Interpreting a covid-19 test result

1 PRACTICE POINTERI nterpreting a covid-19 test resultJessica Watson GP and National Institute for Health Research doctoral research fellow 1, Penny FWhiting associate professor in clinical epidemiology 1, John E Brush professor of internal medicine 21 Centre for Academic Primary Care, Bristol Medical School, University of Bristol, Bristol, UK; 2 Sentara Healthcare and Eastern Virginia MedicalSchool, Norfolk, VA, USAWhat you need to know Interpreting the result of a test for covid-19 depends on two things: theaccuracy of the test, and the pre-test probability or estimated risk ofdisease before testing A positive RT-PCR test for covid-19 test has more weight than a negativetest because of the test s high specificity but moderate sensitivity A single negative covid-19 test should not be used as a rule-out inpatients with strongly suggestive symptoms Clinicians should share information with patients about the accuracy ofcovid-19 testsAcross the world there is a clamour for covid-19 testing, withTedros Adhanom Ghebreyesus, director general of the WorldHealth Organization, encouraging countries to test, test, test.

2 1 The availability of the complete genome of covid-19 early inthe epidemic facilitated development of tests to detect Multiple assays with different gene targets have beendeveloped using reverse transcriptase polymerase chain reaction(RT-PCR).3 These viral RNA tests use samples usually obtainedfrom the respiratory tract by nasopharyngeal swab, to detectcurrent infections. Serology blood tests to detect antibodiesindicating past infection are being developed; these will not beconsidered in depth in this for covid-19 enables infected individuals to be identifiedand isolated to reduce spread,4 allows contact tracing for exposedindividuals,5 and provides knowledge of regional and nationalrates of infection to inform public health interventions.

3 However,questions remain on how to apply test results to make optimaldecisions about individual strategyThis article was produced at speed to address an urgent need to addressuncertainties in testing for covid-19 . We searched Pubmed using the terms covid , SARS-CoV-2 , sensitivity , specificity , diagnosis , test , and PCR ,and KSR evidence using terms for covid and test. This was supplemented bydiscussion with colleagues undertaking formal systematic reviews into accurate are test results?No test gives a 100% accurate result ; tests need to be evaluatedto determine their sensitivity and specificity, ideally bycomparison with a gold standard. The lack of such a clear-cut gold-standard for covid-19 testing makes evaluation of testaccuracy systematic review of the accuracy of covid-19 tests reportedfalse negative rates of between 2% and 29% (equating tosensitivity of 71-98%), based on negative RT-PCR tests whichwere positive on repeat The use of repeat RT-PCRtesting as gold standard is likely to underestimate the true rateof false negatives, as not all patients in the included studiesreceived repeat testing and those with clinically diagnosedcovid-19 were not considered as actually having of viral RNA swabs in clinical practice variesdepending on the site and quality of sampling.

4 In one study,sensitivity of RT-PCR in 205 patients varied, at 93% forbroncho-alveolar lavage, 72% for sputum, 63% for nasal swabs,and only 32% for throat Accuracy is also likely to varydepending on stage of disease8 and degree of viral multiplicationor Higher sensitivities are reported depending onwhich gene targets are used, and whether multiple gene testsare used in 10 Reported accuracies are much higherfor in vitro studies, which measure performance of primers usingcoronavirus cell culture in carefully controlled lack of a clear-cut gold-standard is a challenge forevaluating covid-19 tests; pragmatically, clinical adjudicationmay be the best available gold standard, based on repeatswabs, history, and contact with patients known to havecovid-19, chest radiographs, and computed tomography this introduces some incorporation bias, where thetest being evaluated forms part of the reference standard, andthis would tend to inflate the measured sensitivity of these prevalence can also affect estimates of accuracy: testsdeveloped and evaluated in populations with high prevalence(eg, secondary care) may have lower sensitivity when appliedin a lower prevalence setting (eg, primary care).

