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10.37201/req/060.2020 http://scihub22266oqcxt.onion/10.37201/req/060.2020 32657550!7374038!32657550     free     free     free Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Rev+Esp+Quimioter 2020 ; 33 (4): 267-273 Nephropedia Template TP {{tp|p=32657550|t=2020. Potenciales biomarcadores predictores de mortalidad en pacientes COVID-19 en el Servicio de Urgencias |pdf=|usr=}}{{32657550}} gab.com Text Potenciales biomarcadores predictores de mortalidad en pacientes COVID-19 en el Servicio de Urgencias JO: Rev Esp Quimioter http://www.kidney.de/pget.php?&tw=1&pmid=32657550 #FOAvip OBJECTIVE: Identify which biomarkers performed in the first emergency analysis help to stratify COVID-19 patients according to mortality risk. METHODS: Observational, descriptive and cross-sectional study performed with data collected from patients with suspected COVID-19 in the Emergency Department from February 24 to March 16, 2020. The univariate and multivariate study was performed to find independent mortality markers and calculate risk by building a severity score. RESULTS: A total of 163 patients were included, of whom 33 died and 29 of them were positive for the COVID-19 PCR test. We obtained as possible factors to conform the Mortality Risk Score age> 75 years ((adjusted OR = 12,347, 95% CI: 4,138-36,845 p = 0.001), total leukocytes> 11,000 cells / mm3 (adjusted OR = 2,649, 95% CI: 0.879-7.981 p = 0.083), glucose> 126 mg / dL (adjusted OR = 3.716, 95% CI: 1.247-11.074 p = 0.018) and creatinine> 1.1 mg / dL (adjusted OR = 2.566, 95% CI: 0.889- 7.403, p = 0.081) This score was called COVEB (COVID, Age, Basic analytical profile) with an AUC 0.874 (95% CI: 0.816-0.933, p <0.001; Cut-off point = 1 (sensitivity = 89.66 % (95% CI: 72.6% -97.8%), specificity = 75.59% (95% CI: 67.2% -82.8%). A score <1 has a negative predictive value = 100% (95% CI: 93.51% -100%) and a positive predictive value = 18.59% (95% CI: 12.82% -25.59%). CONCLUSIONS: Clinical severity scales, kidney function biomarkers, white blood cell count parameters, the total neutrophils / total lymphocytes ratio and procalcitonin are early risk factors for mortality. The variables age, glucose, creatinine and total leukocytes stand out as the best predictors of mortality. A COVEB score <1 indicates with a 100% probability that the patient with suspected COVID-19 will not die in the next 30 days. Twit Text FOAVip Potenciales biomarcadores predictores de mortalidad en pacientes COVID-19 en el Servicio de Urgencias ????Rev Esp Quimioter http://www.kidney.de/pget.php?&tw=1&pmid=32657550 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32657550 #FOAvip English Wikipedia <ref>{{Cite pmid|32657550}}</ref> Potenciales biomarcadores predictores de mortalidad en pacientes COVID-19 en el Servicio de Urgencias #MMPMID32657550 Pascual Gomez NF; Monge Lobo I; Granero Cremades I; Figuerola Tejerina A; Ramasco Rueda F; von Wernitz Teleki A; Arrabal Campos FM; Sanz de Benito MA Rev Esp Quimioter 2020[Aug]; 33 (4): 267-273 PMID32657550show ga OBJECTIVE: Identify which biomarkers performed in the first emergency analysis help to stratify COVID-19 patients according to mortality risk. METHODS: Observational, descriptive and cross-sectional study performed with data collected from patients with suspected COVID-19 in the Emergency Department from February 24 to March 16, 2020. The univariate and multivariate study was performed to find independent mortality markers and calculate risk by building a severity score. RESULTS: A total of 163 patients were included, of whom 33 died and 29 of them were positive for the COVID-19 PCR test. We obtained as possible factors to conform the Mortality Risk Score age> 75 years ((adjusted OR = 12,347, 95% CI: 4,138-36,845 p = 0.001), total leukocytes> 11,000 cells / mm3 (adjusted OR = 2,649, 95% CI: 0.879-7.981 p = 0.083), glucose> 126 mg / dL (adjusted OR = 3.716, 95% CI: 1.247-11.074 p = 0.018) and creatinine> 1.1 mg / dL (adjusted OR = 2.566, 95% CI: 0.889- 7.403, p = 0.081) This score was called COVEB (COVID, Age, Basic analytical profile) with an AUC 0.874 (95% CI: 0.816-0.933, p <0.001; Cut-off point = 1 (sensitivity = 89.66 % (95% CI: 72.6% -97.8%), specificity = 75.59% (95% CI: 67.2% -82.8%). A score <1 has a negative predictive value = 100% (95% CI: 93.51% -100%) and a positive predictive value = 18.59% (95% CI: 12.82% -25.59%). CONCLUSIONS: Clinical severity scales, kidney function biomarkers, white blood cell count parameters, the total neutrophils / total lymphocytes ratio and procalcitonin are early risk factors for mortality. The variables age, glucose, creatinine and total leukocytes stand out as the best predictors of mortality. A COVEB score <1 indicates with a 100% probability that the patient with suspected COVID-19 will not die in the next 30 days. |*Betacoronavirus[MESH] |Age Factors[MESH] |Aged[MESH] |Analysis of Variance[MESH] |Area Under Curve[MESH] |Biomarkers/blood[MESH] |Blood Glucose/analysis[MESH] |COVID-19[MESH] |Coronavirus Infections/*blood/diagnosis/*mortality[MESH] |Creatinine/blood[MESH] |Cross-Sectional Studies[MESH] |Emergency Service, Hospital[MESH] |Female[MESH] |Humans[MESH] |Hypertension/mortality[MESH] |Leukocyte Count[MESH] |Male[MESH] |Odds Ratio[MESH] |Pandemics[MESH] |Pneumonia, Viral/*blood/diagnosis/*mortality[MESH] |Predictive Value of Tests[MESH] |Retrospective Studies[MESH] |Reverse Transcriptase Polymerase Chain Reaction[MESH] |Risk Assessment/methods[MESH] |SARS-CoV-2[MESH]Potenciales biomarcadores predictores de mortalidad en pacientes COVID(epmc).pdf DeepDyve Pubget Overpricing