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10.1371/journal.pone.0248438 http://scihub22266oqcxt.onion/10.1371/journal.pone.0248438 33690722!7946184!33690722     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 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       PLoS+One 2021 ; 16 (3): e0248438 Nephropedia Template TP {{tp|p=33690722|t=2021. Clinical prediction rule for SARS-CoV-2 infection from 116 U S emergency departments 2-22-2021 |pdf=|usr=}}{{33690722}} gab.com Text Clinical prediction rule for SARS-CoV-2 infection from 116 U S emergency departments 2-22-2021 JO: PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=33690722 #FOAvip OBJECTIVES: Accurate and reliable criteria to rapidly estimate the probability of infection with the novel coronavirus-2 that causes the severe acute respiratory syndrome (SARS-CoV-2) and associated disease (COVID-19) remain an urgent unmet need, especially in emergency care. The objective was to derive and validate a clinical prediction score for SARS-CoV-2 infection that uses simple criteria widely available at the point of care. METHODS: Data came from the registry data from the national REgistry of suspected COVID-19 in EmeRgency care (RECOVER network) comprising 116 hospitals from 25 states in the US. Clinical variables and 30-day outcomes were abstracted from medical records of 19,850 emergency department (ED) patients tested for SARS-CoV-2. The criterion standard for diagnosis of SARS-CoV-2 required a positive molecular test from a swabbed sample or positive antibody testing within 30 days. The prediction score was derived from a 50% random sample (n = 9,925) using unadjusted analysis of 107 candidate variables as a screening step, followed by stepwise forward logistic regression on 72 variables. RESULTS: Multivariable regression yielded a 13-variable score, which was simplified to a 13-point score: +1 point each for age>50 years, measured temperature>37.5 degrees C, oxygen saturation<95%, Black race, Hispanic or Latino ethnicity, household contact with known or suspected COVID-19, patient reported history of dry cough, anosmia/dysgeusia, myalgias or fever; and -1 point each for White race, no direct contact with infected person, or smoking. In the validation sample (n = 9,975), the probability from logistic regression score produced an area under the receiver operating characteristic curve of 0.80 (95% CI: 0.79-0.81), and this level of accuracy was retained across patients enrolled from the early spring to summer of 2020. In the simplified score, a score of zero produced a sensitivity of 95.6% (94.8-96.3%), specificity of 20.0% (19.0-21.0%), negative likelihood ratio of 0.22 (0.19-0.26). Increasing points on the simplified score predicted higher probability of infection (e.g., >75% probability with +5 or more points). CONCLUSION: Criteria that are available at the point of care can accurately predict the probability of SARS-CoV-2 infection. These criteria could assist with decisions about isolation and testing at high throughput checkpoints. Twit Text FOAVip Clinical prediction rule for SARS-CoV-2 infection from 116 U S emergency departments 2-22-2021 ????PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=33690722 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33690722 #FOAvip English Wikipedia <ref>{{Cite pmid|33690722}}</ref> Clinical prediction rule for SARS-CoV-2 infection from 116 U S emergency departments 2-22-2021 #MMPMID33690722 Kline JA; Camargo CA Jr; Courtney DM; Kabrhel C; Nordenholz KE; Aufderheide T; Baugh JJ; Beiser DG; Bennett CL; Bledsoe J; Castillo E; Chisolm-Straker M; Goldberg EM; House H; House S; Jang T; Lim SC; Madsen TE; McCarthy DM; Meltzer A; Moore S; Newgard C; Pagenhardt J; Pettit KL; Pulia MS; Puskarich MA; Southerland LT; Sparks S; Turner-Lawrence D; Vrablik M; Wang A; Weekes AJ; Westafer L; Wilburn J PLoS One 2021[]; 16 (3): e0248438 PMID33690722show ga OBJECTIVES: Accurate and reliable criteria to rapidly estimate the probability of infection with the novel coronavirus-2 that causes the severe acute respiratory syndrome (SARS-CoV-2) and associated disease (COVID-19) remain an urgent unmet need, especially in emergency care. The objective was to derive and validate a clinical prediction score for SARS-CoV-2 infection that uses simple criteria widely available at the point of care. METHODS: Data came from the registry data from the national REgistry of suspected COVID-19 in EmeRgency care (RECOVER network) comprising 116 hospitals from 25 states in the US. Clinical variables and 30-day outcomes were abstracted from medical records of 19,850 emergency department (ED) patients tested for SARS-CoV-2. The criterion standard for diagnosis of SARS-CoV-2 required a positive molecular test from a swabbed sample or positive antibody testing within 30 days. The prediction score was derived from a 50% random sample (n = 9,925) using unadjusted analysis of 107 candidate variables as a screening step, followed by stepwise forward logistic regression on 72 variables. RESULTS: Multivariable regression yielded a 13-variable score, which was simplified to a 13-point score: +1 point each for age>50 years, measured temperature>37.5 degrees C, oxygen saturation<95%, Black race, Hispanic or Latino ethnicity, household contact with known or suspected COVID-19, patient reported history of dry cough, anosmia/dysgeusia, myalgias or fever; and -1 point each for White race, no direct contact with infected person, or smoking. In the validation sample (n = 9,975), the probability from logistic regression score produced an area under the receiver operating characteristic curve of 0.80 (95% CI: 0.79-0.81), and this level of accuracy was retained across patients enrolled from the early spring to summer of 2020. In the simplified score, a score of zero produced a sensitivity of 95.6% (94.8-96.3%), specificity of 20.0% (19.0-21.0%), negative likelihood ratio of 0.22 (0.19-0.26). Increasing points on the simplified score predicted higher probability of infection (e.g., >75% probability with +5 or more points). CONCLUSION: Criteria that are available at the point of care can accurately predict the probability of SARS-CoV-2 infection. These criteria could assist with decisions about isolation and testing at high throughput checkpoints. |Adult[MESH] |Aged[MESH] |COVID-19/*diagnosis/*epidemiology[MESH] |Clinical Decision Rules[MESH] |Coronavirus Infections/diagnosis[MESH] |Cough[MESH] |Databases, Factual[MESH] |Decision Trees[MESH] |Emergency Service, Hospital/statistics & numerical data/*trends[MESH] |Female[MESH] |Fever[MESH] |Humans[MESH] |Male[MESH] |Mass Screening[MESH] |Middle Aged[MESH] |Registries[MESH] |SARS-CoV-2/pathogenicity[MESH]Clinical prediction rule for SARS-CoV-2 infection from 116 U S emerge(epmc).pdf DeepDyve Pubget Overpricing