Repetition of microbiological tests in suspect of SARS-CoV-2 infection: utility of a score based on clinical probability

Abstract

Background. The diagnosis of SARS-CoV-2 infection presents some limitations. RT-PCR in nasopharyngeal swabs is considered the gold standard for the diagnosis, although it can have false negative results. We aimed to analyze the accuracy of repeating nasopharyngeal swabs based on different clinical probabilities. Methods. Retrospective observational study of the first patients admitted to a two COVID Internal Medicine wards at the University Hospital Marqués de Valdecilla, Santander, from March to April 2020. RT-PCR targering E, N, RdRP and ORFab1 genes and antibody tests detecting IgG. Results. A total of 145 hospitalized patients with suspected SARS-Cov2 infection were admitted and in 98 (67.5%) diagnosis was confirmed. The independent predictive variables for SARS-CoV-2 infection were: epidemiological contact, clinical presentation as pneumonia, absence of pneumonia in the last year, onset of symptoms > 7 days, two or more of the following symptoms -dyspnea, cough or fever- and serum lactate dehydrogenase levels >350 U/L (p<0.05). A score based on these variables yielded an AUC-ROC of 0.89 (CI95%, 0.831-0.946; p<0.001). The accuracy of the first nasopharyngeal swabs was 54.9%. Repeating nasopharyngeal swabs two or three times allows to detect an additional 16% of positive cases. The overall accuracy of successive RT-PCR tests in patients with low pre-test probability was <5%. Conclusions. We have defined a pre-test probability score based on epidemiological and clinical data with a high accuracy for diagnosis of SARS-CoV-2. Repeating nasopharyngeal swabs avoids sampling errors, but only in medium of high probability pre-test clinical scenarios.

Evaluation of Diagnostic Strategies for Identifying SARS-CoV-2 Infection in Clinical Practice: a Systematic Review and Compliance with the Standards for Reporting Diagnostic Accuracy Studies Guideline (STARD)

“…Of the 16 studies which focused on symptomatic patients with suspected SARS-CoV-2 infection ( 12 – 27 ), seven included techniques related with artificial intelligence (AI) ( 12 – 18 ): five of them used a cohort study, either retrospective ( 12 , 13 , 17 , 18 ) or prospective ( 14 ), and two used a cross-sectional study ( 15 , 16 ). The other nine studies developed an algorithm ( 19 , 24 , 26 ) or a probability score ( 20 – 23 , 25 , 27 ) to diagnose infection by SARS-CoV-2. Four of them used a cross-sectional study ( 22 – 25 ), four used a retrospective cohort study ( 19 – 21 , 26 ), and one used a prospective cohort study ( 27 ).…”

“…The other nine studies developed an algorithm ( 19 , 24 , 26 ) or a probability score ( 20 – 23 , 25 , 27 ) to diagnose infection by SARS-CoV-2. Four of them used a cross-sectional study ( 22 – 25 ), four used a retrospective cohort study ( 19 – 21 , 26 ), and one used a prospective cohort study ( 27 ). Most of the studies included symptomatic patients who were admitted to a hospital due to suspected COVID-19; Trubiano JA et al’s study ( 24 ) included patients assessed for COVID-19 at a screening clinic due to symptoms (98.3%), contact with known COVID-19-positive patient (17.3%), or those who had traveled abroad (24.6%), and Elimian KO et al ( 26 ) included symptomatic patients and also those concerned about COVID-19 infection.…”

Herd Immunity to Fight Against COVID-19: A Narrative Review

“…Accordingly, the methodology for developing vaccines becomes more demanding and challenging to achieve enough efficiency to oppose the new variant. Furthermore, several severe issues exist regarding the generation of herd immunity in COVID-19 [12]. Table 1 shows the percentage of the population vaccinated with single, double, and booster doses.…”