ABSTRACT
Background: The inactivated virus vaccine, BBIBP-CorV, was principally distributed across low- and middle-income countries as primary vaccination strategy to prevent poor COVID-19 outcomes. Limited information is available regarding its effect on heterologous boosting. We aim to evaluate the immunogenicity and reactogenicity of a third booster dose of BNT162b2 following a double BBIBP-CorV regime. Methods: We conducted a cross-sectional study among healthcare providers from several healthcare facilities of the Seguro Social de Salud del Perú - ESSALUD. We included participants two-dose BBIBP-CorV vaccinated who presented a three-dose vaccination card at least 21 days passed since the vaccinees received their third dose and were willing to provide written informed consent. Antibodies were determined using LIAISON® SARS-CoV-2 TrimericS IgG (DiaSorin Inc., Stillwater, USA). Factors potentially associated with immunogenicity, and adverse events, were considered. We used a multivariable fractional polynomial modeling approach to estimate the association between anti-SARS-CoV-2 IgG antibodies' geometric mean (GM) ratios and related predictors. Results: We included 595 subjects receiving a third dose with a median (IQR) age of 46 [37], [54], from which 40% reported previous SARS-CoV-2 infection. The overall geometric mean (IQR) of anti-SARS-CoV-2 IgG antibodies was 8,410 (5,115 - 13,000) BAU/mL. Prior SARS-CoV-2 history and full/part-time in-person working modality were significantly associated with greater GM. Conversely, time from boosting to IgG measure was associated with lower GM levels. We found 81% of reactogenicity in the study population; younger age and being a nurse were associated with a lower incidence of adverse events. Conclusions: Among healthcare providers, a booster dose of BNT162b2 following a full BBIBP-CorV regime provided high humoral immune protection. Thus, SARS-CoV-2 previous exposure and working in person displayed as determinants that increase anti-SARS-CoV-2 IgG antibodies.
ABSTRACT
OBJECTIVE: To estimate the prevalence of post-vaccination seropositivity against SARS-CoV-2 and identify its predictors in Peruvian Social Health Insurance (EsSalud) personnel in 2021. METHODS: We conducted a cross-sectional study in a representative simple stratified sample of EsSalud workers. We evaluated IgG anti-SARS-CoV-2 antibodies response (seropositivity) by passive (previous infection) and active immunization (vaccination), and epidemiological and occupational variables obtained by direct interview and a data collection form. Descriptive and inferential statistics were used with correction of sample weights adjusted for non-response rate, and crude and adjusted odds ratio (OR) and geometric mean ratio (GMR) with their respective 95% confidence intervals (95%CI) were estimated. RESULTS: We enrolled 1077 subjects. Seropositivity was 67.4% (95%CI: 63.4-71.1). Predictors of seropositivity were age (negative relation; p < 0.001), previous infection (aOR = 11.7; 95%CI: 7.81-17.5), working in COVID-19 area (aOR = 1.47; 95%CI: 1.02-2.11) and time since the second dose. In relation to antibody levels measured by geometric means, there was an association between male sex (aGMR = 0.77; 95%CI: 0.74-0.80), age (negative relation; p < 0.001), previous infection (aGMR = 13.1; 95%CI:4.99-34.40), non-face-to-face/licensed work modality (aGMR = 0.78; 95%CI: 0.73-0.84), being a nursing technician (aGMR = 1.30; 95%CI: 1.20-1.41), working in administrative areas (aGMR = 1.17; 95%CI: 1.10-1.25), diagnostic support (aGMR = 1.07; 95%CI: 1.01-1.15), critical care (aGMR = 0.85; 95%CI: 0.79-0.93), and in a COVID-19 area (aGMR = 1.30; 95%CI: 1.24-1.36) and time since receiving the second dose (negative relation; p < 0.001). CONCLUSIONS: Seropositivity and antibody levels decrease as the time since receiving the second dose increases. Older age and no history of previous infection were associated with lower seropositivity and antibody values. These findings may be useful for sentinel antibody surveillance and the design of booster dose strategies.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Male , COVID-19/epidemiology , COVID-19/prevention & control , Cross-Sectional Studies , Peru/epidemiology , Antibodies, ViralABSTRACT
