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Ned Tijdschr Geneeskd ; 1642020 05 14.
Article in Dutch | MEDLINE | ID: mdl-32406638

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.


Subject(s)
Algorithms , Betacoronavirus , Coronavirus Infections/diagnosis , Emergency Service, Hospital , Pneumonia, Viral/diagnosis , Triage , Adolescent , Adult , Aged , Aged, 80 and over , Betacoronavirus/isolation & purification , COVID-19 , Female , Fever/etiology , Humans , Male , Middle Aged , Pandemics , Retrospective Studies , Risk Assessment , SARS-CoV-2 , Tomography, X-Ray Computed , Young Adult
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