Vertebral Artery Interventions: A Comprehensive Updated Review.

Patients with posterior circulation ischemia due to vertebral artery stenosis account for 20 to 25% of ischemic strokes and have an increased risk of recurrent stroke. In patients treated with medical therapy alone, the risk of recurrence is particularly increased in the first few weeks after symptoms occur, with an annual stroke rate of 10 to 15%. Additionally, obstructive disease of the vertebrobasilar system carries a worse prognosis, with a 30% mortality at 2-years if managed medically without additional surgical or endovascular intervention. Percutaneous transluminal angioplasty and stenting of symptomatic vertebral artery stenosis are promising options widely used in clinical practice with good technical results; however, the improved clinical outcome has been examined in various clinical trials without a sufficient sample size to conclusively determine whether stenting is better than medical therapy. Surgical revascularization is an alternative approach for the treatment of symptomatic vertebral artery stenosis that carries a 10-20% mortality rate. Despite the advances in medical therapy and endovascular and surgical options, symptomatic vertebral artery stenosis continues to impose a high risk of stroke recurrence with associated high morbidity and mortality. This review aims to provide a focused update on the percutaneous treatment of vertebral artery stenosis, its appropriate diagnostic approach, and advances in medical therapies.

Aorto-right atrial fistula: Late complication of tricuspid valve infective endocarditis.

Abnormal connections between the ascending aorta and the cardiac chambers are rare, especially in the context of right-sided infective endocarditis (IE). Transthoracic echocardiography (TTE) with color-flow Doppler, transesophageal echocardiography (TEE), or both may be required for diagnosis. We present the case of a woman admitted with right-sided heart failure (HF) symptoms. She had a previous history of tricuspid valve IE 30 years ago. TTE and TEE revealed an aorto-right atrium fistula located just under the non-coronary cusp into the right atrium at the level of the previously affected tricuspid valve. The Patient refused surgery and was discharged home on HF medications. She has been stable for the last 3 years. The peculiarity of this case is the late symptomatic presentation of the aorto-atrial fistula and the unusual association to tricuspid valve IE.

Atrial fibrillation detection using an iPhone 4S.

Atrial fibrillation (AF) affects three to five million Americans and is associated with significant morbidity and mortality. Existing methods to diagnose this paroxysmal arrhythmia are cumbersome and/or expensive. We hypothesized that an iPhone 4S can be used to detect AF based on its ability to record a pulsatile photoplethysmogram signal from a fingertip using the built-in camera lens. To investigate the capability of the iPhone 4S for AF detection, we first used two databases, the MIT-BIH AF and normal sinus rhythm (NSR) to derive discriminatory threshold values between two rhythms. Both databases include RR time series originating from 250 Hz sampled ECG recordings. We rescaled the RR time series to 30 Hz so that the RR time series resolution is 1/30 (s) which is equivalent to the resolution from an iPhone 4S. We investigated three statistical methods consisting of the root mean square of successive differences (RMSSD), the Shannon entropy (ShE) and the sample entropy (SampE), which have been proved to be useful tools for AF assessment. Using 64-beat segments from the MIT-BIH databases, we found the beat-to-beat accuracy value of 0.9405, 0.9300, and 0.9614 for RMSSD, ShE, and SampE, respectively. Using an iPhone 4S, we collected 2-min pulsatile time series from 25 prospectively recruited subjects with AF pre- and postelectrical cardioversion. Using derived threshold values of RMSSD, ShE and SampE from the MIT-BIH databases, we found the beat-to-beat accuracy of 0.9844, 0.8494, and 0.9522, respectively. It should be recognized that for clinical applications, the most relevant objective is to detect the presence of AF in the data. Using this criterion, we achieved an accuracy of 100% for both the MIT-BIH AF and iPhone 4S databases.

A novel application for the detection of an irregular pulse using an iPhone 4S in patients with atrial fibrillation.

BACKGROUND: Atrial fibrillation (AF) is common and associated with adverse health outcomes. Timely detection of AF can be challenging using traditional diagnostic tools. Smartphone use is increasing and may provide an inexpensive and user-friendly means to diagnoseAF. OBJECTIVE: To test the hypothesis that a smartphone-based application could detect an irregular pulse fromAF. METHODS: Seventy-six adults with persistent AF were consented for participation in our study. We obtained pulsatile time series recordings before and after cardioversion using an iPhone 4S camera. A novel smartphone application conducted real-time pulse analysis using 2 statistical methods: root mean square of successive RR difference (RMSSD/mean) and Shannon entropy (ShE). We examined the sensitivity, specificity, and predictive accuracy of both algorithms using the 12-lead electrocardiogram as the gold standard. RESULTS: RMSDD/mean and ShE were higher in participants in AF than in those with sinus rhythm. The 2 methods were inversely related to AF in regression models adjusting for key factors including heart rate and blood pressure (beta coefficients per SD increment in RMSDD/mean and ShE were-0.20 and-0.35; P<.001). An algorithm combining the 2 statistical methods demonstrated excellent sensitivity (0.962), specificity (0.975), and accuracy (0.968) for beat-to-beat discrimination of an irregular pulse during AF from sinus rhythm. CONCLUSIONS: In a prospectively recruited cohort of 76 participants undergoing cardioversion for AF, we found that a novel algorithm analyzing signals recorded using an iPhone 4S accurately distinguished pulse recordings during AF from sinus rhythm. Data are needed to explore the performance and acceptability of smartphone-based applications for AF detection.

Recent trends in post-discharge mortality among patients with an initial acute myocardial infarction.

The objectives of this study were to describe contemporary postdischarge death rates of patients hospitalized at all Worcester, Massachusetts, hospitals after initial acute myocardial infarctions (AMIs) and to examine factors associated with a poor prognosis. The medical records of patients discharged from 11 central Massachusetts medical centers after initial AMIs during 2001, 2003, 2005, and 2007 were reviewed, identifying 2,452 patients. This population was composed of predominantly older patients, men (58%), and whites. Overall, the 3-month, 1-year, and 2-year all-cause death rates were 8.9%, 16.4%, and 23.4%, respectively. Over time, reductions in postdischarge mortality were observed in crude as well as multivariate-adjusted analyses. In 2001, the 3-month, 1-year, and 2-year all-cause death rates were 11.1%, 17.1%, and 25.6%, respectively, compared to rates of 7.9%, 12.7%, and 18.6% in patients discharged in 2007. Older age, male gender, hospitalization for a non-ST-segment elevation AMI, renal dysfunction, and preexisting heart failure were associated with an increased risk for dying after hospital discharge. These results suggest that the postdischarge prognosis of patients with initial AMIs has improved, likely reflecting enhanced in-hospital and postdischarge management practices. In conclusion, patients with initial AMIs can also be identified who are at increased risk for dying after hospital discharge, in whom increased surveillance and targeted treatment approaches can be directed.