Impact of the Pandemic on NonInfected Cardiometabolic Patients: A Survey in Countries of Latin America—Rationale and Design of the CorCOVID LATAM Study

Background: The first case of coronavirus 2019 (COVID-19) in Latin America was detected on February 26th, 2020, in Brazil. Later, in June, the World Health Organization announced that the focus of the outbreak had shifted to Latin America, where countries already had poor control of indicators of noncommunicable diseases (NCDs). Concerns about coronavirus infection led to a reduced number of visits and hospitalizations in patients with NCDs, such as cardiovascular disease, diabetes, and cancer. There is a need to determine the impact of the COVID-19 pandemic on patients who have cardiometabolic diseases but do not have clinical evidence of COVID-19 infection. Methods: The CorCOVID LATAM is a cross-sectional survey of ambulatory cardiometabolic patients with no history or evidence of COVID-19 infection. The study will be conducted by the Interamerican Society of Cardiology. An online survey composed of 38 questions using Google Forms will be distributed to patients of 13 Latin American Spanish-speaking countries from June 15th to July 15th, 2020. Data will be analyzed by country and regions. Seven clusters of questions will be analyzed: demographics, socioeconomic and educational level, cardiometabolic profile, lifestyle and habits, body-weight perception, medical follow-up and treatments, and psychological symptoms. Results: Final results will be available upon completion of the study. Conclusions: The present study will provide answers regarding the impact of the COVID-19 pandemic on noninfected cardiometabolic patients. Data on this topic are scarce, as it is an unprecedented threat, without short-term solutions.Fil: Lopez Santi, Ricardo. Hospital Italiano de La Plata; ArgentinaFil: Piskorz, Daniel Leonardo. No especifíca;Fil: Marquez, Manlio F.. Instituto Nacional de Cardiologia Ignacio Chavez; MéxicoFil: Ramirez Ramos, Cristhian. Centro de Medicina del Ejercicio y Rehabilitación Cardíaca; ColombiaFil: Renna, Nicolas Federico. Hospital Espanol de Mendoza; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Ibarrola, Martin. No especifíca;Fil: Wyss, Fernando Stuardo. Servicios y Tecnología Cardiovascular de Guatemala; GuatemalaFil: Naranjo Dominguez, Adrián. Instituto de Cardiologia y Cirugia Cardiovascular; CubaFil: Perez, Gonzalo Emanuel. No especifíca;Fil: Farina, Juan María. No especifíca;Fil: Forte, Ezequiel. Centro Diagnóstico Cardiovascular; ArgentinaFil: Juarez Lloclla, Jorge Paul. Hospital de Apoyo II Santa Rosa; PerúFil: Flores de Espinal, Emma. Hospital Nacional San Juan De Dios; El SalvadorFil: Puente Barragan, Adriana. Instituto Mexicano del Seguro Social; MéxicoFil: Ruise, Mauro Gabriel. Clínica Yunes; ArgentinaFil: Delgado, Diego. University of Toronto; CanadáFil: Baranchuk, Adrian. Queens University; Canad

The worldwide impact of telemedicine during COVID-19: current evidence and recommendations for the future.

During the COVID-19 pandemic, telemedicine has emerged worldwide as an indispensable resource to improve the surveillance of patients, curb the spread of disease, facilitate timely identification and management of ill people, but, most importantly, guarantee the continuity of care of frail patients with multiple chronic diseases. Although during COVID-19 telemedicine has thrived, and its adoption has moved forward in many countries, important gaps still remain. Major issues to be addressed to enable large scale implementation of telemedicine include: (1) establishing adequate policies to legislate telemedicine, license healthcare operators, protect patients' privacy, and implement reimbursement plans; (2) creating and disseminating practical guidelines for the routine clinical use of telemedicine in different contexts; (3) increasing in the level of integration of telemedicine with traditional healthcare services; (4) improving healthcare professionals' and patients' awareness of and willingness to use telemedicine; and (5) overcoming inequalities among countries and population subgroups due to technological, infrastructural, and economic barriers. If all these requirements are met in the near future, remote management of patients will become an indispensable resource for the healthcare systems worldwide and will ultimately improve the management of patients and the quality of care

Effects of dipeptidyl-peptidase 4 inhibitor about vascular inflammation in a metabolic syndrome model.

