Diagnostic accuracy of a fully automated multiplex celiac disease antibody panel for serum and plasma

Abstract Background An automated multiplex platform using capillary blood can promote greater throughput and more comprehensive studies in celiac disease (CD). Diagnostic accuracy should be improved using likelihood ratios for the post-test probability of ruling-in disease. Methods The Ig_plex™ Celiac Disease Panel on the sqidlite™ automated platform measured IgA and IgG antibodies to tTG and DGP in n = 224 CD serum or plasma samples. Diagnostic accuracy metrics were applied to the combined multiplex test results for several CD populations and compared to conventional single antibody ELISA tests. Results With multiple positive antibody results, the post-test probability for ruling-in untreated and treated CD increased to over 90%. The number of samples positive for more than one antibody also increased in untreated CD to ≥90%. Measurement of all four CD antibodies generate cut-off dependent accuracy profiles that can monitor response to treatment with the gluten-free diet (GFD). Higher positive tTG and DGP antibodies are seen more frequently in confirmed CD without (81%–94%) than with GFD treatment (44%–64%). In CD lacking biopsy confirmation, overall agreement of plasma to serum was ≥98% for all antibodies, and 100% for venous to capillary plasma. Conclusions The Ig_plex Celiac Disease Panel increases the likelihood of confirming CD based on the post-test probability of disease results for multi-reactive markers. Specific positivity profiles and cut-off intervals can be used to monitor GFD treatment and likely disease progression. Using serum, venous and capillary plasma yield comparable and accurate results.

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A “Clinician’s Probability Calculator” to convert pre-test to post-test probability of COVID-19 , based on method validation from each laboratory

10.20944/preprints202012.0094.v1 ◽

2020 ◽

Author(s):

Zoe Brooks ◽

Saswati Das ◽

Tom Pliura

Keyword(s):

Health Staff ◽

Test Results ◽

Likelihood Ratios ◽

Percent Agreement ◽

Public Health Staff ◽

Post Test ◽

Online Calculator ◽

Test Result ◽

Post Test Probability ◽

Test Probability

During coronavirus pandemic testing and identifying the virus has been a unique and constant challenge for the scientific community. In this paper, we discuss a practical solution to help guide clinicians and public health staff with the interpretation of the probability that a positive, or negative, COVID-19 test result indicates an infected person, based on their clinical estimate of pre-test probability of infection. The LinkedIn survey confirmed that the pre-test probability of COVID-19 increases with patient age, known contact, and severity of symptoms, as well as prevalence of disease in the local population. PPA (Positive Percent Agreement, PPA) and NPA (Negative Percent Agreement, specificity), differ between individual methods. Results vary between laboratories and the manufacturer for the same method. The confidence intervals of results vary with the number of samples tested, often adding a large range of possibilities to the reported test result. The online calculator met the objective.The authors postulated that the clinical pre-test probability of COVID-19 increases relative to local prevalence of disease plus patient age, known contact, and severity of symptoms. We conducted a small survey on LinkedIn to confirm that hypothesis. We examined results of PPA (Positive Percent Agreement, sensitivity) and NPA (Negative Percent Agreement, specificity) from 73 individual laboratory experiments for molecular tests for SARS-CoV-2as reported to the FIND database,(1) and for selected methods in FDA EUA submissions (2,3). We calculated likelihood ratios to convert pre-test to post-test probability of disease, then further calculated the number of true and false results expected in every ten positive or negative test results, plus an estimate that one in ‘x’ test results is true. We designed an online calculator to create graphics and text to fulfill the objective. A positive or negative test result from one laboratory conveys a higher probability for the presence or absence of COVID-19 than the same result from another laboratory, depending on clinical pre-test probability of disease plus proven method PPA and NPA in each laboratory. Likelihood ratios and confidence intervals provide valuable information but are seldom used in clinical settings. We recommend that testing laboratories verify PPA and NPA, and utilize a tool such as the “Clinician’s Probability Calculator” to verify acceptable test performance and create reports to help guide clinicians and public health staff with estimation of post-test probability of COVID-19 .

