Performance Of Diagnostic Tests Research Articles

Receiver operating characteristic curve analysis in diagnostic accuracy studies: A guide to interpreting the area under the curve value.

This review article provides a concise guide to interpreting receiver operating characteristic (ROC) curves and area under the curve (AUC) values in diagnostic accuracy studies. ROC analysis is a powerful tool for assessing the diagnostic performance of index tests, which are tests that are used to diagnose a disease or condition. The AUC value is a summary metric of the ROC curve that reflects the test's ability to distinguish between diseased and nondiseased individuals. AUC values range from 0.5 to 1.0, with a value of 0.5 indicating that the test is no better than chance at distinguishing between diseased and nondiseased individuals. A value of 1.0 indicates perfect discrimination. AUC values above 0.80 are generally consideredclinically useful, while values below 0.80 are considered of limited clinical utility. When interpreting AUC values, it is important to consider the 95% confidence interval. The confidence interval reflects the uncertainty around the AUC value. A narrow confidence interval indicates that the AUC value is likely accurate, while a wide confidence interval indicates that the AUC value is less reliable. ROC analysis can also be used to identify the optimal cutoff value for an index test. The optimal cutoff value is the value that maximizes the test's sensitivity and specificity. The Youden index can be used to identify the optimal cutoff value. This review article provides a concise guide to interpreting ROC curves and AUC values in diagnostic accuracy studies. By understanding these metrics, clinicians can make informed decisions about the use of index tests in clinical practice.

Diagnostic performances of celiac disease serological tests among Saudi patients.

: The prevalence of celiac disease (CD) is relatively high in Saudi Arabia, and little is known about the accuracy of serological markers in the local population. This study aimed to assess the diagnostic performance of various serological markers for detecting CD in Saudi children and adults. We conducted a retrospective study of 148 CD patients and 512 controls to assess the diagnostic performances of IgA anti-tissue transglutaminase antibodies (TTG), IgG anti-TTG, IgA anti-deamidated gliadin peptide antibodies (anti-DGP), IgG anti-DGP, and endomysium antibodies (EMA). : Immunoglobulin A (IgA) anti-TTG was the most sensitive test [98.9% (95% confidence interval (CI) 94.1-99.8%)], while EMA was the most specific [100%, 95%CI 98.6-100%]. By applying the criteria of IgA anti-TTG titers ≥10 × upper limit of normal (ULN) and positive EMA, 57.3% of patients could have avoided intestinal biopsy. IgG anti-DGP test had a sensitivity of 85.9% (95% CI = 77.3-91.5%) and a specificity of 93.5% (95% CI = (90.0-95.9%). Titers of IgA anti-TTG, IgA anti-DGP, and IgG anti-DGP were higher in CD patients with the Marsh 3c class than in those with the Marsh 3b and Marsh 3a classes. IgG anti-TTG and IgA anti-DGP had no additional diagnostic value. : IgA anti-TTG and EMA are excellent CD markers in children and adults. The use of IgA anti-TTG titers ≥10 × ULN and positive EMA as criteria for CD diagnosis in children and adults might be a good alternative to intestinal biopsy.

CHILDSTAR: CHIldren Living With Diabetes See and Thrive with AI Review.

Artificial intelligence (AI) appears capable of detecting diabetic retinopathy (DR) with a high degree of accuracy in adults; however, there are few studies in children and young adults. Children and young adults (3-26 years) with type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM) were screened at the Dhaka BIRDEM-2 hospital, Bangladesh. All gradable fundus images were uploaded to Cybersight AI for interpretation. Two main outcomes were considered at a patient level: 1) Any DR, defined as mild non-proliferative diabetic retinopathy (NPDR or more severe; and 2) Referable DR, defined as moderate NPDR or more severe. Diagnostic test performance comparing Orbis International's Cybersight AI with the reference standard, a fully qualified optometrist certified in DR grading, was assessed using the Matthews correlation coefficient (MCC), area under the receiver operating characteristic curve (AUC-ROC), area under the precision-recall curve (AUC-PR), sensitivity, specificity, positive and negative predictive values. Among 1274 participants (53.1% female, mean age 16.7 years), 19.4% (n = 247) had any DR according to AI. For referable DR, 2.35% (n = 30) were detected by AI. The sensitivity and specificity of AI for any DR were 75.5% (CI 69.7-81.3%) and 91.8% (CI 90.2-93.5%) respectively, and for referable DR, these values were 84.2% (CI 67.8-100%) and 98.9% (CI 98.3%-99.5%). The MCC, AUC-ROC and the AUC-PR for referable DR were 63.4, 91.2 and 76.2% respectively. AI was most successful in accurately classifying younger children with shorter duration of diabetes. Cybersight AI accurately detected any DR and referable DR among children and young adults, despite its algorithms having been trained on adults. The observed high specificity is particularly important to avoid over-referral in low-resource settings. AI may be an effective tool to reduce demands on scarce physician resources for the care of children with diabetes in low-resource settings.

