Addressing COVID-19 health disparities through a regional community health response.

To combat racial/ethnic and socioeconomic health disparities associated with COVID-19 in our surrounding communities, the Cleveland Clinic Community Health & Partnership team developed a comprehensive program focused on connecting and communicating with local officials, faith-based organizations, and individual community members. Since March of 2020, our team has donated resources (e.g.

A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence.

COVID-19 has infected 77.4 million people worldwide and has caused 1.7 million fatalities as of December 21, 2020.

Wilson disease tissue classification and characterization using seven artificial intelligence models embedded with 3D optimization paradigm on a weak training brain magnetic resonance imaging datasets: a supercomputer application.

Wilson's disease (WD) is caused by copper accumulation in the brain and liver, and if not treated early, can lead to severe disability and death. WD has shown white matter hyperintensity (WMH) in the brain magnetic resonance scans (MRI) scans, but the diagnosis is challenging due to (i) subtle intensity changes and (ii) weak training MRI when using artificial intelligence (AI). Design and validate seven types of high-performing AI-based computer-aided design (CADx) systems consisting of 3D optimized classification, and characterization of WD against controls.

The Impact of Physician Productivity Models on Access to Subspecialty Care: A White Paper From the Society for the Study of Male Reproduction and the Society for Male Reproduction and Urology.

Male infertility is a common disease. Male infertility is also a core competency of urology training and clinical practice. In this white paper from the Society for the Study of Male Reproduction and the Society for Male Reproduction and Urology, we identify and define different physician productivity plans.

The last survivor of unitary and two-piece inflatables-the Ambicor. Does it still have a role in today's implant marketplace?

The history of the development of today's very dependable three-piece inflatable penile prostheses is fascinating. In its infancy, the three piece was plagued with frequent revisions and a relatively complex insertion and consequently unitary and two-piece prostheses flourished with the implanting urologists. While the surgery was less difficult because these devices did not require the dreaded reservoir insertion, they often proved unsatisfactory to patients in flaccidity, erection and longevity.

Integration of cardiovascular risk assessment with COVID-19 using artificial intelligence.

Artificial Intelligence (AI), in general, refers to the machines (or computers) that mimic "cognitive" functions that we associate with our mind, such as "learning" and "solving problem". New biomarkers derived from medical imaging are being discovered and are then fused with non-imaging biomarkers (such as office, laboratory, physiological, genetic, epidemiological, and clinical-based biomarkers) in a big data framework, to develop AI systems. These systems can support risk prediction and monitoring.

Cardiovascular disease and stroke risk assessment in patients with chronic kidney disease using integration of estimated glomerular filtration rate, ultrasonic image phenotypes, and artificial intelligence: a narrative review.

Chronic kidney disease (CKD) and cardiovascular disease (CVD) together result in an enormous burden on global healthcare. The estimated glomerular filtration rate (eGFR) is a well-established biomarker of CKD and is associated with adverse cardiac events. This review highlights the link between eGFR reduction and that of atherosclerosis progression, which increases the risk of adverse cardiovascular events.

Artificial intelligence framework for predictive cardiovascular and stroke risk assessment models: A narrative review of integrated approaches using carotid ultrasound.

Recent Findings: Cardiovascular disease (CVD) is the leading cause of mortality and poses challenges for healthcare providers globally. Risk-based approaches for the management of CVD are becoming popular for recommending treatment plans for asymptomatic individuals. Several conventional predictive CVD risk models based do not provide an accurate CVD risk assessment for patients with different baseline risk profiles.

Ultrasound-based stroke/cardiovascular risk stratification using Framingham Risk Score and ASCVD Risk Score based on "Integrated Vascular Age" instead of "Chronological Age": a multi-ethnic study of Asian Indian, Caucasian, and Japanese cohorts.

Background: Vascular age (VA) has recently emerged for CVD risk assessment and can either be computed using conventional risk factors (CRF) or by using carotid intima-media thickness (cIMT) derived from carotid ultrasound (CUS). This study investigates a novel method of integrating both CRF and cIMT for estimating VA [so-called integrated VA (IVA)]. Further, the study analyzes and compares CVD/stroke risk using the Framingham Risk Score (FRS)-based risk calculator when adapting IVA against VA.

Cardiovascular/stroke risk predictive calculators: a comparison between statistical and machine learning models.

Background: Statistically derived cardiovascular risk calculators (CVRC) that use conventional risk factors, generally underestimate or overestimate the risk of cardiovascular disease (CVD) or stroke events primarily due to lack of integration of plaque burden. This study investigates the role of machine learning (ML)-based CVD/stroke risk calculators (CVRC) and compares against statistically derived CVRC (CVRC) based on (I) conventional factors or (II) combined conventional with plaque burden (integrated factors).

Methods: The proposed study is divided into 3 parts: (I) statistical calculator: initially, the 10-year CVD/stroke risk was computed using 13 types of CVRC (without and with plaque burden) and binary risk stratification of the patients was performed using the predefined thresholds and risk classes; (II) ML calculator: using the same risk factors (without and with plaque burden), as adopted in 13 different CVRC, the patients were again risk-stratified using CVRC based on support vector machine (SVM) and finally; (III) both types of calculators were evaluated using AUC based on ROC analysis, which was computed using combination of predicted class and endpoint equivalent to CVD/stroke events.

