Outcomes of intact thoracic endovascular aortic repair in octogenarians.

BACKGROUND: Thoracic endovascular aortic repair (TEVAR) is a suitable alternative to open aortic surgery especially for older patients with poor general health and functional status. However, data on the benefit of TEVAR in elderly patients are limited. The aim of this study was to use a large national database to compare the outcomes of TEVAR in octogenarians vs nonoctogenarians in the treatment of thoracic aortic aneurysms and dissection. METHODS: All patients who underwent TEVAR for nonruptured thoracic aneurysms or dissection (zones 1-5) between January 2014 and February 2019 were identified in the Vascular Quality Initiative database. The primary outcome was in-hospital mortality. Secondary outcomes included cardiac adverse events; neurologic events; respiratory complications; new-onset dialysis; leg compartment syndrome; postoperative hematoma in addition to spinal, bowel, arm, and leg emboli/ischemia; and return to the operating room. Outcomes were compared between octogenarians (age ≥80 years) and nonoctogenarians (age <80 years) using univariable and multivariable logistic regression models. RESULTS: A total of 2042 patients were identified, including 390 octogenarians (19.1%). Compared with nonoctogenarians, octogenarians had higher percentages of females (49.5% vs 40.4%; P < .01) and White patients (75.9% vs 68.6%; P < .01) and were more likely to present with thoracic aneurysms (86.2% vs 64.3%; P < .001). They also had larger aortic diameters (maximum diameter, 60.3 ± 15.8 mm vs 53.4 ± 17.4 mm), less proximal disease zones (zone 1, 3.3% vs 5.5%; zone 2, 13.9% vs 24.1%; P < .001) and were more likely to undergo the procedure under local/regional anesthesia (5.4% vs 2.4%; P < .01) compared with patients less than 80 years of age. No association was observed between octogenarians and in-hospital mortality after TEVAR for aneurysms (5.1% vs 3.3%; odds ratio [OR], 1.38; 95% confidence interval [CI], 0.72-2.61; P = .33) or dissection (5.6% vs 4.9%; OR, 0.68; 95% CI, 0.14-3.32; P = .63). However, for thoracic aneurysm repair, octogenarians had a 44% higher adjusted odds of in-hospital complications (27.4% vs 20.7%; OR, 1.44; 95% CI, 1.04-1.98; P = .03) compared with their younger counterparts. In-hospital complications (27.8% vs 26.2%; P = .79; OR, 1.02; 95% CI, 0.50-2.11; P = .95) were similar in octogenarians undergoing endovascular repair for dissections of the thoracic aorta. Octogenarians were also associated with 1.74 times the mortality hazard compared with nonoctogenarians (adjusted hazard ratio, 1.74; 95% CI, 1.18-2.58; P = .01). CONCLUSIONS: TEVAR is an acceptable treatment option for octogenarians who have aortic arch and descending aortic aneurysms or dissections (zones 1-5). However, in case of aneurysms, they might be at a higher risk of in-hospital complications. Octogenarians also had increased hazard of 1-year mortality; however, the exact cause of this mortality could not be deciphered. Our findings suggest that elderly patients should not be denied TEVAR based on age if they are medically and anatomically fit for this procedure.

Hospital Volume Impacts the Outcomes of Endovascular Repair of Thoracoabdominal Aortic Aneurysms.

