiety; however, it is unknown if the absence of depression is a protector against poststroke anxiety. The authors of this study sought to elucidate the effect of age and depression on poststroke or TIA anxiety.  

This study was conducted using registry data from the DOC Feasibility Study, a prospective longitudinal cohort of stroke, TIA, and non-stroke patients. Only those with a diagnosis of stroke or TIA were included for analysis in this study. Aphasic patients were excluded. Anxiety was assessed using the Generalized Anxiety Disorder 7-item (GAD-7) scale with a score ≥10 indicating moderate to severe symptoms. Depression was assessed using the Epidemiological Studies Depression Scale (CES-D) with ≥16 indicating moderate to severe symptoms.

257 patients were included, 125 with stroke and 133 with a TIA. 21.7% of patients had a GAD-7 score of ≥10. 25.2% had CES-D scores ≥16. Young patients (<50 years old) and those with CES-D scores ≥16 were more likely to have anxiety after a TIA or stroke. See Figure.

Figure. Frequency of high-risk anxiety and depressive symptoms in younger and older stroke patients.

Figure. Frequency of high-risk anxiety and depressive symptoms in younger and older stroke patients. Frequency of high-risk anxiety and depression symptoms includes patients with and without comorbid symptoms; frequency of high-risk anxiety+depression includes patients with comorbid symptoms.
By |November 4th, 2019|clinical|0 Comments

Collaterals Aid in Predicting Rate of Infarct Growth: Value in Transfer Decisions

Ravinder-Jeet Singh, MBBS, DM

Puhr-Westerheide D, Tiedt S, Rotkopf LT, Herzberg M, Reidler P, Fabritius MP, et al. Clinical and Imaging Parameters Associated With Hyperacute Infarction Growth in Large Vessel Occlusion Stroke. Stroke. 2019;50:2799–2804.

Infarct growth among patients with large vessel occlusion (LVO) is highly variable. In some patients, infarct progresses very quickly (rapid progressor) and they have no or small penumbra even during early hours after their stroke onset, while others progress more slowly (slow progressor) and have large penumbral tissue at later time windows. Therefore, size of pre-treatment penumbra and response to reperfusion therapies, especially endovascular thrombectomy, would vary depending on time from symptom onset and rate of infarct growth, resulting in patient-specific time-windows to intervene. While rapid progressors could benefit from reperfusion therapy during very early time-window, the slow progressors can potentially benefit from treatment in either early- or late-windows This concept has been tested in the recent early- and late-window thrombolysis and thrombectomy trials. Therefore, early distinction between rapid vs slow progressor might prove particularly useful in making time-sensitive decisions, especially interfacility transfer decisions, typically between more peripheral primary stroke centers to larger endovascular therapy capable centers.

The variability in infarct growth is determined by multiple demographic, clinical, and imaging factors, such as age, blood pressure, blood glucose, stroke severity, initial infarct size, and time from ictus; these factors can influence “final” infarct volume and determine functional outcomes. Collateral blood flow status plays an especially major role in providing residual flow, and infarct size. Whether these same factors also underlie “early” infarct growth is less well studied. In the present study, the authors investigated clinical and imaging factors associated with early (hyperacute) infarct growth.

By |November 1st, 2019|clinical|0 Comments