3-D optimized classification and characterization artificial intelligence paradigm for cardiovascular/stroke risk stratification using carotid ultrasound-based delineated plaque: Atheromatic™ 2.0.

Background And Purpose: Atherosclerotic plaque tissue rupture is one of the leading causes of strokes. Early carotid plaque monitoring can help reduce cardiovascular morbidity and mortality. Manual ultrasound plaque classification and characterization methods are time-consuming and can be imprecise due to significant variations in tissue characteristics.

COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification: A review.

Artificial intelligence (AI) has penetrated the field of medicine, particularly the field of radiology. Since its emergence, the highly virulent coronavirus disease 2019 (COVID-19) has infected over 10 million people, leading to over 500,000 deaths as of July 1st, 2020. Since the outbreak began, almost 28,000 articles about COVID-19 have been published (https://pubmed.

Cardiovascular risk assessment in patients with rheumatoid arthritis using carotid ultrasound B-mode imaging.

Rheumatoid arthritis (RA) is a systemic chronic inflammatory disease that affects synovial joints and has various extra-articular manifestations, including atherosclerotic cardiovascular disease (CVD). Patients with RA experience a higher risk of CVD, leading to increased morbidity and mortality. Inflammation is a common phenomenon in RA and CVD.

Two-stage artificial intelligence model for jointly measurement of atherosclerotic wall thickness and plaque burden in carotid ultrasound: A screening tool for cardiovascular/stroke risk assessment.

Motivation: The early screening of cardiovascular diseases (CVD) can lead to effective treatment. Thus, accurate and reliable atherosclerotic carotid wall detection and plaque measurements are crucial. Current measurement methods are time-consuming and do not utilize the power of knowledge-based paradigms such as artificial intelligence (AI).

Does the Carotid Bulb Offer a Better 10-Year CVD/Stroke Risk Assessment Compared to the Common Carotid Artery? A 1516 Ultrasound Scan Study.

The objectives of this study are to (1) examine the "10-year cardiovascular risk" in the common carotid artery (CCA) versus carotid bulb using an integrated calculator called "AtheroEdge Composite Risk Score 2.0" (AECRS2.0) and (2) evaluate the performance of AECRS2.

Future diagnostics in male infertility: genomics, epigenetics, metabolomics and proteomics.

A male factor is involved in 50% of couples with infertility. Unfortunately, the etiology of male factor infertility remains classified as idiopathic in nearly 50% of cases. The semen analysis (SA) continues to be first line for the workup of male infertility, but it is an imperfect test with high variability between samples.

Nandrolone decanoate relieves joint pain in hypogonadal men: a novel prospective pilot study and review of the literature.

Testosterone is an archetypal androgenic-anabolic steroid (AAS), while its exogenous administration is considered to be the gold standard for the treatment of male hypogonadism. The benefits are not due to its intrinsic nature alone but are due to the result of its interactions with the androgen receptor (AR). As the management of hypogonadism continues to advance into the modern era, it would be preferable for modern andrologists to have multiple tools at their disposal to influence AR activity.

Beyond the androgen receptor: the role of growth hormone secretagogues in the modern management of body composition in hypogonadal males.

Male hypogonadism is an increasingly prevalent clinical condition that affects patients' quality of life and overall health. Obesity and metabolic syndrome can both cause and result from hypogonadism. Although testosterone remains the gold standard for hypogonadism management, its benefits are not always conserved across different populations, especially with regards to changes in body composition.

Integration of estimated glomerular filtration rate biomarker in image-based cardiovascular disease/stroke risk calculator: a south Asian-Indian diabetes cohort with moderate chronic kidney disease.

Background: Recently, a 10-year image-based integrated calculator (called AtheroEdge Composite Risk Score-AECRS1.0) was developed which combines conventional cardiovascular risk factors (CCVRF) with image phenotypes derived from carotid ultrasound (CUS). Such calculators did not include chronic kidney disease (CKD)-based biomarker called estimated glomerular filtration rate (eGFR).

A novel metric for treatment durability in clinical trials of minimally invasive treatments for benign prostatic hyperplasia.

: Clinical trial manuscripts commonly report results of individual endpoints. However, durability of a medical treatment may be difficult to determine when evaluating endpoint outcomes individually. We reviewed pivotal trial manuscripts of two minimally invasive benign prostatic hyperplasia (BPH) treatments and estimated the rate of treatment durability using a composite, symptom-centric metric.

Morphological Carotid Plaque Area Is Associated With Glomerular Filtration Rate: A Study of South Asian Indian Patients With Diabetes and Chronic Kidney Disease.

We evaluated the association between automatically measured carotid total plaque area (TPA) and the estimated glomerular filtration rate (eGFR), a biomarker of chronic kidney disease (CKD). Automated average carotid intima-media thickness (cIMTave) and TPA measurements in carotid ultrasound (CUS) were performed using AtheroEdge (AtheroPoint). Pearson correlation coefficient (CC) was then computed between the TPA and eGFR for (1) males versus females, (2) diabetic versus nondiabetic patients, and (3) between the left and right carotid artery.

Low-cost preventive screening using carotid ultrasound in patients with diabetes.

Diabetes and atherosclerosis are the predominant causes of stroke and cardiovascular disease (CVD) both in low- and high-income countries. This is due to the lack of appropriate medical care or high medical costs. Low-cost 10-year preventive screening can be used for deciding an effective therapy to reduce the effects of atherosclerosis in diabetes patients.