BACKGROUND: Few centers in the United States have the expertise to manage patients with a thoracoabdominal aortic aneurysm (TAAA). The purpose of this study is to use a nationally representative vascular database to assess the role of hospital volume on outcomes in patients undergoing endovascular repair for TAAA. METHODS: All patients undergoing complex endovascular repair (cEVAR) for TAAA were identified in the Vascular Quality Initiative (VQI) database (2012-2018). The total mean number of cases per year was identified at each center and were used to group into three quantiles containing an equal number of patients (Low [LVH], Medium [MVH], High [HVH]). Standard univariate and multivariable (logistic regression) analyses were performed to evaluate the patient's characteristics and short-term outcomes. RESULTS: A total of 2,115 patients from 118 centers (Low - 92, Medium - 19, High - 7) were identified in VQI from 2012 to 2018. The annual mean (S.D.) number of cases at HVH, MVH, LVH were 22.7 (4.7), 9.6 (3.0), 3.6 (1.4), respectively. The repair of Type III TAAA was slightly higher in HVH versus MVH versus LVH (22.5% vs. 21.0% vs. 15.1%), while Type I was more common among LVH versus MVH versus HVH (13.7% vs. 11.5% vs. 3.7%) (Both P < 0.001). Custom/modified devices were more likely to be used in HVH versus MVH versus LVH (67.9% vs. 27.6% vs. 27.2%) (P < 0.001). Additionally, HVH and MVH utilized fenestrated/branched or chimney/snorkel options more frequently, whereas surgical bypasses were common in LVH for revascularization of visceral arteries. In univariate analysis, HVH were associated with significantly lower mortality (2.2% vs. 5.1% and 6.5%), failure to rescue [FTR] (3.5% vs. 11.6% and 12.1%) and any complication (24.6% vs. 27.1% and 31.2%) compared to LVH and MVH (All P < 0.001). After adjusting for potential confounders, both LVH and MVH were associated with 2-4 fold increase in the odds of mortality [OR (95% CI): 2.30 (1.20-4.41) and 2.14 (1.16-3.93)] and FTR [OR (95% CI): 4.42 (1.86-10.54) and 4.08 (1.73-9.62)] compared to HVH. CONCLUSIONS: Our study demonstrates significantly lower morbidity and mortality in high volume hospitals performing cEVAR for TAAA, despite operating on older patients with more complex TAAA types. This is likely due to better rescue phenomenon in addition to more experienced operators. Complex endovascular repair of TAAA can be performed safely in high volume aortic centers of excellence.

Factors Associated with the Development of Posterior Capsule Opacification Requiring Yttrium Aluminum Garnet Capsulotomy.

SIGNIFICANCE: Determining risk factors for posterior capsule opacification will allow for further interventions to reduce the risk of development and thus additional procedures. PURPOSE: The purpose of this study was to investigate risk factors associated with development of clinically significant posterior capsule opacification requiring yttrium aluminum garnet (YAG) capsulotomy. METHODS: Medical records of patients (≥18 years) who underwent cataract surgery between January 1, 2011, and March 31, 2014, at Kresge Eye Institute were reviewed. Three hundred eyes requiring YAG capsulotomy up to 3 years after cataract surgery were included in the YAG capsulotomy group. Three hundred eyes not requiring YAG capsulotomy up to 3 years after cataract surgery were selected via age-matched simple randomization (control group). RESULTS: The YAG capsulotomy group included patients with younger age (65.8 ± 11.3 vs. 70.1 ± 10.6 years, P < .001), more men (42.67 vs. 34.67%, P = .04), fewer patients with hypertension (73.00 vs. 83.00%, P < .001), and more patients with hydrophilic intraocular lenses (74.67 vs. 47.00%, P < .001). Logistic regression analysis demonstrated a negative association between YAG capsulotomy and age (coefficient, -0.04; 95% confidence interval [CI], 0.95 to 0.98; P < .001) and hydrophobic intraocular lenses (coefficient, -1.50; 95% CI, 0.15 to 0.33; P < .001), and a positive association with presence of glaucoma (coefficient, 0.88; 95% CI, 1.39 to 4.17; P = .002). Elapsed time to YAG capsulotomy was sooner in patients with a history of uveitis (95% CI, 5.10 to 9.70 months; P = .02) and insertion of hydrophilic intraocular lenses (95% CI, 18.67 to 21.57 months; P < .001). CONCLUSIONS: Results of this study suggest that development of visually significant posterior capsule opacification is associated with younger age, glaucoma, and hydrophilic intraocular lenses, and it occurs earlier among those with hydrophilic intraocular lenses and a history of uveitis.

Finger-Counting-Based Gesture Recognition within Cars Using Impulse Radar with Convolutional Neural Network.

The diversion of a driver's attention from driving can be catastrophic. Given that conventional button- and touch-based interfaces may distract the driver, developing novel distraction-free interfaces for the various devices present in cars has becomes necessary. Hand gesture recognition may provide an alternative interface inside cars. Given that cars are the targeted application area, we determined the optimal location for the radar sensor, so that the signal reflected from the driver's hand during gesturing is unaffected by interference from the motion of the driver's body or other motions within the car. We implemented a Convolutional Neural Network-based technique to recognize the finger-counting-based hand gestures using an Impulse Radio (IR) radar sensor. The accuracy of the proposed method was sufficiently high for real-world applications.

AI-CADR: Artificial Intelligence Based Risk Stratification of Coronary Artery Disease using Novel Non-invasive Biomarkers.

