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10.1017/S0950268820002769 http://scihub22266oqcxt.onion/10.1017/S0950268820002769 33183384!7729168!33183384     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Epidemiol+Infect 2020 ; 148 (ä): e273 Nephropedia Template TP {{tp|p=33183384|t=2020. Development and validation of a simple risk score for diagnosing COVID-19 in the emergency room |pdf=|usr=}}{{33183384}} gab.com Text Development and validation of a simple risk score for diagnosing COVID-19 in the emergency room JO: Epidemiol Infect http://www.kidney.de/pget.php?&tw=1&pmid=33183384 #FOAvip As the COVID-19 pandemic continues to escalate and place pressure on hospital system resources, a proper screening and risk stratification score is essential. We aimed to develop a risk score to identify patients with increased risk of COVID-19, allowing proper identification and allocation of limited resources. A retrospective study was conducted of 338 patients who were admitted to the hospital from the emergency room to regular floors and tested for COVID-19 at an acute care hospital in the Metropolitan Washington D.C. area. The dataset was split into development and validation sets with a ratio of 6:4. Demographics, presenting symptoms, sick contact, triage vital signs, initial laboratory and chest X-ray results were analysed to develop a prediction model for COVID-19 diagnosis. Multivariable logistic regression was performed in a stepwise fashion to develop a prediction model, and a scoring system was created based on the coefficients of the final model. Among 338 patients admitted to the hospital from the emergency room, 136 (40.2%) patients tested positive for COVID-19 and 202 (59.8%) patients tested negative. Sick contact with suspected or confirmed COVID-19 case (3 points), nursing facility residence (3 points), constitutional symptom (1 point), respiratory symptom (1 point), gastrointestinal symptom (1 point), obesity (1 point), hypoxia at triage (1 point) and leucocytosis (-1 point) were included in the prediction score. A risk score for COVID-19 diagnosis achieved area under the receiver operating characteristic curve of 0.87 (95% confidence interval (CI) 0.82-0.92) in the development dataset and 0.85 (95% CI 0.78-0.92) in the validation dataset. A risk prediction score for COVID-19 can be used as a supplemental tool to assist clinical decision to triage, test and quarantine patients admitted to the hospital from the emergency room. Twit Text FOAVip Development and validation of a simple risk score for diagnosing COVID-19 in the emergency room ????Epidemiol Infect http://www.kidney.de/pget.php?&tw=1&pmid=33183384 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33183384 #FOAvip English Wikipedia <ref>{{Cite pmid|33183384}}</ref> Development and validation of a simple risk score for diagnosing COVID-19 in the emergency room #MMPMID33183384 Sung J; Choudry N; Bachour R Epidemiol Infect 2020[Nov]; 148 (ä): e273 PMID33183384show ga As the COVID-19 pandemic continues to escalate and place pressure on hospital system resources, a proper screening and risk stratification score is essential. We aimed to develop a risk score to identify patients with increased risk of COVID-19, allowing proper identification and allocation of limited resources. A retrospective study was conducted of 338 patients who were admitted to the hospital from the emergency room to regular floors and tested for COVID-19 at an acute care hospital in the Metropolitan Washington D.C. area. The dataset was split into development and validation sets with a ratio of 6:4. Demographics, presenting symptoms, sick contact, triage vital signs, initial laboratory and chest X-ray results were analysed to develop a prediction model for COVID-19 diagnosis. Multivariable logistic regression was performed in a stepwise fashion to develop a prediction model, and a scoring system was created based on the coefficients of the final model. Among 338 patients admitted to the hospital from the emergency room, 136 (40.2%) patients tested positive for COVID-19 and 202 (59.8%) patients tested negative. Sick contact with suspected or confirmed COVID-19 case (3 points), nursing facility residence (3 points), constitutional symptom (1 point), respiratory symptom (1 point), gastrointestinal symptom (1 point), obesity (1 point), hypoxia at triage (1 point) and leucocytosis (-1 point) were included in the prediction score. A risk score for COVID-19 diagnosis achieved area under the receiver operating characteristic curve of 0.87 (95% confidence interval (CI) 0.82-0.92) in the development dataset and 0.85 (95% CI 0.78-0.92) in the validation dataset. A risk prediction score for COVID-19 can be used as a supplemental tool to assist clinical decision to triage, test and quarantine patients admitted to the hospital from the emergency room. |*Emergency Service, Hospital[MESH] |*SARS-CoV-2[MESH] |Aged[MESH] |COVID-19/*diagnosis/epidemiology[MESH] |Cohort Studies[MESH] |Female[MESH] |Hospitalization[MESH] |Humans[MESH] |Male[MESH] |Maryland[MESH] |Middle Aged[MESH] |Nursing Homes[MESH] |Pandemics[MESH] |Retrospective Studies[MESH]Development and validation of a simple risk score for diagnosing COVID(epmc).pdf DeepDyve Pubget Overpricing