SD-Bioline malaria rapid diagnostic test performance and time to become negative after treatment of malaria infection in Southwest Nigerian Children.

Given the challenges of microscopy, we compared its performance with SD-Bioline malaria rapid diagnostic test (MRDT) and polymerase chain reaction (PCR) and evaluated the time it took for positive results to become negative after treatment of children with acute uncomplicated malaria. We present the report of 485 participants with complete MRDT, microscopy, and PCR data out of 511 febrile children aged 3-59 months who participated in a cohort study over a 12-month period in rural and urban areas of Ibadan, Nigeria. MRDT-positive children received antimalaria and tested at every visit over 28 days. Speciation was also carried out by PCR. With microscopy as the gold standard, SD-Bioline™ had 95.2% sensitivity, 66.4% specificity, 67.5% positive predictive value (PPV), and 94.9 negative predictive value (NPV), while with PCR the findings were 84.3% sensitivity, 66.5% specificity, 72.7% PPV, and 80.1% NPV. PCR speciation of malaria parasites revealed 91.6% Plasmodium falciparum, 18.9% Plasmodium malariae, and 4.4% Plasmodium ovale. Among the 47 children with P. malariae infections, 66.0% were coinfected with P. falciparum, while 54.6% cases of P. ovale occurred as coinfections with P. falciparum. The median time to a negative MRDT was 23.2 days, while the median time to a negative malaria microscopy was 3.8 days. The two survival curves were significantly different. The SD-BiolineTM MRDT performed well, with remarkable persistence of rapid test-positive for an average of 23 days post treatment. The prevalence of P. malaria is somewhat greater than expected.

313. Performance of Rapid Diagnostic Testing at Days 4-6 from Diagnosis: Implications for Discharge from Isolation on a University Campus

Abstract Background Omicron rapidly replaced delta as the predominant strain causing COVID-19 related illness in the United States (US) in December 2021, the same month the US CDC reduced the recommended isolation period from 10 to 5 days for asymptomatic individuals or those with resolving symptoms. New evidence suggests some asymptomatic individuals with omicron remain culture positive beyond 5 days from diagnosis. We sought to evaluate the performance of a SARS-CoV-2 antigen rapid diagnostic test (RDT) in predicting persistent potential for transmission at the end of a five-day isolation period among young, fully vaccinated individuals in a university community setting. Methods A subgroup of participants enrolled in a longitudinal COVID-19 cohort were asked to self-perform RDTs on days 4 to 6 from diagnostic test date in addition to a separate self-collected anterior nasal swab used for culture and RT-PCR, and a daily symptom screen (15 COVID-19 symptom questions on a 4-point scale). We calculated the daily and overall sensitivity and specificity of the RDTs in comparison to SARS-CoV-2 culture result. We also compared the N1 cycle threshold (CT) values and symptom score on each day of the study by RDT results. Results Of 23 participants, the mean age was 20 years, all had completed their primary COVID-19 vaccine series, and 13 (65.0%) had received a booster vaccine (Table 1). Compared to culture, sensitivity and specificity of the RDTs were 100% and 62% respectively (Table 2). Compared to participants with negative RDTs, median CT values were lower in those with positive RDTs on each day of the study (Figure 1). Participants who had positive RDTs on all three days had higher symptom scores (Figure 2) than those without. Conclusion RDTs have a high sensitivity in detecting culture positive SARS-CoV-2 on Days 4 to 6 from initial diagnostic test. However, the high false positive rate of 38% means that over a third of culture negative individuals will stay in isolation longer than necessary if RDTs are used in test to release from isolation protocols. Viral loads (CT values) and symptom scores were higher for participants with persistently positive RDT result. An approach that uses a combination of RDTs, CT values and symptom score may prove useful in guiding isolation duration. Disclosures Davidson H. Hamer, MD, Trinity Biotech: Advisor/Consultant Catherine M. Klapperich, Ph.D., BioSens8, LLC: Ownership Interest.

