Comparison of clinician diagnosis of COVID-19 with real time polymerase chain reaction in an adult-representative population in Sweden.

BACKGROUND: Due to the high transmissibility of SARS-CoV-2, accurate diagnosis is essential for effective infection control, but the gold standard, real-time reverse transcriptase-polymerase chain reaction (RT-PCR), is costly, slow, and test capacity has at times been insufficient. We compared the accuracy of clinician diagnosis of COVID-19 against RT-PCR in a general adult population. METHODS: COVID-19 diagnosis data by 30th September 2021 for participants in an ongoing population-based cohort study of adults in Western Sweden were retrieved from registers, based on positive RT-PCR and clinician diagnosis using recommended ICD-10 codes. We calculated accuracy measures of clinician diagnosis using RT-PCR as reference for all subjects and stratified by age, gender, BMI, and comorbidity collected pre-COVID-19. RESULTS: Of 42,621 subjects, 3,936 (9.2%) and 5705 (13.4%) had had COVID-19 identified by RT-PCR and clinician diagnosis, respectively. Sensitivity and specificity of clinician diagnosis against RT-PCR were 78% (95%CI 77-80%) and 93% (95%CI 93-93%), respectively. Positive predictive value (PPV) was 54% (95%CI 53-55%), while negative predictive value (NPV) was 98% (95%CI 98-98%) and Youden's index 71% (95%CI 70-72%). These estimates were similar between men and women, across age groups, BMI categories, and between patients with and without asthma. However, while specificity, NPV, and Youden's index were similar between patients with and without chronic obstructive pulmonary disease (COPD), sensitivity was slightly higher in patients with (84% [95%CI 74-90%]) than those without (78% [95%CI 77-79%]) COPD. CONCLUSIONS: The accuracy of clinician diagnosis for COVID-19 is adequate, regardless of gender, age, BMI, and asthma, and thus can be used for screening purposes to supplement RT-PCR.

Evaluation of two different domestic colloidal gold assay kit fornew coronavirus antibody in low endemic areas

This study aimed to evaluate the application and diagnostic efficacy of two different colloidal gold kits for the detection of 2019-nCoV immunoglobulin M antibody (anti-IgM) and immunoglobulin G antibody (anti-IgG) in Beijing, a low endemic area, and to guide the rational clinical application. The sera of 29 patients with confirmed novel coronavirus pneumonia (COVID-19) and 19 411 patients from the non-infected screening population were selected to evaluate the sensitivity, specificity and false-positive rate of the 2019-nCoV antibody test kits from Zhuhai Lizhu and Tangshan Innotek using colloidal gold immunochromatography. The sensitivity of Inotec 2019-nCoV was slightly higher than that of Lizhu 2019-nCoV, with a sensitivity of 58.62% and 55.17%, respectively;the specimen collection time of the all-negative group was significantly less than that of the antibody-positive group (P < 0.05);the false-positive rate of the two reagents in the low-prevalence area was 0.16%, and the false-positive rate of 2019-nCoV IgG was higher in Inotec than in Lizhu. The false positive rate for 2019-nCoV IgM was significantly higher than that for IgG for the same brand (Inotec ?2=14.756 09, P=0.000 0;Lizhu ?2=27.492 62, P=0.000). Conclusion The 2019-nCoV antibody test is rapid, simple and easy to perform, with high specificity, and can be used as a rapid screening indicator for new crowns;the specificity, correctness and negative predictive value of the two kits are good, and the application of the other kit for retesting when a positive result occurs can reduce the false positive rate of informing the clinic;the application and analysis of positive reports of new crown antibodies should be combined with the endemic area and clinical comprehensive judgment.

Making Sense of Sensitivity: Using Candy and Anthropometric Data to Visually and Manipulatively Illustrate Sensitivity, Positive Predictive Value, and Related Terms.

