Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1007/s10140-020-01821-1 http://scihub22266oqcxt.onion/10.1007/s10140-020-01821-1 32691211!7369539!32691211     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       Emerg+Radiol 2020 ; 27 (6): 641-651 Nephropedia Template TP {{tp|p=32691211|t=2020. Chest CT for triage during COVID-19 on the emergency department: myth or truth?|pdf=|usr=}}{{32691211}} gab.com Text Chest CT for triage during COVID-19 on the emergency department: myth or truth JO: Emerg Radiol http://www.kidney.de/pget.php?&tw=1&pmid=32691211 #FOAvip PURPOSE: We aimed to investigate the diagnostic performance of chest CT compared with first RT-PCR results in adult patients suspected of COVID-19 infection in an ED setting. We also constructed a predictive machine learning model based on chest CT and additional data to improve the diagnostic accuracy of chest CT. METHODS: This study's cohort consisted of 319 patients who underwent chest CT and RT-PCR testing at the ED. Patient characteristics, demographics, symptoms, vital signs, laboratory tests, and chest CT results (CO-RADS) were collected. With first RT-PCR as reference standard, the diagnostic performance of chest CT using the CO-RADS score was assessed. Additionally, a predictive machine learning model was constructed using logistic regression. RESULTS: Chest CT, with first RT-PCR as a reference, had a sensitivity, specificity, PPV, and NPV of 90.2%, 88.2%, 84.5%, and 92.7%, respectively. The prediction model with CO-RADS, ferritin, leucocyte count, CK, days of complaints, and diarrhea as predictors had a sensitivity, specificity, PPV, and NPV of 89.3%, 93.4%, 90.8%, and 92.3%, respectively. CONCLUSION: Chest CT, using the CO-RADS scoring system, is a sensitive and specific method that can aid in the diagnosis of COVID-19, especially if RT-PCR tests are scarce during an outbreak. Combining a predictive machine learning model could further improve the accuracy of diagnostic chest CT for COVID-19. Further candidate predictors should be analyzed to improve our model. However, RT-PCR should remain the primary standard of testing as up to 9% of RT-PCR positive patients are not diagnosed by chest CT or our machine learning model. Twit Text FOAVip Chest CT for triage during COVID-19 on the emergency department: myth or truth ????Emerg Radiol http://www.kidney.de/pget.php?&tw=1&pmid=32691211 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32691211 #FOAvip English Wikipedia <ref>{{Cite pmid|32691211}}</ref> Chest CT for triage during COVID-19 on the emergency department: myth or truth? #MMPMID32691211 Hermans JJR; Groen J; Zwets E; Boxma-De Klerk BM; Van Werkhoven JM; Ong DSY; Hanselaar WEJJ; Waals-Prinzen L; Brown V Emerg Radiol 2020[Dec]; 27 (6): 641-651 PMID32691211show ga PURPOSE: We aimed to investigate the diagnostic performance of chest CT compared with first RT-PCR results in adult patients suspected of COVID-19 infection in an ED setting. We also constructed a predictive machine learning model based on chest CT and additional data to improve the diagnostic accuracy of chest CT. METHODS: This study's cohort consisted of 319 patients who underwent chest CT and RT-PCR testing at the ED. Patient characteristics, demographics, symptoms, vital signs, laboratory tests, and chest CT results (CO-RADS) were collected. With first RT-PCR as reference standard, the diagnostic performance of chest CT using the CO-RADS score was assessed. Additionally, a predictive machine learning model was constructed using logistic regression. RESULTS: Chest CT, with first RT-PCR as a reference, had a sensitivity, specificity, PPV, and NPV of 90.2%, 88.2%, 84.5%, and 92.7%, respectively. The prediction model with CO-RADS, ferritin, leucocyte count, CK, days of complaints, and diarrhea as predictors had a sensitivity, specificity, PPV, and NPV of 89.3%, 93.4%, 90.8%, and 92.3%, respectively. CONCLUSION: Chest CT, using the CO-RADS scoring system, is a sensitive and specific method that can aid in the diagnosis of COVID-19, especially if RT-PCR tests are scarce during an outbreak. Combining a predictive machine learning model could further improve the accuracy of diagnostic chest CT for COVID-19. Further candidate predictors should be analyzed to improve our model. However, RT-PCR should remain the primary standard of testing as up to 9% of RT-PCR positive patients are not diagnosed by chest CT or our machine learning model. |*Emergency Service, Hospital[MESH] |*Triage[MESH] |Adolescent[MESH] |Adult[MESH] |Aged[MESH] |Aged, 80 and over[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |COVID-19 Testing[MESH] |COVID-19 Vaccines[MESH] |Clinical Laboratory Techniques[MESH] |Coronavirus Infections/diagnosis/*diagnostic imaging/epidemiology[MESH] |Female[MESH] |Humans[MESH] |Machine Learning[MESH] |Male[MESH] |Middle Aged[MESH] |Netherlands/epidemiology[MESH] |Pandemics[MESH] |Pneumonia, Viral/*diagnostic imaging/epidemiology[MESH] |Prospective Studies[MESH] |Radiography, Thoracic/*methods[MESH] |SARS-CoV-2[MESH] |Sensitivity and Specificity[MESH]Chest CT for triage during COVID-19 on the emergency department: myth (epmc).pdf DeepDyve Pubget Overpricing