Radiomics-based machine learning models for prediction of medulloblastoma subgroups: a systematic review and meta-analysis of the diagnostic test performance.

Medulloblastomas are a major cause of cancer-related mortality in the pediatric population. Four molecular groups have been identified, and these molecular groups drive risk stratification, prognostic modeling, and the development of novel treatment modalities. It has been demonstrated that radiomics-based machine learning (ML) models are effective at predicting the diagnosis, molecular class, and grades of CNS tumors. To assess radiomics-based ML models' diagnostic performance in predicting medulloblastoma subgroups and the methodological quality of the studies. A comprehensive literature search was performed on PubMed; the last search was conducted on 1 May 2022. Studies that predicted all four medulloblastoma subgroups in patients with histopathologically confirmed medulloblastoma and reporting area under the curve (AUC) values were included in the study. The quality assessments were conducted according to the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) and Checklist for Artificial Intelligence in Medical Imaging (CLAIM). A meta-analysis of radiomics-based ML studies' diagnostic performance for the preoperative evaluation of medulloblastoma subgrouping was performed. Five studies were included in this meta-analysis. Regarding patient selection, two studies indicated an unclear risk of bias according to the QUADAS-2. The five studies had an average CLAIM score and compliance score of 23.2 and 0.57, respectively. The meta-analysis showed pooled AUCs of 0.88, 0.82, 0.83, and 0.88 for WNT, SHH, group 3, and group 4 for classification, respectively. Radiomics-based ML studies have good classification performance in predicting medulloblastoma subgroups, with AUCs >0.80 in every subgroup. To be applied to clinical practice, they need methodological quality improvement and stability.

Diagnostic testing for and detection of physical abuse in infants with brief resolved unexplained events

BackgroundA Brief Resolved Unexplained Event (BRUE) can be a sign of occult physical abuse. ObjectivesTo identify rates of diagnostic testing able to detect physical abuse (head imaging, skeletal survey, and liver transaminases) at BRUE presentation. The secondary objective was to estimate the rate of physical abuse diagnosed at initial BRUE presentation through 1 year of age. Participants and settingInfants who presented with a BRUE at one of 15 academic or community hospitals were followed from initial BRUE presentation until 1 year of age for BRUE recurrence or revisits. MethodsThis study was part of the BRUE Research and Quality Improvement Network, a multicenter retrospective cohort examining infants with BRUE. Generalized estimating equations assessed associations with performance of diagnostic testing (adjusted odds ratio (aOR)). ResultsOf the 2036 infants presenting with a BRUE, 6.2 % underwent head imaging, 7.0 % skeletal survey, and 12.1 % liver transaminases. Infants were more likely to undergo skeletal survey if there were physical examination findings concerning for trauma (aOR 8.23, 95 % CI [1.92, 35.24], p < 0.005) or concerning social history (aOR 1.89, 95 % CI [1.13, 3.16], p = 0.015). There were 7 (0.3 %) infants diagnosed with physical abuse: one at BRUE presentation, one <3 days after BRUE presentation, and five >30 days after BRUE presentation. ConclusionThere were low rates of diagnostic testing and physical abuse identified in infants presenting with BRUE. Further study including standardized testing protocols is warranted to identify physical abuse in infants presenting with a BRUE.

Partial Verification Bias Correction Using Inverse Probability Bootstrap Sampling for Binary Diagnostic Tests.

In medical care, it is important to evaluate any new diagnostic test in the form of diagnostic accuracy studies. These new tests are compared to gold standard tests, where the performance of binary diagnostic tests is usually measured by sensitivity (Sn) and specificity (Sp). However, these accuracy measures are often biased owing to selective verification of the patients, known as partial verification bias (PVB). Inverse probability bootstrap (IPB) sampling is a general method to correct sampling bias in model-based analysis and produces debiased data for analysis. However, its utility in PVB correction has not been investigated before. The objective of this study was to investigate IPB in the context of PVB correction under the missing-at-random assumption for binary diagnostic tests. IPB was adapted for PVB correction, and tested and compared with existing methods using simulated and clinical data sets. The results indicated that IPB is accurate for Sn and Sp estimation as it showed low bias. However, IPB was less precise than existing methods as indicated by the higher standard error (SE). Despite this issue, it is recommended to use IPB when subsequent analysis with full data analytic methods is expected. Further studies must be conducted to reduce the SE.