The classic concepts of sensitivity and specificity are commonly taught by definition only, often with discipline-specific jargon and without any tangible relation to their use in the real world. Yet, the COVID pandemic and the spotlight on diagnostic screening tests have brought a need for science and health care students, health professionals, and the general public to have improved understanding of sensitivity and specificity and how they connect to further interpretive values. These understandings are critical for correct communications and explanations to those outside the sciences. Using simple candies or marbles as visuals, in conjunction with real-world scenarios, this activity was designed to help frame these concepts for students. Additionally, this activity provides practice with basic calculations and interpretations to reinforce how data can be used in determining testing values, surrogate testing, data cutoffs, and accuracy predictions. The activity is flexible and can easily be done in 1 to 2 h in a classroom setting, as a laboratory exercise, or as an outreach or online activity.

Clinical utility of negative methicillin-resistant Staphylococcus aureus (MRSA) nasal surveillance swabs in skin and skin structure infections.

BACKGROUND: Negative methicillin-resistant Staphylococcus aureus (MRSA) nasal swabs have a high negative predictive value of approximately 99% in respiratory infections. There is, however, a lack of data evaluating its use beyond respiratory infections. METHODS: We conducted a retrospective analysis to determine the clinical utility of MRSA swabs for identifying MRSA-associated skin and skin structure infections (SSSIs) and the potential effects on antimicrobial stewardship efforts. Baseline characteristics, culture data, and antibiotic data were collected to determine the difference in duration of vancomycin therapy. Positive predictive value, negative predictive value, sensitivity, and specificity were secondary outcomes. RESULTS: A total of 473 patients were included, of which 156 patients had a positive MRSA nasal swab and 317 patients had a negative swab. The median duration of vancomycin was 4 days in the positive group and 3 days in the negative group (P = .01). The positive predictive value and negative predictive value were 22.4% and 97.5%. The sensitivity and specificity were 81.4% and 71.9%. CONCLUSION: Patients with a negative MRSA nasal swab received approximately 1 day less of vancomycin, which represented a decrease in drug administered. The negative predictive value for SSSIs is promising, showing potential for the role of MRSA nasal swabs in de-escalating therapy.

Ventilator-Associated Pneumonia Due to MRSA vs. MSSA: What Should Guide Empiric Therapy?

The guidelines on ventilator-associated pneumonia (VAP) recommend an empiric therapy against methicillin-resistant Staphylococcus aureus (MRSA) according to its prevalence rate. Considering the MRSA and MSSA VAP prevalence over the last 9 years in our tertiary care hospital, we assessed the clinical value of the MRSA nasal-swab screening in either predicting or ruling out MRSA VAP. We extracted the data of 1461 patients with positive bronchoalveolar lavage (BAL). Regarding the MRSA nasal-swab screening, 170 patients were positive for MRSA or MSSA. Overall, MRSA had a high prevalence in our ICU. Despite the COVID-19 pandemic, there was a significant downward trend in MRSA prevalence, while MSSA remained steady over time. Having VAP due to MRSA did not have any impact on LOS and mortality. Finally, the MRSA nasal-swab testing demonstrated a very high negative predictive value for MRSA VAP. Our results suggested the potential value of a patient-centered approach to improve antibiotic stewardship.

Applicability of three nutritional screening tools in patients with liver cirrhosis under the Global Leadership Initiative on Malnutrition criteria. (Theme Issue: Diagnosis and treatment of liver failure in children.) [Chinese]

Objective: To investigate whether Royal Free Hospital Nutritional Prioritizing Tool (RFH-NPT) is more suitable than Nutritional Risk Screening 2002 (NRS-2002) in nutritional risk screening for patients with liver cirrhosis, as well as the applicability of subjective global assessment (SGA) in the nutritional assessment of patients with liver cirrhosis.

Screening testing in health care: Getting it right.

