Covid-19 in Cartagena and the Bolívar Department, Colombia. Current status, perspectives and challenges until the arrival of the vaccine

COVID-19, caused by SARS-CoV-2, a new coronavirus, was first observed in Wuhan (China) in November 2019. In a short time, SARS-CoV-2 spread across the world, creating a pandemic. There is a need to know the current situation of each country and region and to generate strategies to contain and mitigate the impact on global health and the economy. To control COVID-19 in Cartagena and the Department of Bolívar, Colombia, a strategic network involving public health entities and higher education institutions has emerged. The network has been in place for six months, and 77,122 subjects have been tested in Cartagena and Bolívar Department, of whom 8,260 (10.71%) tested positive (RT-qPCR). Of those who tested positive, 51.4% were male (p>0.05), and 13.1% were health personnel (9.43% female, p < 0.05). The mortality rate was relatively low, 1.22%, with males being the most affected, accounting for 0.9% of deaths (p > 0.05). The daily case report showed upward and downward fluctuations by the mobility restrictions applied to the population, and from day 120 of the start of the pandemic, the epidemiological curve stabilized, and a logarithmic plateau was reached. COVID-19 spread in 39/46 municipalities of Bolívar; however, Bolívar and Cartagena had a low number of cases and deaths compared to other departments and city in Colombia. Cartagena and Bolívar have been given an economic opening with restrictions on crowding and mandatory use of a mouth cover until a vaccine is available. UNIMOL was the first laboratory in Cartagena, Bolívar and Colombia to receive approval from the National Institute of Health to process COVID-19 samples; thanks to the timely diagnosis of cases by UNIMOL, intensive care unit (ICU) occupancy did not exceed capacity, and population confinement was appropriately initiated

Anomalías congénitas en familias de Ararca (Isla de Barú). Bolívar-Colombia

Revista Ciencias Biomédicas Vol.6, Núm.2 (2015) Pag 251 - 258Introducción: las enfermedades genéticas y los defectos de nacimiento son considerados problemas de salud pública a nivel mundial, con una incidencia de alrededor del 1%. Las principales complicaciones clínicas de estas enfermedades se caracterizan por comprometer la calidad de vida de los afectados, causando una grave discapacidad intelectual o física, por su carácter progresivo y condicionan una mortalidad precoz de los individuos afectados y generan una carga en las familias de las personas que las padecen. Objetivo: caracterizar las familias que reporten personas con anomalías congénitas que se puedan catalogar como genéticas, incluyendo el componente socioeconómico. Materiales y métodos: se planteó una metodología descriptiva, observacional y se analizaron algunos aspectos genéticos, como historia clínica genética y citogenética; se incluyeron variables socioeconómicas de una comunidad rural que previamente evidenció la presentación de enfermedades genéticas. Resultados: se reportaron cinco casos de personas con enfermedades congénitas y con indicación de trastorno genético, tres casos pertenecían a una misma familia; se analizó el componente sociodemográfico. Se evidenció un estado de pobreza de las familias, nivel educativo bajo en la mayoría, y casos de analfabetismo. Salarios que no alcanzan el mínimo, hacinamiento de las personas en las viviendas y relaciones intrafamiliares quebradas, evidente apatía entre los integrantes de las familias estudiadas. Conclusión: esta investigación permitió verificar en la comunidad de Ararca cinco casos de trastornos genéticos que podrían estar asociados a compromiso con factores ambientales y socioeconómicos. Se recomienda brindar apoyo interdisciplinario a las comunidades y trabajar en el diagnóstico a temprana edad con el fin de evitar discapacidad para desempeñarse en la sociedad y mitigar el impacto sobre las familias afectadas

Surface-enhanced Raman Spectroscopy in urinalysis of hypertension patients with kidney disease

Abstract Arterial hypertension (AH) is a multifactorial and asymptomatic disease that affects vital organs such as the kidneys and heart. Considering its prevalence and the associated severe health repercussions, hypertension has become a disease of great relevance for public health across the globe. Conventionally, the classification of an individual as hypertensive or non-hypertensive is conducted through ambulatory blood pressure monitoring over a 24-h period. Although this method provides a reliable diagnosis, it has notable limitations, such as additional costs, intolerance experienced by some patients, and interferences derived from physical activities. Moreover, some patients with significant renal impairment may not present proteinuria. Accordingly, alternative methodologies are applied for the classification of individuals as hypertensive or non-hypertensive, such as the detection of metabolites in urine samples through liquid chromatography or mass spectrometry. However, the high cost of these techniques limits their applicability for clinical use. Consequently, an alternative methodology was developed for the detection of molecular patterns in urine collected from hypertension patients. This study generated a direct discrimination model for hypertensive and non-hypertensive individuals through the amplification of Raman signals in urine samples based on gold nanoparticles and supported by chemometric techniques such as partial least squares-discriminant analysis (PLS-DA). Specifically, 162 patient urine samples were used to create a PLS-DA model. These samples included 87 urine samples from patients diagnosed with hypertension and 75 samples from non-hypertensive volunteers. In the AH group, 35 patients were diagnosed with kidney damage and were further classified into a subgroup termed (RAH). The PLS-DA model with 4 latent variables (LV) was used to classify the hypertensive patients with external validation prediction (P) sensitivity of 86.4%, P specificity of 77.8%, and P accuracy of 82.5%. This study demonstrates the ability of surface-enhanced Raman spectroscopy to differentiate between hypertensive and non-hypertensive patients through urine samples, representing a significant advance in the detection and management of AH. Additionally, the same model was then used to discriminate only patients diagnosed with renal damage and controls with a P sensitivity of 100%, P specificity of 77.8%, and P accuracy of 82.5%