Effect of a recent parenteral dexamethasone and ketoprofen administration on the immunological diagnosis of tuberculosis in goats.

Caprine tuberculosis (TB) is a zoonosis caused by members of the Mycobacterium tuberculosis complex (MTBC). Caprine TB eradication programmes are based mainly on intradermal tuberculin tests and slaughterhouse surveillance. Different factors may affect the performance of the TB diagnostic tests used in caprine herds and, therefore, their ability to detect infected animals. The present study evaluates the effect of the fraudulent administration of two anti-inflammatory substances, dexamethasone and ketoprofen, on the performance of the TB diagnostic techniques used in goats, as well as the suitability of high performance liquid chromatography (HPLC) for their detection in hair samples. The animals (n = 90) were distributed in three groups: (1) a group treated with dexamethasone (n = 30); a second group treated with ketoprofen (n = 30); and a third non-treated control group (n = 30). Both dexamethasone and ketoprofen groups were subjected to intramuscular inoculation with the substances 48 h after the administration of bovine and avian purified protein derivatives (PPDs), that is, 24 h before the tests were interpreted. All the animals were subjected to the single and comparative intradermal tuberculin (SIT and CIT, respectively) tests, interferon-gamma release assay (IGRA) and P22 ELISA. The number of SIT test reactors was significantly lower in the dexamethasone (p = 0.001) and ketoprofen (p < 0.001) groups 72 h after the bovine PPD inoculation compared with the control group. A significantly higher number of positive reactors to IGRA was detected within the dexamethasone group (p = 0.016) 72 h after PPD administration compared to the control group. Dexamethasone and ketoprofen detection in either hair or serum samples was challenging when using HPLC since these substances were not detected in animals whose skin fold thickness (SFT) was reduced, what could be an issue if they are used for fraudulent purposes. In conclusion, the parenteral administration of dexamethasone or ketoprofen 48 h after the PPDs administration can significantly reduce the increase in SFT (mm) and subsequently the number of positive reactors to SIT test.

Omicron Wave SARS-CoV-2 Diagnosis: Evaluation of Saliva, Anterior Nasal, and Nasopharyngeal Swab Samples.

The Omicron variant differs from earlier strains of SARS-CoV-2 in the way it enters host cells and grows in vitro. We therefore reevaluated its diagnosis using saliva, nasopharyngeal swab (NPs), and anterior nasal swab (ANs) specimens from 202 individuals (64.9% symptomatic) tested at the Toulouse University Hospital SARS-CoV-2 drive-through testing center. All tests were done with the Thermo Fisher TaqPath COVID-19 reverse transcription-PCR (RT-PCR) kit. Overall, 92 subjects (45.5%) had one or more positive specimens. Global sensitivities of saliva, NPs, and ANs were 94.6%, 90.2%, and 82.6%, respectively. Saliva provided significantly greater sensitivity among symptomatic patients tested within 5 days of symptom onset (100%) than did ANs (83.1%) or NPs (89.8%). We obtained follow-up samples for 7/20 individuals with discordant results. Among them, 5 symptomatic patients were diagnosed positive on saliva sample only, soon after symptom onset; NPs and ANs became positive only later. Thus, saliva samples are effective tools for the detection of the Omicron variant. In addition to its many advantages, such as improved patient acceptance and reduced cost, saliva sampling could help limit viral spread through earlier viral detection. IMPORTANCE Diagnostic testing for SARS-CoV-2 is an essential component of the global strategy for the prevention and control of COVID-19. Since the beginning of the pandemic, numerous studies have evaluated the diagnostic sensitivity of different respiratory and oral specimens for SARS-CoV-2 detection. The pandemic has been since dominated by the emergence of new variants, the latest being the Omicron variant characterized by numerous mutations and changes in host tropism in vitro that might affect the diagnostic performance of tests depending on the sampling location. In this prospective study, we evaluated the clinical performance of NPs, ANs, and saliva for SARS-CoV-2 diagnosis during the Omicron wave. Our results highlight the effectiveness of saliva-based RT-PCR for the early detection of the Omicron variant. These findings may help to refine guidelines and support the use of a highly sensitive diagnostic method that allows earlier diagnosis, when transmission is the most critical.