BACKGROUND: There is a movement to engage oral health care professionals in administering tests to identify people at risk of developing contagious diseases and other medical conditions. The purpose of this overview was to provide clinicians with fundamental concepts to understand how to evaluate a screening test's capability to give a correct result and its implications for practice (health outcomes). TYPES OF STUDIES REVIEWED: The authors reviewed epidemiologic and statistical articles addressing the purpose of performing screening tests for medical conditions with a special emphasis on understanding and interpreting test results on the basis of specific test characteristics. RESULTS: Tests with different sensitivities and specificities will provide different probabilities of correctly classifying people with or without a disease of interest. By understanding how to interpret tests results and how to communicate the consequences (that is, impact on health outcomes) of positive and negative test results, oral health care professionals will be able to generate appropriate medical referrals and determine the need for further testing, as well as provide a public service. CONCLUSIONS AND PRACTICAL IMPLICATIONS: An understanding by oral health care professionals of how to interpret screening test results will benefit their patients substantially and, in the case of contagious diseases, the public at large.

Comparison of SARS-CoV-2 Detection by Rapid Antigen and by Three Commercial RT-qPCR Tests: A Study from Martin University Hospital in Slovakia.

The global pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is having a tremendous impact on the global economy, health care systems and the lives of almost all people in the world. The Central European country of Slovakia reached one of the highest daily mortality rates per 100,000 inhabitants in the first 3 months of 2021, despite implementing strong prophylactic measures, lockdowns and repeated nationwide antigen testing. The present study reports a comparison of the performance of the Standard Q COVID-19 antigen test (SD Biosensor) with three commercial RT-qPCR kits (vDetect COVID-19-MultiplexDX, gb SARS-CoV-2 Multiplex-GENERI BIOTECH Ltd. and Genvinset COVID-19 [E]-BDR Diagnostics) in the detection of infected individuals among employees of the Martin University Hospital in Slovakia. Health care providers, such as doctors and nurses, are classified as "critical infrastructure", and there is no doubt about the huge impact that incorrect results could have on patients. Out of 1231 samples, 14 were evaluated as positive for SARS-CoV-2 antigen presence, and all of them were confirmed by RT-qPCR kit 1 and kit 2. As another 26 samples had a signal in the E gene, these 40 samples were re-isolated and subsequently re-analysed using the three kits, which detected the virus in 22, 23 and 12 cases, respectively. The results point to a divergence not only between antigen and RT-qPCR tests, but also within the "gold standard" RT-qPCR testing. Performance analysis of the diagnostic antigen test showed the positive predictive value (PPV) to be 100% and negative predictive value (NPV) to be 98.10%, indicating that 1.90% of individuals with a negative result were, in fact, positive. If these data are extrapolated to the national level, where the mean daily number of antigen tests was 250,000 in April 2021, it points to over 4700 people per day being misinterpreted and posing a risk of virus shedding. While mean Ct values of the samples that were both antigen and RT-qPCR positive were about 20 (kit 1: 20.47 and 20.16 for Sarbeco E and RdRP, kit 2: 19.37 and 19.99 for Sarbeco E and RdRP and kit 3: 17.47 for ORF1b/RdRP), mean Ct values of the samples that were antigen-negative but RT-qPCR-positive were about 30 (kit 1: 30.67 and 30.00 for Sarbeco E and RdRP, kit 2: 29.86 and 31.01 for Sarbeco E and RdRP and kit 3: 27.47 for ORF1b/RdRP). It confirms the advantage of antigen test in detecting the most infectious individuals with a higher viral load. However, the reporting of Ct values is still a matter of ongoing debates and should not be conducted without normalisation to standardised controls of known concentration.

Eleven routine clinical features predict COVID-19 severity uncovered by machine learning of longitudinal measurements.

Severity prediction of COVID-19 remains one of the major clinical challenges for the ongoing pandemic. Here, we have recruited a 144 COVID-19 patient cohort, resulting in a data matrix containing 3,065 readings for 124 types of measurements over 52 days. A machine learning model was established to predict the disease progression based on the cohort consisting of training, validation, and internal test sets. A panel of eleven routine clinical factors constructed a classifier for COVID-19 severity prediction, achieving accuracy of over 98% in the discovery set. Validation of the model in an independent cohort containing 25 patients achieved accuracy of 80%. The overall sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 0.70, 0.99, 0.93, and 0.93, respectively. Our model captured predictive dynamics of lactate dehydrogenase (LDH) and creatine kinase (CK) while their levels were in the normal range. This model is accessible at https://www.guomics.com/covidAI/ for research purpose.

