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The aim of this study was to investigate the penetration of cefepime into rat peritoneal fluid by microdialysis and to determine the relationship between unbound drug plasma and tissue concentration in healthy animals and in a sepsis model established through cecal ligation and puncture-induced peritonitis. Probe recovery was performed by dialysis and retrodialysis. Cefepime was administered at a dose of 110 mg/kg intravenously. Samples were collected for about 4 h, and concentrations were determined by liquid chromatography-electrospray ionization-QTOF MS. Tissue penetration was also determined. Probe recovery in vivo was 38.78% ± 3.31% and 38.83% ± 2.74% in the control and peritonitis groups, respectively. Cefepime was rapidly distributed in the peritoneal fluid in both groups. The peritoneal fluid/plasma cefepime ratio was 0.38 and 0.32 for the control and peritonitis groups, respectively. Cefepime concentrations were above the MIC of 4 mg/L for the main enterobacteria. The infection model that was used had no apparent effect on the pharmacokinetics of cefepime in rats. This was the first study to determine free cefepime concentrations in the peritoneal fluid of healthy rats and rats with experimental peritonitis.
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Abstract Introduction: The guidelines recommend estimating the glomerular filtration rate using serum creatinine-based equations as a predictor of kidney disease, preferably adjusted for local population groups. Methods: Cross-sectional study that evaluated the performance of four equations used for estimating GFR compared to endogenous creatinine clearance (ClCr) in 1,281 participants. Modification of Diet equations in Renal Disease Study Group (MDRD), Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), CKD-EPI with adjustment for local population (CKD-EPI local) and Full Age Spectrum (FAS) in comparison with endogenous creatinine clearance (ClCr). We used the Quantile Regression to calculate the median bias, interquartile range (IQR), Bland-Altman agreement analysis and 30% margin of error (P30). Results: The mean age of participants was 52.5 ± 16.5 years with 466 women (38%), median ClCr[IQR] of 92.0 [58.0; 122.0] mL/min/1.73 m2, with 320 (25%) participants presenting ClCr < 60 mL/min/1.73 m2. The performance of the local CKD-EPI and FAS equations were superior to MDRD and CKD-EPI in relation to variability (0.92 [0.89; 0.94]) and P30 (90.5% [88.7; 92, 0]). In the group with ClCr < 60 mL/min/1.73 m2, the local CKD-EPI and FAS equations showed less variability than the CKD-EPI and MDRD (0.90 [0.86; 0.98] and 1.05 [0.97; 1.09] vs. 0.63 [0.61; 0.68] and 0.65 [0.62; 0.70], P < 0.01) and best P30 (85.5) % [81.0; 90.0], 88.0% [84.0; 92.0] vs. 52.0% (46.0; 58.0) and 53.0% [47.0; 58 .5], P < 0.01). Conclusion: Local CKD-EPI and FAS equations performed better than CKD-EPI and MDRD when compared to ClCr.
Resumo Introdução: As diretrizes recomendam a estimativa da taxa de filtração glomerular pelo uso de equações baseadas em creatinina sérica como preditor de doença renal, preferencialmente ajustadas para grupos populacionais locais. Métodos: Estudo transversal que avaliou o desempenho de quatro equações para estimativa da TFG em comparação com a depuração de creatinina endógena (DCE) em 1.281 participantes. Foram avaliadas as equações Modification of Diet in Renal Disease Study Group (MDRD), Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), CKD-EPI com ajuste para a população local (CKD-EPI local) e Full Age Spectrum (FAS) em comparação com a depuração de creatinina endógena (DCE). Utilizamos a Regressão Quantílica para cálculo do viés mediano, intervalo interquartil (IQR), análise de concordância de Bland-Altman e margem de erro de 30% (P30). Resultados: A idade média dos participantes era de 52,5 ± 16,5 anos com 466 mulheres (38%), mediana da DCE [IQR] de 92,0 [58,0; 122,0] mL/min/1,73 m2, com 320 (25%) participantes apresentando DCE < 60 mL/min/1,73 m2. A performance das equações CKD-EPI local e FAS foram superiores às MDRD e CKD-EPI em relação à variabilidade (0,92 [0,89; 0,94]) e P30 (90,5% [88,7; 92,0]). No grupo com DCE < 60 mL/min/1,73 m2, as equações CKD-EPI local e FAS apresentaram menor variabilidade que as CKD-EPI e MDRD (0,90 [0,86; 0,98] e 1,05 [0,97; 1,09] vs. 0,63 [0,61; 0,68] e 0,65 [0,62; 0,70], P < 0,01) e melhores P30 (85,5% [81,0; 90,0], 88,0% [84,0; 92,0] vs. 52,0% (46,0; 58,0) e 53,0% [47,0; 58,5], P < 0,01). Conclusão: As equações CKD-EPI local e FAS tiveram desempenho superior às CKD-EPI e MDRD, quando comparadas a DCE.
