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10.1016/j.trsl.2021.05.004 http://scihub22266oqcxt.onion/10.1016/j.trsl.2021.05.004 34048985!8149473!34048985     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Transl+Res 2021 ; 236 (ä): 147-159 Nephropedia Template TP {{tp|p=34048985|t=2021. Circulating microRNA profiles predict the severity of COVID-19 in hospitalized patients |pdf=|usr=}}{{34048985}} gab.com Text Circulating microRNA profiles predict the severity of COVID-19 in hospitalized patients JO: Transl Res http://www.kidney.de/pget.php?&tw=1&pmid=34048985 #FOAvip We aimed to examine the circulating microRNA (miRNA) profile of hospitalized COVID-19 patients and evaluate its potential as a source of biomarkers for the management of the disease. This was an observational and multicenter study that included 84 patients with a positive nasopharyngeal swab Polymerase chain reaction (PCR) test for SARS-CoV-2 recruited during the first pandemic wave in Spain (March-June 2020). Patients were stratified according to disease severity: hospitalized patients admitted to the clinical wards without requiring critical care and patients admitted to the intensive care unit (ICU). An additional study was completed including ICU nonsurvivors and survivors. Plasma miRNA profiling was performed using reverse transcription polymerase quantitative chain reaction (RT-qPCR). Predictive models were constructed using least absolute shrinkage and selection operator (LASSO) regression. Ten circulating miRNAs were dysregulated in ICU patients compared to ward patients. LASSO analysis identified a signature of three miRNAs (miR-148a-3p, miR-451a and miR-486-5p) that distinguishes between ICU and ward patients [AUC (95% CI) = 0.89 (0.81-0.97)]. Among critically ill patients, six miRNAs were downregulated between nonsurvivors and survivors. A signature based on two miRNAs (miR-192-5p and miR-323a-3p) differentiated ICU nonsurvivors from survivors [AUC (95% CI) = 0.80 (0.64-0.96)]. The discriminatory potential of the signature was higher than that observed for laboratory parameters such as leukocyte counts, C-reactive protein (CRP) or D-dimer [maximum AUC (95% CI) for these variables = 0.73 (0.55-0.92)]. miRNA levels were correlated with the duration of ICU stay. Specific circulating miRNA profiles are associated with the severity of COVID-19. Plasma miRNA signatures emerge as a novel tool to assist in the early prediction of vital status deterioration among ICU patients. Twit Text FOAVip Circulating microRNA profiles predict the severity of COVID-19 in hospitalized patients ????Transl Res http://www.kidney.de/pget.php?&tw=1&pmid=34048985 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34048985 #FOAvip English Wikipedia <ref>{{Cite pmid|34048985}}</ref> Circulating microRNA profiles predict the severity of COVID-19 in hospitalized patients #MMPMID34048985 de Gonzalo-Calvo D; Benitez ID; Pinilla L; Carratala A; Moncusi-Moix A; Gort-Paniello C; Molinero M; Gonzalez J; Torres G; Bernal M; Pico S; Almansa R; Jorge N; Ortega A; Bustamante-Munguira E; Gomez JM; Gonzalez-Rivera M; Micheloud D; Ryan P; Martinez A; Tamayo L; Aldecoa C; Ferrer R; Ceccato A; Fernandez-Barat L; Motos A; Riera J; Menendez R; Garcia-Gasulla D; Penuelas O; Torres A; Bermejo-Martin JF; Barbe F Transl Res 2021[Oct]; 236 (ä): 147-159 PMID34048985show ga We aimed to examine the circulating microRNA (miRNA) profile of hospitalized COVID-19 patients and evaluate its potential as a source of biomarkers for the management of the disease. This was an observational and multicenter study that included 84 patients with a positive nasopharyngeal swab Polymerase chain reaction (PCR) test for SARS-CoV-2 recruited during the first pandemic wave in Spain (March-June 2020). Patients were stratified according to disease severity: hospitalized patients admitted to the clinical wards without requiring critical care and patients admitted to the intensive care unit (ICU). An additional study was completed including ICU nonsurvivors and survivors. Plasma miRNA profiling was performed using reverse transcription polymerase quantitative chain reaction (RT-qPCR). Predictive models were constructed using least absolute shrinkage and selection operator (LASSO) regression. Ten circulating miRNAs were dysregulated in ICU patients compared to ward patients. LASSO analysis identified a signature of three miRNAs (miR-148a-3p, miR-451a and miR-486-5p) that distinguishes between ICU and ward patients [AUC (95% CI) = 0.89 (0.81-0.97)]. Among critically ill patients, six miRNAs were downregulated between nonsurvivors and survivors. A signature based on two miRNAs (miR-192-5p and miR-323a-3p) differentiated ICU nonsurvivors from survivors [AUC (95% CI) = 0.80 (0.64-0.96)]. The discriminatory potential of the signature was higher than that observed for laboratory parameters such as leukocyte counts, C-reactive protein (CRP) or D-dimer [maximum AUC (95% CI) for these variables = 0.73 (0.55-0.92)]. miRNA levels were correlated with the duration of ICU stay. Specific circulating miRNA profiles are associated with the severity of COVID-19. Plasma miRNA signatures emerge as a novel tool to assist in the early prediction of vital status deterioration among ICU patients. |*Hospitalization[MESH] |*Severity of Illness Index[MESH] |Aged[MESH] |Biomarkers/blood[MESH] |COVID-19/*blood/*genetics/virology[MESH] |Circulating MicroRNA/*blood[MESH] |Critical Illness[MESH] |Female[MESH] |Humans[MESH] |Intensive Care Units[MESH] |Male[MESH]Circulating microRNA profiles predict the severity of COVID-19 in hosp(epmc).pdf DeepDyve Pubget Overpricing