Clinical Performance of SARS-CoV-2 Molecular Tests.

Molecular testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the gold standard for diagnosis of coronavirus disease 2019 (COVID-19), but the clinical performance of these tests is still poorly understood, particularly with regard to disease course, patient-specific factors, and viral shedding. From 10 March to 1 May 2020, NewYork-Presbyterian laboratories performed 27,377 SARS-CoV-2 molecular assays from 22,338 patients. Repeat testing was performed for 3,432 patients, of which 2,413 had initial negative and 802 had initial positive results. Repeat-tested patients were more likely to have severe disease and low viral loads. The negative predictive value of the first-day result among repeat-tested patients was 81.3% The clinical sensitivity of SARS-CoV-2 molecular assays was estimated between 58% and 96%, depending on the unknown number of false-negative results in single-tested patients. Conversion to negative was unlikely to occur before 15 to 20 days after initial testing or 20 to 30 days after the onset of symptoms, with 50% conversion occurring at 28 days after initial testing. Conversion from first-day negative to positive results increased linearly with each day of testing, reaching 25% probability in 20 days. Sixty patients fluctuated between positive and negative results over several weeks, suggesting that caution is needed when single-test results are acted upon. In summary, our study provides estimates of the clinical performance of SARS-CoV-2 molecular assays and suggests time frames for appropriate repeat testing, namely, 15 to 20 days after a positive test and the same day or next 2 days after a negative test for patients with high suspicion for COVID-19.

Setting minimum clinical performance specifications for tests based on disease prevalence and minimum acceptable positive and negative predictive values: Practical considerations applied to COVID-19 testing.

OBJECTIVES: Several guidelines for the evaluation of laboratory tests for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection have recommended establishing an a priori definition of minimum clinical performance specifications before test selection and method evaluation. METHODS: Using positive (PPV) and negative predictive values (NPV), we constructed a spreadsheet tool for determining the minimum clinical specificity (conditional on NPV or PPV, sensitivity and prevalence) and minimum clinical sensitivity (conditional on NPV or PPV, specificity and prevalence) of tests. RESULTS: At a prevalence of 1%, there are no minimum sensitivity requirements to achieve a desired NPV of 60%-95% for a given clinical specificity above 20%. It is not possible to achieve 60-95% PPV even with 100% clinical sensitivity, except when the clinical specificity is near 100%. The opposite trend is seen in high prevalence settings (60%), where a relatively low minimum clinical sensitivity is required to achieve a desired PPV for a given clinical specificity, and a higher minimum clinical specificity is required to achieve a desired NPV for a given clinical sensitivity. DISCUSSION: The selection of laboratory tests and the testing strategy for SARS-CoV-2 involves delicate trade-offs between NPV and PPV based on prevalence and clinical sensitivity and clinical specificity. Practitioners and health authorities should carefully consider the clinical scenarios under which the test result will be used and select the most appropriate testing strategy that fulfils the a priori defined clinical performance specification.

Unexpected Ground-Glass Opacities on Abdominopelvic CT of a Patient With a Negative SARS-CoV-2 Antigen Test Result and No Respiratory Symptoms Upon Admission.