ABSTRACT
INTRODUCTION: The guidelines recommend estimating the glomerular filtration rate using serum creatinine-based equations as a predictor of kidney disease, preferably adjusted for local population groups. METHODS: Cross-sectional study that evaluated the performance of four equations used for estimating GFR compared to endogenous creatinine clearance (ClCr) in 1,281 participants. Modification of Diet equations in Renal Disease Study Group (MDRD), Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), CKD-EPI with adjustment for local population (CKD-EPI local) and Full Age Spectrum (FAS) in comparison with endogenous creatinine clearance (ClCr). We used the Quantile Regression to calculate the median bias, interquartile range (IQR), Bland-Altman agreement analysis and 30% margin of error (P30). RESULTS: The mean age of participants was 52.5 ± 16.5 years with 466 women (38%), median ClCr[IQR] of 92.0 [58.0; 122.0] mL/min/1.73 m2, with 320 (25%) participants presenting ClCr < 60 mL/min/1.73 m2. The performance of the local CKD-EPI and FAS equations were superior to MDRD and CKD-EPI in relation to variability (0.92 [0.89; 0.94]) and P30 (90.5% [88.7; 92, 0]). In the group with ClCr < 60 mL/min/1.73 m2, the local CKD-EPI and FAS equations showed less variability than the CKD-EPI and MDRD (0.90 [0.86; 0.98] and 1.05 [0.97; 1.09] vs. 0.63 [0.61; 0.68] and 0.65 [0.62; 0.70], P < 0.01) and best P30 (85.5) % [81.0; 90.0], 88.0% [84.0; 92.0] vs. 52.0% (46.0; 58.0) and 53.0% [47.0; 58 .5], P < 0.01). CONCLUSION: Local CKD-EPI and FAS equations performed better than CKD-EPI and MDRD when compared to ClCr.
Subject(s)
Renal Insufficiency, Chronic , Adult , Aged , Creatinine , Cross-Sectional Studies , Female , Glomerular Filtration Rate , Humans , Middle AgedABSTRACT
Os biomarcadores tumorais em sua maioria são proteínas ou pedaços de proteínas incluindo antígenos de superfície celular, proteínas citoplasmáticas, enzimas e hormônios. O objetivo desse trabalho e revisar quais são os biomarcadores ideais para o rastreamento de câncer de mama e do câncer de pulmão. A busca foi desenvolvida nos meses de fevereiro a março de 2020 através das seguintes bases de dados: Biblioteca Virtual em saúde (BVS), SciELO, PubMed, e o Google acadêmico. Ao todo foram encontrados 28 artigos, sendo artigos originais, revisões e resumos científicos. Os biomarcadores tumorais ideais para o rastreamento de câncer de mama são os receptores hormonais o estrógeno e a progesterona, Cerb B2, Catepsina D, e CA 15.3. Já os biomarcadores tumorais para o rastreamento do câncer de pulmão são os CEA (antígeno carcinoembrionário), TPA (antígeno polipeptídeo tecidual), SCC-Ag (antígeno de carcinoma de células escamosas), Chr A (cromogranina A) e o NSE (enolase neurônio-específica). Conclui-se mediante a realização da revisão bibliográfica, que o estudo dos biomarcadores tumorais tem se mostrado de grande importância no rastreamento do câncer de mama e de pulmão. São eles que orientam a conduta quanto ao prognóstico, grau de estadiamento, tratamento e posteriormente para acompanhar a sua eficácia.
Most tumor biomarkers are proteins or pieces of protein including cell surface antigens, cytoplasmic proteins, enzymes and hormones. The purpose of this work is to review what are the ideal biomarkers for screening for breast cancer and lung cancer. The search was developed from February to March 2020 through the following databases: Virtual Health Library (VHL), Scielo, Pubmed and Google Academic. In all, 28 articles were found, including original articles, reviews, scientific abstracts. The ideal tumor biomarkers for breast cancer screening are the hormone receptors estrogen and progesterone, Cerb B2, Cathepsin D, CA 15.3.The tumor biomarkers for lung cancer screening are CEA (carcinoembryonic antigen), TPA (tissue polypeptide antigen), SCC-Ag (squamous cell carcinoma antigen), Chr A (chromogranin A) and NSE (neuron enolase -specific). It is concluded that by carrying out this literature review, in which the study of tumor biomarkers has shown to be of great importance in screening for breast and lung cancer. They are the ones who guide the conduct regarding prognosis degree of staging, treatment and subsequently to monitor its effectiveness.
