A S M Dofferhoff1,2, A Swinkels3, T Sprong1, Y Berk4, M Spanbroek4, M H Nabuurs-Franssen3, M Vermaat5, B van de Kerkhof6, M H C Willekens6, A Voss3. 1. Canisius-Wilhelmina Ziekenhuis, afd. Interne Geneeskunde, Nijmegen. 2. Contact: A.S.M. Dofferhoff (a.dofferhoff@cwz.nl). 3. Canisius-Wilhelmina Ziekenhuis, afd. Medische Microbiologie, Nijmegen. 4. Canisius-Wilhelmina Ziekenhuis, afd. Longziekten, Nijmegen. 5. Canisius-Wilhelmina Ziekenhuis, afd. Radiologie, Nijmegen. 6. Canisius-Wilhelmina Ziekenhuis, afd. SEH, Nijmegen.
Abstract
OBJECTIVE: Evaluation of a diagnostic algorithm for estimating the risk of COVID-19 in patients who are referred to an emergency department for being suspected of having the disease. DESIGN: Retrospective study. METHOD: Patients with fever with no apparent cause and patients with recently developed respiratory symptoms, whether or not in combination with fever, were routinely given a PCR test, blood tests (lymphocyte count and LDH levels) and a chest CT scan. The CT scan was assessed according to the CO-RADS classification. Based on the findings, the patients were divided into 3 cohorts (proven COVID-19, strong suspicion of COVID-19, and low suspicion of COVID-19) and the appropriate isolation measures were taken. RESULTS: In the period from 8 to 31 March 2020, the algorithm was applied to 312 patients. COVID-19 was proven for 69 (22%) patients. COVID-19 was strongly suspected for 151 (48%) patients and suspicion was low for the remaining 92 (29%) patients. The percentage of patients with positive PCR results and the percentage of patients with abnormal laboratory test results increased as the CO-RADS score increased. Among patients with a CO-RADS score of 4 or 5, this percentage increased further when they also had lymphopenia or elevated LDH levels. We have adjusted the flowchart based on our findings. CONCLUSION: In case of patients who have been referred to an emergency department for suspected COVID-19, a good COVID-19 risk assessment can be made on the basis of clinical signs, laboratory abnormalities and low-dose CT scans. Even before the results of the PCR test are known and even if the results are negative, patients can be classified as 'proven COVID-19 patients' using the algorithm.
OBJECTIVE: Evaluation of a diagnostic algorithm for estimating the risk of COVID-19 in patients who are referred to an emergency department for being suspected of having the disease. DESIGN: Retrospective study. METHOD:Patients with fever with no apparent cause and patients with recently developed respiratory symptoms, whether or not in combination with fever, were routinely given a PCR test, blood tests (lymphocyte count and LDH levels) and a chest CT scan. The CT scan was assessed according to the CO-RADS classification. Based on the findings, the patients were divided into 3 cohorts (proven COVID-19, strong suspicion of COVID-19, and low suspicion of COVID-19) and the appropriate isolation measures were taken. RESULTS: In the period from 8 to 31 March 2020, the algorithm was applied to 312 patients. COVID-19 was proven for 69 (22%) patients. COVID-19 was strongly suspected for 151 (48%) patients and suspicion was low for the remaining 92 (29%) patients. The percentage of patients with positive PCR results and the percentage of patients with abnormal laboratory test results increased as the CO-RADS score increased. Among patients with a CO-RADS score of 4 or 5, this percentage increased further when they also had lymphopenia or elevated LDH levels. We have adjusted the flowchart based on our findings. CONCLUSION: In case of patients who have been referred to an emergency department for suspected COVID-19, a good COVID-19 risk assessment can be made on the basis of clinical signs, laboratory abnormalities and low-dose CT scans. Even before the results of the PCR test are known and even if the results are negative, patients can be classified as 'proven COVID-19patients' using the algorithm.
Authors: Sanam Ebrahimzadeh; Nayaar Islam; Haben Dawit; Jean-Paul Salameh; Sakib Kazi; Nicholas Fabiano; Lee Treanor; Marissa Absi; Faraz Ahmad; Paul Rooprai; Ahmed Al Khalil; Kelly Harper; Neil Kamra; Mariska Mg Leeflang; Lotty Hooft; Christian B van der Pol; Ross Prager; Samanjit S Hare; Carole Dennie; René Spijker; Jonathan J Deeks; Jacqueline Dinnes; Kevin Jenniskens; Daniël A Korevaar; Jérémie F Cohen; Ann Van den Bruel; Yemisi Takwoingi; Janneke van de Wijgert; Junfeng Wang; Elena Pena; Sandra Sabongui; Matthew Df McInnes Journal: Cochrane Database Syst Rev Date: 2022-05-16
Authors: Nikolas Lessmann; Clara I Sánchez; Ludo Beenen; Luuk H Boulogne; Monique Brink; Erdi Calli; Jean-Paul Charbonnier; Ton Dofferhoff; Wouter M van Everdingen; Paul K Gerke; Bram Geurts; Hester A Gietema; Miriam Groeneveld; Louis van Harten; Nils Hendrix; Ward Hendrix; Henkjan J Huisman; Ivana Išgum; Colin Jacobs; Ruben Kluge; Michel Kok; Jasenko Krdzalic; Bianca Lassen-Schmidt; Kicky van Leeuwen; James Meakin; Mike Overkamp; Tjalco van Rees Vellinga; Eva M van Rikxoort; Riccardo Samperna; Cornelia Schaefer-Prokop; Steven Schalekamp; Ernst Th Scholten; Cheryl Sital; Lauran Stöger; Jonas Teuwen; Kiran Vaidhya Venkadesh; Coen de Vente; Marieke Vermaat; Weiyi Xie; Bram de Wilde; Mathias Prokop; Bram van Ginneken Journal: Radiology Date: 2020-07-30 Impact factor: 11.105
Authors: Nayaar Islam; Sanam Ebrahimzadeh; Jean-Paul Salameh; Sakib Kazi; Nicholas Fabiano; Lee Treanor; Marissa Absi; Zachary Hallgrimson; Mariska Mg Leeflang; Lotty Hooft; Christian B van der Pol; Ross Prager; Samanjit S Hare; Carole Dennie; René Spijker; Jonathan J Deeks; Jacqueline Dinnes; Kevin Jenniskens; Daniël A Korevaar; Jérémie F Cohen; Ann Van den Bruel; Yemisi Takwoingi; Janneke van de Wijgert; Johanna Aag Damen; Junfeng Wang; Matthew Df McInnes Journal: Cochrane Database Syst Rev Date: 2021-03-16