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A Bayesian decision support sequential model for severity of illness predictors and intensive care admissions in pneumonia

BMC Medical Informatics and Decision Making ◽

10.1186/s12911-019-1015-5 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 1

Author(s):

Amado Alejandro Baez ◽

Laila Cochon ◽

Jose Maria Nicolas

Keyword(s):

Predictive Value ◽

Severity Of Illness ◽

Positive Test ◽

Bayesian Decision ◽

Likelihood Ratios ◽

Negative Test ◽

Significant Difference ◽

Post Test ◽

Post Test Probability ◽

Test Probability

Abstract Background Community-acquired pneumonia (CAP) is one of the leading causes of morbidity and mortality in the USA. Our objective was to assess the predictive value on critical illness and disposition of a sequential Bayesian Model that integrates Lactate and procalcitonin (PCT) for pneumonia. Methods Sensitivity and specificity of lactate and PCT attained from pooled meta-analysis data. Likelihood ratios calculated and inserted in Bayesian/ Fagan nomogram to calculate posttest probabilities. Bayesian Diagnostic Gains (BDG) were analyzed comparing pre and post-test probability. To assess the value of integrating both PCT and Lactate in Severity of Illness Prediction we built a model that combined CURB65 with PCT as the Pre-Test markers and later integrated the Lactate Likelihood Ratio Values to generate a combined CURB 65 + Procalcitonin + Lactate Sequential value. Results The BDG model integrated a CUBR65 Scores combined with Procalcitonin (LR+ and LR-) for Pre-Test Probability Intermediate and High with Lactate Positive Likelihood Ratios. This generated for the PCT LR+ Post-test Probability (POSITIVE TEST) Posterior probability: 93% (95% CI [91,96%]) and Post Test Probability (NEGATIVE TEST) of: 17% (95% CI [15–20%]) for the Intermediate subgroup and 97% for the high risk sub-group POSITIVE TEST: Post-Test probability:97% (95% CI [95,98%]) NEGATIVE TEST: Post-test probability: 33% (95% CI [31,36%]) . ANOVA analysis for CURB 65 (alone) vs CURB 65 and PCT (LR+) vs CURB 65 and PCT (LR+) and Lactate showed a statistically significant difference (P value = 0.013). Conclusions The sequential combination of CURB 65 plus PCT with Lactate yielded statistically significant results, demonstrating a greater predictive value for severity of illness thus ICU level care.

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The diagnostic accuracy of wrist cineradiography in diagnosing scapholunate dissociation

Journal of Hand Surgery (European Volume) ◽

10.1177/1753193413489056 ◽

2013 ◽

Vol 39 (3) ◽

pp. 263-271 ◽

Cited By ~ 20

Author(s):

G. S. I. Sulkers ◽

N. W. L. Schep ◽

M. Maas ◽

C. M. A. M. van der Horst ◽

J. C. Goslings ◽

...

Keyword(s):

Diagnostic Accuracy ◽

Predictive Value ◽

Diagnostic Value ◽

Inclusion Criteria ◽

Scapholunate Ligament ◽

Scapholunate Dissociation ◽

Post Test ◽

Sensitivity Specificity ◽

Post Test Probability ◽

Test Probability

Ruptures of the scapholunate ligament (SLL) may cause carpal instability, also known as scapholunate dissociation (SLD). SLD may lead to osteoarthritis of the radiocarpal and midcarpal joints. The aim of this retrospective study was to determine the diagnostic value of wrist cineradiography in detecting SLD. All cineradiographic studies made during a 24 year period were retrieved. All patients who underwent the confirmation method (arthroscopy and/or arthrotomy) and cineradiography were included. In total, 84 patients met the inclusion criteria. Sensitivity, specificity, likelihood ratio, positive predictive value, negative predictive value, and diagnostic accuracy for detecting SLD were calculated for radiography and cineradiography. Cineradiography had a sensitivity of 90%, a specificity of 97%, and a diagnostic accuracy of 0.93 in detecting SLD. Radiography had a sensitivity of 81%, a specificity of 80%, and a diagnostic accuracy of 0.81. Cineradiography has a high diagnostic value for diagnosing SLDs. A positive cineradiography markedly increases the post-test probability of SLD.

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Diagnostic accuracy of three clinical dehydration scales: a systematic review

Archives of Disease in Childhood ◽

10.1136/archdischild-2017-313762 ◽

2017 ◽

Vol 103 (4) ◽

pp. 383-388 ◽

Cited By ~ 6

Author(s):

Anna Falszewska ◽

Hania Szajewska ◽

Piotr Dziechciarz

Keyword(s):