Coronary artery disease (CAD) is one of the most common causes of sudden cardiac arrest, accounting for a large percentage of global mortality. A timely diagnosis and detection may save a person's life. The research suggests a methodological framework for non-invasive risk stratification based on information only possible after invasive coronary angiography. Novel clinical, chemical, and molecular cardiac biomarkers were used as input features from an especially collected dataset. Following a thorough evaluative search in the biomarker feature space, the optimum feature and classifier or regression technique (regressor) set were selected using K-fold cross-validation. Ten machine learning (ML) classifiers were employed in classification tasks to determine the number of affected cardiac vessels, the Gensini group, and the severity of CAD with 82.58%, 86.26%, and 90.91% accuracy, respectively. Eleven approaches were used in regression tasks to calculate stenosis percentage and Gensini score, with R-squared values of 0.58 and 0.56, respectively. Following a thorough evaluative search in the biomarkers feature space, the optimum feature and classifier or regressor set were selected using K-fold cross-validation. The biomarkers and classifier or regressor combinations serve as the foundation for the proposed risk stratification framework, incorporating clinical protocol. Finally, our proposed framework is compared to state-of-the-art studies, offering a robust, well-rounded, early detection capable, and novel 'biomarkers-ML combination' approach to risk stratification.

Analysis of channel uncertainty in ARQ relay networks.

Several power allocation algorithms for cooperative relay networks are presented in the literature. These contributions assume perfect channel knowledge and capacity achieving codes. However in practice, obtaining the channel state information at a relay or at the destination is an estimation problem and can generally not be error free. The investigation of the power allocation mechanism in a wireless network due to channel imperfections is important because it can severely degrade its performance regarding throughput and bit error rate. In this paper, the impact of imperfect channel state information on the power allocation of an adaptive relay network is investigated. Moreover, a framework including Automatic Repeat reQuest (ARQ) mechanism is provided to make the power allocation mechanism robust against these channel imperfections. For this framework, the end-to-end SNR is calculated considering imperfect channel knowledge using ARQ analytically. The goal is to emphasize the impact of imperfect channel knowledge on the power allocation mechanism. In this paper, the simulation results illustrate the impact of channel uncertainties on the average outage probability, throughput, and consumed sum power for different qualities of channel estimation. It is shown that the presented framework with ARQ is extremely robust against the channel imperfections.

Analysis of PCG signals using quality assessment and homomorphic filters for localization and classification of heart sounds.

BACKGROUND AND OBJECTIVE: Accurate localization of heart beats in phonocardiogram (PCG) signal is very crucial for correct segmentation and classification of heart sounds into S1 and S2. This task becomes challenging due to inclusion of noise in acquisition process owing to number of different factors. In this paper we propose a system for heart sound localization and classification into S1 and S2. The proposed system introduces the concept of quality assessment before localization, feature extraction and classification of heart sounds. METHODS: The signal quality is assessed by predefined criteria based upon number of peaks and zero crossing of PCG signal. Once quality assessment is performed, then heart beats within PCG signal are localized, which is done by envelope extraction using homomorphic envelogram and finding prominent peaks. In order to classify localized peaks into S1 and S2, temporal and time-frequency based statistical features have been used. Support Vector Machine using radial basis function kernel is used for classification of heart beats into S1 and S2 based upon extracted features. The performance of the proposed system is evaluated using Accuracy, Sensitivity, Specificity, F-measure and Total Error. The dataset provided by PASCAL classifying heart sound challenge is used for testing. RESULTS: Performance of system is significantly improved by quality assessment. Results shows that proposed Localization algorithm achieves accuracy up to 97% and generates smallest total average error among top 3 challenge participants. The classification algorithm achieves accuracy up to 91%. CONCLUSION: The system provides firm foundation for the detection of normal and abnormal heart sounds for cardiovascular disease detection.

Application of Bioactive Compounds from Scutellaria in Neurologic Disorders.

Inflammation of the brain is one of the most highly researched yet mysterious areas in modern day neurology. The process of inflammation is a normal mechanism of wound healing that can result from acute injuries such as traumas or can be caused by genetic/environmental factors. After the initial insult, the immune system defenses, specifically microglial cells, are activated in order to combat the infection or injury. However, prolonged or chronic inflammation is often deleterious due mainly to accumulation of free reactive oxygen species (ROS) and other pro-inflammatory cytokines in the brain FADDIN EN.CITE. Plant-derived natural compounds have the potential to ameliorate the causes and symptoms of neuroinflammation, due to their various anti-oxidant and anti-inflammatory activities, without completely muting the immune defenses. Scutellaria is a perennial plant in the mint family that has been used to treat diseases in Asia and Eastern Europe throughout history. This chapter reviews the active components of various Scutellaria species and their mechanisms of action to prevent chronic neurologic disorders involving neuroinflammation and neurodegeneration.