5 11 Correspondence to J Watson personal use only: See rights and reprints : 2020;369:m1808 doi: (Published 12 May 2020)Page 1 of 7 PracticePRACTICE on 27 May 2022 by guest. Protected by : first published as on 12 May 2020. Downloaded from One community based study of 4653 close contacts of patientswith covid-19 tested RT-PCR throat swabs every 48 hoursduring a 14 day quarantine period. Of 129 eventually diagnosedwith covid-19 by RT-PCR, 92 ( ) had a positive test onthe first throat swab, equating to a sensitivity of 71% in thislower prevalence, community evidence and independent validation of covid-19 testsare As current studies show marked variation and arelikely to overestimate sensitivity, we will use the lower end ofcurrent estimates from systematic reviews,6 with the approximatenumbers of 70% for sensitivity and 95% for specificity forillustrative do clinicians need to know tounderstand a test result ?

6 Sensitivity and specificity can be confusing terms that may bemisunderstood14 (see supplementary file Definitions andformulae for calculating measures of test accuracy ). Sensitivityis the proportion of patients with disease who have a positivetest, or the true positive rate. Specificity is the proportion ofpatients without disease who have a negative test, or truenegative rate. These terms describe the operating characteristicsof a test and can be used to gauge the credibility of a test can be combined to calculate likelihood ratios, which aredimensionless numbers that indicate the strength of a positiveor negative test For calculating probabilities, a likelihoodratio can be used as a multiplier to convert pre-test odds topost-test odds.

7 Positive likelihood ratios greater than 1 areprogressively stronger, with 10 representing a very strongpositive test result . Negative likelihood ratios less than 1 arealso progressively stronger, with representing a very strongnegative test result . In the case of the nasopharyngeal swabRNA test for covid-19 , the positive likelihood ratio is about 14,which is A positive covid-19 test result should bevery compelling. The negative likelihood ratio is , which isa moderate result , but not nearly as compelling as a positiveresult because of the moderate sensitivity (about 70%) of thecovid-19 of a test result depends not only on thecharacteristics of the test itself but also on the pre-test probabilityof disease.

8 Clinicians use a heuristic (a learned mental shortcut) called anchoring and adjusting to settle on a pre-testprobability (called the anchor). They then adjust this probabilitybased on additional information. This heuristic is a useful shortcut but comes with the potential for bias. When people fail toestimate the pre-test probability and only respond to a piece ofnew information, they commit a fallacy called base-rate fallacy called anchoring is failing adequately to adjustone s probability estimate, given the strength of newinformation. Likelihood ratios can give a clinician an idea ofhow much to adjust their probability estimates. Cliniciansintuitively use anchoring and adjusting thoughtfully to estimatepre- and post-test probabilities unconsciously in everydayclinical practice.

9 However, faced with a new and unfamiliardisease such as covid-19 , mental short cuts can be uncertainand unreliable and public narrative about the definitive natureof testing can skew 1 shows how a clinician s thinking about a patient sprobability should shift, based on either a positive or negativetest result for covid-19 . First, the clinician should estimate apre-test probability, using knowledge of local rates of covid-19infection from national16 and regional17 data and patients symptoms and signs,18 likelihood of alternative diagnoses, andhistory of exposure to covid-19 . After choosing a pre-testprobability on the x axis, one should then trace up to either theupper curve for a positive test result or the lower curve for anegative test result , then trace over to the y axis to read theestimate for post-test probability.

10 The figure shows that the shiftin the probability is asymmetric, with a positive test resulthaving a greater impact than a negative test result , owing to themodest sensitivity and negative likelihood ratio of the infographic (fig 2) shows the outcomes when 100 peoplewith a pre-test probability of 80% are tested for covid-19 usingnatural frequencies, which are generally easier to calculators are available which allow clinicians to adjustpre-test probability, sensitivity, and specificity to estimatepost-test probability19 What else should clinicians considerwhen Interpreting test results?A single negative test result may not beinformative if the pre-test probability is highA 52 year old general practitioner in London develops a cough,intermittent fever, and malaise.