Evaluation of qualitative and semi-quantitative cut offs for rapid diagnostic lateral flow test in relation to serology for the detection of SARS-CoV-2 antibodies: findings of a prospective study

Background:There is limited information to compare the qualitative and semi-quantitative performance of rapid diagnostic tests (RDT) and serology for the assessment of antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Therefore, the objective of the study was (a) to compare the efficacy of SARS-CoV-2 antibody detection between RDT and laboratory serology, trying to identify appropriate semi-quantitative cut-offs for RDT in relation with quantitative serology values and to (b) evaluate diagnostic accuracy of RDT compared to the NAAT gold standard in an unselected adult population.Methods:SARS-CoV-2 antibodies were simultaneously measured with lateral flow immunochromatographic assays (LFA), the Cellex qSARS-CoV-2 IgG/IgM Rapid Test (by capillary blood), the iFlash-SARS-CoV-2 IgG/IgM chemiluminescent immunoassay (CLIA) (by venous blood) and the nucleic acid amplification test (NAAT) in samples from in- and out-patients with confirmed, suspected and negative diagnosis of coronavirus disease 2019 (COVID-19) attending Udine Hospital (Italy) (March-May 2020). Interpretation of RDT was qualitative (positive/negative) and semi-quantitative based on a chromatographic intensity scale (negative, weak positive, positive).Results:Overall, 720 paired antibody measures were performed on 858 patients. The qualitative and semiquantitative agreement analysis performed in the whole sample between LFA and CLIA provided a Kendall’s tau of 0.578 (p < 0.001) and of 0.623 (p < 0.001), respectively, for IgM and IgG. In patients with a diagnosis of COVID-19, accordance between LFA and CLIA was maintained as a function of time from the onset of COVID-19 disease and the severity of disease both for qualitative and semi-quantitative assessments. RDT compared to the NAAT gold standard in 858 patients showed 78.5% sensitivity (95% CI 75.1%-81.7%) and 94.1% specificity (95% CI 90.4%-96.8%), with variable accordance depending on the timing from symptom onset.Conclusion:The RDT used in our study can be a non-invasive and reliable alternative to serological tests and facilitate both qualitative and a semi-quantitative antibody detection in COVID-19.

Diagnostic Performance of Noninvasive Tests for Advanced Hepatic Fibrosis in Young Age Population

Most noninvasive tests (NITs) for hepatic fibrosis are designed for middle-aged patients with chronic liver disease. We compared the diagnostic performance of major NITs (aspartate aminotransferase-to-platelet ratio index [APRI], Fibrosis-4 index, and nonalcoholic fatty liver disease fibrosis score) for a community-based cohort. This cross-sectional study analyzed 8775 participants who underwent magnetic resonance elastography at community health check-up centers. Advanced hepatic fibrosis (≥F3)was defined by magnetic resonance elastography thresholds of 3.6 kPa. Thediagnostic performance of 3 NITs was evaluated according to the etiology of liver disease, sex,metabolic syndrome, obesity, and increased aminotransferase levels in 4 age groups. The APRI generally showed the best area under the receiver operating characteristic curve in patients aged 45 years or younger, and it was statistically significant in patients with chronic viral hepatitis and alcoholic fatty liver disease (P < .043). The best APRI cut-off value for detecting advanced hepatic fibrosis was 0.4, with a sensitivity and specificity of 75.8% and 73.5%, respectively, in the community-based cohort. The APRI showed balanced sensitivity and specificity across all age groups, whereas the other metrics showed low sensitivity in those aged <45 and low specificity in those >65 years. The APRI showed better sensitivity and negative predictive value than the Fibrosis-4 index and the nonalcoholic fatty liver disease fibrosis score in community-based populations with mixed etiology, and, thus, can be performed as the primary test in young adults (age, ≤45 y).

