Abstract:Objetivo: Verificación del desempeño de las pruebas serológicas rápidas utilizadas en el departamento de Risaralda, Colombia. Métodos: Estudio analitico, de corte transversal. Incluyó muestras de sueros de trabajadores de la salud de la ciudad de Pereira, quienes tuvieron sospecha clínica y epidemiológica por SARS-CoV-2. El procesamiento y validación de las pruebas fue realizado en las instalaciones de la Universidad Tecnológica de Pereira. Se calculó sensibilidad y especificidad de las pruebas rápidas serológ… Show more
“…[ 7 ] Commercial ICG tests from leading brands are adequate for a methodology of rapid identification of individual SARS‐CoV‐2 infection even though asymptomatic, with sensitivity of 65–99% and specificity of 92–100% for IgM and IgG, respectively. [ 12 ] Since these tests present variable quality, studies indicate some results do not correlate with RT‐PCR in the acute phase of the infection, especially when tested between 8 and 11 days after the onset of symptoms [ 10 , 13 , 14 , 15 ] ; nevertheless, they are widely used in order to identify late phase IgG antibodies in individual exposed to SARS‐CoV‐2. False‐negative results with RT‐PCR may occur due to viral evolution.…”
The severe COVID‐19 pandemic requires the development of novel, rapid, accurate, and label‐free techniques that facilitate the detection and discrimination of SARS‐CoV‐2 infected subjects. Raman spectroscopy has been used to diagnose COVID‐19 in serum samples of suspected patients without clinical symptoms of COVID‐19 but presented positive immunoglobulins M and G (IgM and IgG) assays versus Control (negative IgM and IgG). A dispersive Raman spectrometer (830 nm, 350 mW) was employed, and triplicate spectra were obtained. A total of 278 spectra were used from 94 serum samples (54 Control and 40 COVID‐19). The main spectral differences between the positive IgM and IgG versus Control, evaluated by principal component analysis (PCA), were features assigned to proteins including albumin (lower in the group COVID‐19 and in the group IgM/IgG and IgG positive) and features assigned to lipids, phospholipids, and carotenoids (higher the group COVID‐19 and in the group IgM/IgG positive). Features referred to nucleic acids, tryptophan, and immunoglobulins were also seen (higher the group COVID‐19). A discriminant model based on partial least squares regression (PLS‐DA) found sensitivity of 84.0%, specificity of 95.0%, and accuracy of 90.3% for discriminating positive Ig groups versus Control. When considering individual Ig group versus Control, it was found sensitivity of 77.3%, specificity of 97.5%, and accuracy of 88.8%. The higher classification error was found for the IgM group (no success classification). Raman spectroscopy may become a technique of choice for rapid serological evaluation aiming COVID‐19 diagnosis, mainly detecting the presence of IgM/IgG and IgG after COVID‐19 infection.
“…[ 7 ] Commercial ICG tests from leading brands are adequate for a methodology of rapid identification of individual SARS‐CoV‐2 infection even though asymptomatic, with sensitivity of 65–99% and specificity of 92–100% for IgM and IgG, respectively. [ 12 ] Since these tests present variable quality, studies indicate some results do not correlate with RT‐PCR in the acute phase of the infection, especially when tested between 8 and 11 days after the onset of symptoms [ 10 , 13 , 14 , 15 ] ; nevertheless, they are widely used in order to identify late phase IgG antibodies in individual exposed to SARS‐CoV‐2. False‐negative results with RT‐PCR may occur due to viral evolution.…”
The severe COVID‐19 pandemic requires the development of novel, rapid, accurate, and label‐free techniques that facilitate the detection and discrimination of SARS‐CoV‐2 infected subjects. Raman spectroscopy has been used to diagnose COVID‐19 in serum samples of suspected patients without clinical symptoms of COVID‐19 but presented positive immunoglobulins M and G (IgM and IgG) assays versus Control (negative IgM and IgG). A dispersive Raman spectrometer (830 nm, 350 mW) was employed, and triplicate spectra were obtained. A total of 278 spectra were used from 94 serum samples (54 Control and 40 COVID‐19). The main spectral differences between the positive IgM and IgG versus Control, evaluated by principal component analysis (PCA), were features assigned to proteins including albumin (lower in the group COVID‐19 and in the group IgM/IgG and IgG positive) and features assigned to lipids, phospholipids, and carotenoids (higher the group COVID‐19 and in the group IgM/IgG positive). Features referred to nucleic acids, tryptophan, and immunoglobulins were also seen (higher the group COVID‐19). A discriminant model based on partial least squares regression (PLS‐DA) found sensitivity of 84.0%, specificity of 95.0%, and accuracy of 90.3% for discriminating positive Ig groups versus Control. When considering individual Ig group versus Control, it was found sensitivity of 77.3%, specificity of 97.5%, and accuracy of 88.8%. The higher classification error was found for the IgM group (no success classification). Raman spectroscopy may become a technique of choice for rapid serological evaluation aiming COVID‐19 diagnosis, mainly detecting the presence of IgM/IgG and IgG after COVID‐19 infection.
Corruption in healthcare is on the rise. When corruption infiltrates global health, causes embezzlement of public health funds, malfunctioning medical equipment, fraudulent or ineffective health services such as expired medicines and fake vaccines that could have life-or-death consequences. A corrupt healthcare system, amid global health crises like the COVID-19 pandemic, when resources are in constraint and trust is in high demand, can lead to devastating, though avoidable, health and economic consequences. It is imperative for policymakers, health experts, patients, caregivers, and global health funders to promptly acknowledge and address corruption in healthcare. The current pandemic generates an emergency and disorder state on health care systems across the globe, especially in low- and middle-income countries, where a weakening of control measures is evident, creating the perfect storm for corruption. This paper builds on existing research to examine processes that support essential stakeholder engagement in anti-corruption efforts. In this context, an extensive review of literature has been conducted by using various databases such as PubMed, Science direct, SCOPUS, Research Gate, and Google Scholar and a total of 45 articles and documents on corruption and COVID-19 were screened and selected by authors independently. To fill the knowledge gaps about the need for actions to be taken during a pandemic like COVID-19, we propose an anti-corruption grassroots movement that focuses on changing the social norms surrounding corruption in healthcare. By pushing forward a practice that normalizes conversations about corruption in everyday health practices and involving more stakeholders in the protection of public health resources, we argue that not only local health systems can become more resilient and resistant to corruption, but also global health initiatives can become more effective and efficient to improve individual and global health.
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