BACKGROUND: In this study, we used vidagliptin(V) to examine the role of the DDP-IV, incretin system component, in the activation of different molecular inflammatory cytokines, NF-kB and VCAM-1 to generate a microenvironment that supports cardiovascular remodeling. METHODS: Male WKY and SHR were separated into five groups: Control, FFR: WKY rats receiving a 10% (w/v) fructose solution during all 12 weeks, SHR, FFHR: SHR receiving a 10% (w/v) fructose solution during all 12 weeks and FFHR+V: (5 mg/kg per day for 6 weeks) (n = 8 each group). Metabolic variables and systolic blood pressure were measured. The TBRAS, eNOS activity, and NAD(P)H oxidase activity were estimated to evaluate oxidative stress. Cardiac and vascular remodeling were evaluated. To assess the cytokine, NF-kB and VCAM-1 immunostaining techniques were used. RESULTS: The FFHR experimental model presents metabolic syndrome criteria, vascular and cardiac remodeling, vascular inflammation due to increased expression of NF-kB, VCAM-1, and pro-atherogenic cytokines. Chronic treatment with V was able to reverse total or partiality of variables studied. CONCLUSIONS: Data demonstrated an important effect of DDP-IV in reducing vascular inflammation, accompanied by a favorable reduction in metabolic and structural parameters

Metabolic and cardiovascular variables.

<p>The above values correspond to metabolic and cardiovascular variables. Symbols indicate:</p><p>*p<0.001 vs. WKY;</p><p>∧p<0.001 vs. SHR;</p>#<p>p<0.01 vs. FFR.</p><p>**vs. FFHR.</p><p>Metabolic and cardiovascular variables.</p

Cytokine release profiles on different experimental models.

a<p>Name of cytokine.</p>b<p>Relative levels: -, undetectable; H, high: L, low.</p>c<p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0106563#pone-0106563-g003" target="_blank">Figure 3</a> for the location of the duplicate spots in the matrix.</p>d<p>When the control “∼” symbol was used to indicate an approximation of zero, the values indicate the fold increase vs. WKY (control group). NC, no change (less than or equal to the fold change in the WKY group).</p><p>Cytokine release profiles on different experimental models.</p

Detection of cytokines on membrane antibody arrays by chemiluminescence.

<p>Duplicate spots in the following locations represent each cytokine. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0106563#pone-0106563-g001" target="_blank">Figure 1</a>. The average net light intensity for each pair of cytokine spots detected based on ray-scale levels using US NIH Image software ver 1.66. Cytokines names: Neutrophil chemotactic cytokine 2 and 3 (CINC-2 and CINC-3), ciliary neurotrophic factor (CNFT), monocyte chemotactic protein-1 (MCP-1), inflammatory protein macrophage-3 alpha (MIP-3 alpha), nerve growth factor beta (beta-NGF), tissue inhibitor of metalloproteinase-1 (TIMP-1) and vascular endothelial growth factor (VEGF), granulocyte colony stimulating factor, macrophage (GM-CSF), interferon gamma (INF-γ), interleukin 1 alpha and beta (IL-1α, IL-1β), interleukin 4, 6 and 10 (IL-4, IL-6, IL-10), lipopolysaccharide induced CXC chemokine (LIX or CXCL5), leptin, tumor necrosis factor alpha (TNF-α).</p

ChemiArray Rat Lysate Cytokine Antibody Array I Map.

<p>ChemiArray Rat Lysate Cytokine Antibody Array I Map.</p