Introducción: El filtrado Glomerular es el marcador de función renal más aceptado. Para su estimación se han desarrollado diversos métodos: depuración de creatinina en orina de 24 horas (DCC) o ecuaciones derivadas de la creatinina sérica. Dichas ecuaciones permiten el diagnóstico y estratificación de la Enfermedad Renal Crónica. Las ecuaciones más usadas son MDRD y CKD EPI que incorpora datos sobre edad, sexo, etnia y creatinina sérica. La asociación americana de diabetes en 2010 recomienda el uso de la ecuación MDRD para la estratificación de la ERC en el paciente diabético; Sin embargo en estadios iniciales de daño renal dicha ecuación tiende a subestimar el valor real. A la fecha la ecuación CKD-EPI está demostrando mejor correlación en estadios tempranos de daño sin embargo los estudios no son concluyentes sobre su utilidad. Objetivo: Determinar la correlación y el grado de concordancia entre la ecuación de CKD-EPI y MDRD con la depuración de creatinina en orina de 24 horas para la estimación de la tasa de filtrado glomerular en pacientes diabéticos tipo 2, mayores de edad que acuden al servicio de Patología Clínica sección Bioquímica-depuración de creatinina del HNERM, en el periodo octubre-diciembre 2013. Metodología: Es un estudio Analítico comparativo, prospectivo observacional. Se obtuvo una muestra de 152 pacientes diabéticos, se aplicó el test de correlación de Spearman, se aplicó el coeficiente de correlación de concordancia, y para determinar el bias respecto a la DCC se utilizó la gráfica de Bland Altman. Resultados: Se evaluó las ecuaciones CKD EPI, MDRD 4 con la DCC respectivamente la ecuación CKD EPI tuvo mejor correlación R 0.86, se evaluó el grado de concordancia con el índice Kappa k 0.69 (muy bueno) IC 0.61-0.78, y la ecuación MDRD 4, 0.63, IC 0.56 y 0.71. Se evalúo el bias entre los métodos y se observa en toda la población que la ecuación CKD EPI y MDRD 4 sobrestiman la TFG en relación a la DCC, en -3.1 y -8.1 respectivamente...
Introduction: Glomerular filtration is the most widely accepted marker of renal function. Nowadays, there have been developed various methods: Urine creatinine clearance 24 hours (OCC) or equations derived from serum creatinine. These equations allow the diagnosis and stratification of chronic kidney disease. The MDRD and CKD EPI equations are the most used, which ones incorporate data on age, sex, ethnicity and serum creatinine. At 2010 The American Diabetes Association recommended the use of the MDRD equation for stratification of CKD in diabetic patients; However in early stages of kidney damage this equation tends to underestimate the true value. To date, the CKD-EPI equation is proving better correlation in early stages of damage but studies are inconclusive about its usefulness. Objective: To determine the correlation and the concordance between the CKD-EPI and MDRD with creatinine clearance in 24 hour urine for estimating glomerular filtration rate in type 2 diabetic patients, who came to Clinical Pathology service biochemically creatinine clearance section of HNERM, in the period from October to December 2013. Methods: there was an analytical-comparative, prospective observational study. A sample of 152 diabetic patients was obtained, the Spearman correlation test was applied, the concordance correlation coefficient is applied, and to determine the bias respect to the DCC was used the graph of Bland Altman. Results: it was analyzed CKD EPI and MDRD 4 equations with the DCC respectively the CKD EPI had better correlation R 0.86, the degree of agreement was analyzed with the Kappa index k 0.69 (very good) CI 0.61 to 0.78, and the MOR04 0.63, CI 0.56 to 0.71. The bias between the methods was evaluated; CKD EPI and MDRD 4 overestimate GFR in relation to the DCC, -3.1 and -8.1 respectively, the CKD EPI has lower bias. Conclusions: The CKD EPI is comparable with DCC in 24-hour urine and has better performance and correlation than MDRD equation 4.