Performance of diagnostic tests based on continuous bivariate markers

In medical diagnostic research, it is customary to collect multiple continuous biomarker measures to improve the accuracy of diagnostic tests. A prevalent practice is to combine the measurements of these biomarkers into one single composite score. However, incorporating those biomarker measurements into a single score depends on the combination of methods and may lose vital information needed to make an effective and accurate decision. Furthermore, a diagnostic cut-off is required for such a combined score, and it is difficult to interpret in actual clinical practice. The paper extends the classical biomarkers’ accuracy and predictive values from univariate to bivariate markers. Also, we will develop a novel pseudo-measures system to maximize the vital information from multiple biomarkers. We specified these pseudo-and-or classifiers for the true positive rate, true negative rate, false-positive rate, and false-negative rate. We used them to redefine classical measures such as the Youden index, diagnostics odds ratio, likelihood ratios, and predictive values. We provide optimal cut-off point selection based on the modified Youden index with numerical illustrations and real data analysis for this paper's newly developed pseudo measures.

Diagnostic accuracy of SARS-CoV-2 antigen test in the pediatric population: A systematic review and meta-analysis.

BackgroundSevere acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused the global coronavirus disease 2019 (COVID-19) pandemic. Rapid identification and isolation of patients infected with SARS-CoV-2 are critical methods for blocking COVID-19 transmission. The advantages of antigen tests, such as their relatively low cost and short turnaround time, can contribute to the prompt identification of infectious individuals. However, the diagnostic accuracy of antigen tests for COVID-19 in children remains inconclusive. This meta-analysis aimed to evaluate the diagnostic performance of antigen tests for SARS-CoV-2 in the pediatric population.MethodsWe conducted a literature search for relevant studies in the PubMed, Embase, Google Scholar, and Biomed Central databases. Studies evaluating the diagnostic accuracy of antigen tests for SARS-CoV-2 in pediatric patients were included. In addition, we included studies that provided sufficient data to construct a 2 × 2 table on a per-patient basis. The final literature search was performed on October 10, 2021. Days after symptom onset, asymptomatic and symptomatic individuals may have been potential sources of heterogeneity. The overall sensitivity and specificity of the antigen tests were generated using a bivariate random-effects model.ResultsFive studies with 4,400 participants were included. The meta-analysis of antigen tests generated a pooled sensitivity of 65.9% (95% CI: 52.8%–77.0%) and pooled specificity of 99.9% (95% CI: 98.9%–100.0%). A subgroup analysis of studies reporting antigen test data for symptomatic patients showed a pooled sensitivity of 64.5% and a pooled specificity of 99.7%. The subgroup analysis of studies that included 881 asymptomatic participants generated a pooled sensitivity of 48.4% and a pooled specificity of 99.5%.ConclusionAntigen tests exhibit moderate sensitivity and high specificity for detecting SARS-CoV-2 in children. Antigen tests might have moderate sensitivity for detecting SARS-CoV-2 in symptomatic children, and serial testing might effectively prevent further SARS-CoV-2 transmission.

Comparison of diagnostic performances of different serological tests for SARS-CoV-2 antibody detection in cats and dogs.

SummarySerosurveillance among animals, including pets, plays an important role in the current coronavirus disease 2019 (COVID‐19) pandemic, because severe acute respiratory coronavirus 2 (SARS‐CoV‐2) infections in animal populations could result in the establishment of new virus reservoirs. Serological assays that offer the required sensitivity and specificity are essential. In this study we evaluated the diagnostic performance of three different commercially available immunoassays for the detection of SARS‐CoV‐2 antibodies in pets, namely two ELISA tests for the detection of antibodies against SARS‐CoV‐2 nucleocapsid [ID Screen SARS CoV‐2 double antigen multispecies (Double antigen) and ID Screen® SARS‐CoV‐2‐N IgG indirect ELISA (Indirect)] and one test for the detection of neutralizing antibodies against SARS‐CoV‐2 receptor‐binding‐domain [surrogate virus neutralization test (sVNT)]. The obtained results were compared with those of conventional virus neutralization test (VNT), which was regarded as reference method. A total of 191 serum samples were analyzed. Thirteen (6.8%) samples showed VNT positive results. The overall sensitivity was higher for sVNT (100%) compared to nucleocapsid‐based ELISA assays (23% for Double antigen and 60% for Indirect). The specificity was 100% for Indirect ELISA and sVNT, when a higher cut‐off (>30%) was used compared to the one previously defined by the manufacturer (>20%), whereas the other test showed lower value (99%). The sVNT test showed the highest accuracy and agreement with VNT, with a perfect agreement when the higher cut‐off was applied. The agreement between each nucleocapsid‐based ELISA test and VNT was 96% for Indirect and 94% for Double antigen. Our findings showed that some commercially available serological tests may lead to a high rate of false negative results, highlighting the importance of assays validation for the detection of SARS‐CoV‐2 antibodies in domestic animals.This article is protected by copyright. All rights reserved

