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10.1016/j.resuscitation.2020.08.124 http://scihub22266oqcxt.onion/10.1016/j.resuscitation.2020.08.124 32918985!7480278!32918985     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Resuscitation 2020 ; 156 (ä): 84-91 Nephropedia Template TP {{tp|p=32918985|t=2020. Predicting intensive care unit admission and death for COVID-19 patients in the emergency department using early warning scores |pdf=|usr=}}{{32918985}} gab.com Text Predicting intensive care unit admission and death for COVID-19 patients in the emergency department using early warning scores JO: Resuscitation http://www.kidney.de/pget.php?&tw=1&pmid=32918985 #FOAvip AIMS: To identify the most accurate early warning score (EWS) for predicting an adverse outcome in COVID-19 patients admitted to the emergency department (ED). METHODS: In adult consecutive patients admitted (March 1-April 15, 2020) to the ED of a major referral centre for COVID-19, we retrospectively calculated NEWS, NEWS2, NEWS-C, MEWS, qSOFA, and REMS from physiological variables measured on arrival. Sensitivity, specificity, positive (PPV) and negative predictive value (NPV), and the area under the receiver operating characteristic (AUROC) curve of each EWS for predicting admission to the intensive care unit (ICU) and death at 48?h and 7 days were calculated. RESULTS: We included 334 patients (119 [35.6%] females, median age 66 [54-78] years). At 7 days, the rates of ICU admission and death were 56/334 (17%) and 26/334 (7.8%), respectively. NEWS was the most accurate predictor of ICU admission within 7 days (AUROC 0.783 [95% CI, 0.735-0.826]; sensitivity 71.4 [57.8-82.7]%; NPV 93.1 [89.8-95.3]%), while REMS was the most accurate predictor of death within 7 days (AUROC 0.823 [0.778-0.863]; sensitivity 96.1 [80.4-99.9]%; NPV 99.4[96.2-99.9]%). Similar results were observed for ICU admission and death at 48?h. NEWS and REMS were as accurate as the triage system used in our ED. MEWS and qSOFA had the lowest overall accuracy for both outcomes. CONCLUSION: In our single-centre cohort of COVID-19 patients, NEWS and REMS measured on ED arrival were the most sensitive predictors of 7-day ICU admission or death. EWS could be useful to identify patients with low risk of clinical deterioration. Twit Text FOAVip Predicting intensive care unit admission and death for COVID-19 patients in the emergency department using early warning scores ????Resuscitation http://www.kidney.de/pget.php?&tw=1&pmid=32918985 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32918985 #FOAvip English Wikipedia <ref>{{Cite pmid|32918985}}</ref> Predicting intensive care unit admission and death for COVID-19 patients in the emergency department using early warning scores #MMPMID32918985 Covino M; Sandroni C; Santoro M; Sabia L; Simeoni B; Bocci MG; Ojetti V; Candelli M; Antonelli M; Gasbarrini A; Franceschi F Resuscitation 2020[Nov]; 156 (ä): 84-91 PMID32918985show ga AIMS: To identify the most accurate early warning score (EWS) for predicting an adverse outcome in COVID-19 patients admitted to the emergency department (ED). METHODS: In adult consecutive patients admitted (March 1-April 15, 2020) to the ED of a major referral centre for COVID-19, we retrospectively calculated NEWS, NEWS2, NEWS-C, MEWS, qSOFA, and REMS from physiological variables measured on arrival. Sensitivity, specificity, positive (PPV) and negative predictive value (NPV), and the area under the receiver operating characteristic (AUROC) curve of each EWS for predicting admission to the intensive care unit (ICU) and death at 48?h and 7 days were calculated. RESULTS: We included 334 patients (119 [35.6%] females, median age 66 [54-78] years). At 7 days, the rates of ICU admission and death were 56/334 (17%) and 26/334 (7.8%), respectively. NEWS was the most accurate predictor of ICU admission within 7 days (AUROC 0.783 [95% CI, 0.735-0.826]; sensitivity 71.4 [57.8-82.7]%; NPV 93.1 [89.8-95.3]%), while REMS was the most accurate predictor of death within 7 days (AUROC 0.823 [0.778-0.863]; sensitivity 96.1 [80.4-99.9]%; NPV 99.4[96.2-99.9]%). Similar results were observed for ICU admission and death at 48?h. NEWS and REMS were as accurate as the triage system used in our ED. MEWS and qSOFA had the lowest overall accuracy for both outcomes. CONCLUSION: In our single-centre cohort of COVID-19 patients, NEWS and REMS measured on ED arrival were the most sensitive predictors of 7-day ICU admission or death. EWS could be useful to identify patients with low risk of clinical deterioration. |*Betacoronavirus[MESH] |Aged[MESH] |COVID-19[MESH] |Coronavirus Infections/epidemiology/*therapy[MESH] |Early Warning Score[MESH] |Female[MESH] |Hospital Mortality/trends[MESH] |Humans[MESH] |Intensive Care Units/*statistics & numerical data[MESH] |Italy/epidemiology[MESH] |Male[MESH] |Middle Aged[MESH] |Pandemics[MESH] |Patient Admission/*statistics & numerical data[MESH] |Pneumonia, Viral/epidemiology/*therapy[MESH] |ROC Curve[MESH] |Retrospective Studies[MESH] |Risk Assessment/*methods[MESH] |SARS-CoV-2[MESH] |Survival Rate/trends[MESH]Predicting intensive care unit admission and death for COVID-19 patien(epmc).pdf DeepDyve Pubget Overpricing