One of the biggest challenges during the coronavirus disease 2019 (COVID-19) pandemic continues to be the detection of asymptomatic and presymptomatic persons infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Persons infected with SARS-CoV-2 who do not have symptoms of COVID-19 may transmit the virus to others and may have subclinical lung abnormalities. Some hospitals use SARS-CoV-2 antigen tests for pre-admission screening testing because they are relatively inexpensive, have a rapid turnaround time, and can be performed at the point of care; however, antigen tests are generally less sensitive than nucleic acid amplification tests with reverse transcription polymerase chain reaction (RT-PCR) assay. Moreover, as the local COVID-19 prevalence increases, the negative predictive value of antigen tests may decrease, meaning that the probability of having false-negative results may increase. We present a case of a patient who, prior to admission for a surgical procedure, had a negative antigen test result for SARS-CoV-2, had no respiratory symptoms, and had no suspected or known exposure to SARS-CoV-2; however, she tested positive for SARS-CoV-2 RNA after admission. The only factor that led the healthcare team to suspect SARS-CoV-2 infection was an unexpected finding of bilateral ground-glass opacities on an abdominopelvic computed tomography (CT), which was performed to assess the extent of a perianal abscess the patient presented. This case highlights the importance of using highly sensitive SARS-CoV-2 tests for pre-admission screening testing in the hospital setting.

Feasibility of using point-of-care lung ultrasound for early triage of COVID-19 patients in the emergency room.

PURPOSE: Diagnostic value of point-of-care lung ultrasound (POCUS) in detection of coronavirus disease (COVID-19) in an emergency setting is currently unclear. In this study, we aimed to compare diagnostic performance, in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy, of POCUS lung, chest CT, and RT-PCR for clinically suspected COVID-19 infections in patients submitting to the emergency room (ER). MATERIAL AND METHODS: This retrospective study enrolled 93 patients with a suspected COVID-19 infection, admitted to the ER between March 28th and April 20th, 2020. Test subjects showed one or more symptoms of an acute respiratory infection, for which consequent COVID-19 testing was achieved using POCUS lung, chest CT, and RT-PCR. CT images were analyzed by 2 radiologists blinded to RT-PCR results. POCUS lung was performed by three emergency medical doctors, and reports were analyzed by the researcher, blinded to clinical information, US imaging, CT, and RT-PCR test results. RESULTS: Compared with RT-PCR, POCUS lung demonstrated outstanding sensitivity and NPV (93.3% and 94.1% respectively) while showing poor values for specificity, PPV, and accuracy (21.3%, 19.2%, and 33.3% respectively). In contrast, similar inquiries using chest CT as index test, excellent sensitivity, specificity, NPV, and accuracy (80.0%, 86.7%, 95.6%, and 85.6%, respectively) were reported, beside a moderate value for PPV (54.5%). CONCLUSION: POCUS may provide early ER triage with a useful, rapid, low-threshold, and safe screening tool in evaluating possible COVID-19 infections. Due to limited specificity, suggestive POCUS lung findings should be confirmed with RT-PCR or chest CT.

When to rule out COVID-19: How many negative RT-PCR tests are needed?

Amidst the COVID-19 pandemic, clinicians have been plagued with dilemmas related to the uncertainty about diagnostic testing for the virus. It has become commonplace for a patient under investigation (PUI) to repeatedly test negative but have imaging findings that are consistent with COVID-19. This raises the question of when the treating team should entertain alternative diagnoses. We present such a case to help provide a framework for how to weigh repeatedly negative test results in clinical decision making when there is ongoing concern for COVID-19.

Laboratory Assay Evaluation Demystified: A Review of Key Factors Influencing Interpretation of Test Results Using Different Assays for SARS-CoV-2 Infection Diagnosis.

Laboratory tests are an integral part of the diagnosis and management of patients; however, these tests are far from perfect. Their imperfections can be due to patient health condition, specimen collection, and/or technological difficulty with performing the assay and/or interpretation. To be useful clinically, testing requires calculation of positive predictive values (PPVs) and negative predictive values (NPVs). During the current global pandemic of COVID-19 (coronavirus disease 2019), multiple assays with unknown clinical sensitivity and specificity have been rapidly developed to aid in the diagnosis of the disease. Due to a lack of surveillance testing, the prevalence of COVID-19 remains unknown. Hence, using this situation as an clinical example, the goal of this article is to clarify the key factors that influence the PPV and NPV yielded by diagnostic testing, By doing so, we hope to offer health-care providers information that will help them better understand the potential implications of utilizing these test results in clinical patient management.