Evaluation of 2 refractometers to estimate different passive immunity status in Simmental dairy calves

Inadequate transfer of passive immunity (ITPI) is major risk for mortality, morbidity and decreased growth performance in dairy and beef calves. Refractometry method is used in estimating ITPI in dairy and beef calves but studies evaluating refractometers for Simmental dairy calves are limited. The objectives of this study were determining the accuracy of digital serum total protein refractometer (STP-REF) and digital Brix refractometer (BRIX-REF) in the estimating of different passive immunity status (<10, <18, <25 and <32 g/L) in Simmental dairy calves. Serum samples were collected from apparently healthy Simmental dairy calves aged 1–8 days (n = 291). Serum total solid percentages were measured using BRIX-REF, serum total protein concentrations were measured using STP-REF and serum IgG concentrations were measured using radial immunodiffusion (RID) assay as a reference test. Correlation coefficients were calculated between RID test and refractometers results, and each other. The diagnostic test performance of the refractometers at IgG concentrations of < 10, < 18, < 25 and < 32 g/L was measured by performing a receiver operating characteristics (ROC) analysis. The optimal thresholds of the refractometers were determined based on Youden's J statistics and after accounting for different costs between false positive and false negative cases using misclassification cost term analysis. The overall test performance and the agreement of the refractometers were assessed using area under the ROC curve and Cohen's kappa analysis. Optimal thresholds were determined as < 7.9, < 8.3, < 8.7, < 9.4% for the BRIX-REF, and < 4.6, < 5.2, < 5.4, < 5.8 g/dL for the STP-REF in estimating IgG concentrations of < 10, < 18, < 25, < 32 g/L, respectively. Se and Sp of BRIX-REF were 88.8% and 89.1% for < 7.9% Brix, 81.6% and 94.2% for < 8.3% Brix, 77.9% and 97.4% for < 8.7% Brix and 81.7% and 91.2% for < 9.4% Brix, respectively. Se and Sp of STP-REF 92.5% and 88.2% for < 4.6 g/dL; 92.1% and 87.1% for < 5.2 g/dL; 81.7% and 93.6% for < 5.4 g/dL; 79.0% and 94.1% for < 5.8 g/dL, respectively. Both, digital Brix and STP refractometers performed well to estimate the status of passive immunity in dairy Simmental calves.

Evaluation of Extra-Cranial Carotid Arteries by Digital Subtraction Angiogram (DSA) in Stroke Patients in a Tertiary Care Hospital

Introduction: Carotid artery stenosis is one of the important causes of ischemic stroke. This may be diagnosed by Doppler Ultrasound and Digital Subtraction Angiogram (DSA) both of which have some advantages and disadvantages. Objective: The aim of this study was to assess extra-cranial carotid artery with the help of DSA among patients of ischemic stroke and transient ischemic attack (TIA). Materials and Methods: This observational cross sectional study was conducted in the Department of Neurology in Bangabandhu Sheikh Mujib Medical University (BSMMU) Dhaka from July 2013 to June 2015 for a period of two years. This study included a total of 50 patients. Diagnostic performance test of DSA was done at 50%, 50-69%, 70-99%, 100% cut off point of stenosis of right internal carotid artery (RICA) and Left internal carotid artery (LICA). Results: The mean age of cases was 61 ± 11.42 years. Out of 50 vessels, maximum cases were diagnosed as &lt;50% stenosis of carotid artery (26 cases of RICA, 23 cases of LICA. Out of 50 vessels, 50%-69%, 70 but _ less than near occlusion and total occlusion were found among 10, 10, 4 vessels in RICA and 10, 9, 8 vessels in LICA respectively. The present study showed that 50 vessels of RICA was measured by DSA and diagnosed 28 (56%), 10 (20%), 7 (14%) and 5 (10%) carotid vessels as _ 50%, 50-69%, _70% but less than total occluded and total occluded cases respectively. This study also showed that 50 vessels of LICA was measured by DSA and diagnosed 23 (56%), 12 (24%), 8 (16%), 7 (14%) carotid vessels as _ 50%, 50-69%, _ 70% but less than total occluded and total occluded cases respectively. Conclusion: DSA as the gold standard has amply been performed in most diagnostic circumstances of carotid artery stenosis. So, the present study was done to evaluate extra cranial carotid arterial system by DSA in stroke patients in Bangladesh. Medicine Today 2022 Vol.34(2): 121-124

Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases

The study aims to analyze inequalities in Covid-19 outcomes in Brazil in 2020/2021 according to the per capita Gross Domestic Product (pcGDP) of municipalities. All cases of Severe Acute Respiratory Syndrome (SARS) who were hospitalized or died, regardless of hospitalization, registered in Brazil in 2020 and 2021 were analyzed (n = 2,902,742), including those with a confirmed diagnosis of Covid-19 (n = 1,894,165). We calculated lethality due to Covid-19, the performance of diagnostic tests among patients with SARS, and the hospital care received by those with Covid-19 according to the pcGDP of the patients' municipalities of residence. Data were analyzed for each epidemiological week and the risk of each outcome was estimated using Poisson regression. Municipalities in the lowest pcGDP decile had (i) 30% (95%CI 28%–32%) higher lethality from Covid-19, (ii) three times higher proportion of patients with SARS without the collection of biological material for the diagnosis of Covid-19, (iii) 16% (95%CI 15%–16%) higher proportion of SARS patients testing in a period longer than two days from the onset of symptoms, (iv) 140% (95%CI 134%–145%) higher absence of CT scan use. There is deep socioeconomic inequality among Brazilian municipalities regarding the occurrence of Covid-19 negative outcomes.

The effect of an artificial intelligence algorithm on chest X-ray interpretation of radiology residents.

Chest X-rays are the most commonly performed diagnostic examinations. An artificial intelligence (AI) system that evaluates the images fast and accurately help reducing workflow and management of the patients. An automated assistant may reduce the time of interpretation in daily practice. We aim to investigate whether radiology residents consider the recommendations of an AI system for their final decisions, and to assess the diagnostic performances of the residents and the AI system. Posteroanterior (PA) chest X-rays with confirmed diagnosis were evaluated by 10 radiology residents. After interpretation, the residents checked the evaluations of the AI Algorithm and made their final decisions. Diagnostic performances of the residents without AI and after checking the AI results were compared. Residents' diagnostic performance for all radiological findings had a mean sensitivity of 37.9% (vs 39.8% with AI support), a mean specificity of 93.9% (vs 93.9% with AI support). The residents obtained a mean AUC of 0.660 vs 0.669 with AI support. The AI algorithm diagnostic accuracy, measured by the overall mean AUC, was 0.789. No significant difference was detected between decisions taken with and without the support of AI. Although, the AI algorithm diagnostic accuracy were higher than the residents, the radiology residents did not change their final decisions after reviewing AI recommendations. In order to benefit from these tools, the recommendations of the AI system must be more precise to the user. This research provides information about the willingness or resistance of radiologists to work with AI technologies via diagnostic performance tests. It also shows the diagnostic performance of an existing AI algorithm, determined by real-life data.

Factors Affecting the Performance of HRP2-Based Malaria Rapid Diagnostic Tests.

The recent COVID-19 pandemic has profoundly impacted global malaria elimination programs, resulting in a sharp increase in malaria morbidity and mortality. To reduce this impact, unmet needs in malaria diagnostics must be addressed while resuming malaria elimination activities. Rapid diagnostic tests (RDTs), the unsung hero in malaria diagnosis, work to eliminate the prevalence of Plasmodium falciparum malaria through their efficient, cost-effective, and user-friendly qualities in detecting the antigen HRP2 (histidine-rich protein 2), among other proteins. However, the testing mechanism and management of malaria with RDTs presents a variety of limitations. This paper discusses the numerous factors (including parasitic, host, and environmental) that limit the performance of RDTs. Additionally, the paper explores outside factors that can hinder RDT performance. By understanding these factors that affect the performance of HRP2-based RDTs in the field, researchers can work toward creating and implementing more effective and accurate HRP2-based diagnostic tools. Further research is required to understand the extent of these factors, as the rapidly changing interplay between parasite and host directly hinders the effectiveness of the tool.