Diagnostic Accuracy ◽

Low Income ◽

Positive Likelihood Ratio ◽

High Income ◽

Low Income Countries ◽

Severe Dehydration ◽

Post Test ◽

Sensitivity Specificity ◽

Post Test Probability ◽

Test Probability

ObjectiveTo systematically assess the diagnostic accuracy of the Clinical Dehydration Scale (CDS), the WHO Scale and the Gorelick Scale in identifying dehydration in children with acute gastroenteritis (AGE).DesignThree databases, two registers of clinical trials and the reference lists from identified articles were searched for diagnostic accuracy studies in children with AGE. The index tests were the CDS, WHO Scale and Gorelick Scale, and reference standard was the percentage loss of body weight. The main analysed outcomes were the sensitivity, specificity, positive likelihood ratio (LR) and negative LR.ResultsTen studies were included. In high-income countries, the CDS provided a moderate-to-large increase in the post-test probability of predicting moderate to severe (≥6%) dehydration (positive LR 3.9–11.79), but it was of limited value for ruling it out (negative LR 0.55–0.71). In low-income countries, the CDS showed limited value both for ruling in and ruling out moderate-to-severe dehydration. In both settings, the CDS showed poor diagnostic accuracy for ruling in or out no dehydration (<3%) or some dehydration (3%–6%). The WHO Scale showed no or limited value in assessing dehydration in children with diarrhoea. With one exception, the included studies did not confirm the diagnostic accuracy of the Gorelick Scale.ConclusionLimited evidence suggests that the CDS can help in ruling in moderate-to-severe dehydration (≥6%) in high-income settings only. The WHO and Gorelick Scales are not helpful for assessing dehydration in children with AGE.

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Component-Resolved Diagnosis of Hazelnut Allergy in Children

Nutrients ◽

10.3390/nu13020640 ◽

2021 ◽

Vol 13 (2) ◽

pp. 640

Author(s):

Carlo Caffarelli ◽

Carla Mastrorilli ◽

Angelica Santoro ◽

Massimo Criscione ◽

Michela Procaccianti

Keyword(s):

Diagnostic Accuracy ◽

Area Under The Curve ◽

Food Challenge ◽

Final Diagnosis ◽

Childhood And Adolescence ◽

Test Results ◽

Post Test ◽

Food Challenges ◽

Post Test Probability ◽

Test Probability

Hazelnuts commonly elicit allergic reactions starting from childhood and adolescence, with a rare resolution over time. The definite diagnosis of a hazelnut allergy relies on an oral food challenge. The role of component resolved diagnostics in reducing the need for oral food challenges in the diagnosis of hazelnut allergies is still debated. Therefore, three electronic databases were systematically searched for studies on the diagnostic accuracy of specific-IgE (sIgE) on hazelnut proteins for identifying children with a hazelnut allergy. Studies regarding IgE testing on at least one hazelnut allergen component in children whose final diagnosis was determined by oral food challenges or a suggestive history of serious symptoms due to a hazelnut allergy were included. Study quality was assessed by the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Eight studies enrolling 757 children, were identified. Overall, sensitivity, specificity, area under the curve and diagnostic odd ratio of Cor a 1 sIgE were lower than those of Cor a 9 and Cor a 14 sIge. When the test results were positive, the post-test probability of a hazelnut allergy was 34% for Cor a 1 sIgE, 60% for Cor a9 sIgE and 73% for Cor a 14 sIgE. When the test results were negative, the post-test probability of a hazelnut allergy was 55% for Cor a 1 sIgE, 16% for Cor a9 sIgE and 14% for Cor a 14 sIgE. Measurement of IgE levels to Cor a 9 and Cor a 14 might have the potential to improve specificity in detecting clinically tolerant children among hazelnut-sensitized ones, reducing the need to perform oral food challenges.

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“Clinician’s Probability Calculator” to Convert Pre-Test to Post-Test Probability of COVID-19, Based on Method Validation from Each Laboratory

10.20944/preprints202012.0094.v3 ◽

2021 ◽

Author(s):

Zoe Brooks ◽

Saswati Das ◽

Tom Pliura

Keyword(s):

Test Performance ◽

False Negative ◽

Likelihood Ratios ◽

Unique Challenge ◽

Molecular Tests ◽

Percent Agreement ◽

Post Test ◽

Test Result ◽

Post Test Probability ◽

Test Probability

Identifying the SARS-CoV-2 virus has been a unique challenge for the scientific community. In this paper, we discuss a practical solution to help guide clinicians with interpretation of the probability that a positive, or negative, COVID-19 test result indicates an infected person, based on their clinical estimate of pre-test probability of infection.The authors conducted a small survey on LinkedIn to confirm that hypothesis that that the clinical pre-test probability of COVID-19 increases relative to local prevalence of disease plus patient age, known contact, and severity of symptoms. We examined results of PPA (Positive Percent Agreement, sensitivity) and NPA (Negative Percent Agreement, specificity) from 73 individual laboratory experiments for molecular tests for SARS-CoV-2 as reported to the FIND database 1, and for selected methods in FDA EUA submissions2,3. Authors calculated likelihood ratios to convert pre-test to post-test probability of disease and designed an online calculator to create graphics and text to report results. Despite best efforts, false positive and false negative Covid-19 test results are unavoidable4,5. A positive or negative test result from one laboratory has a different probability for the presence of disease than the same result from another laboratory. Likelihood ratios and confidence intervals can convert the physician or other healthcare professional’s clinical estimate of pre-test probability to post-test probability of disease. Ranges of probabilities differ depending on proven method PPA and NPA in each laboratory. We recommend that laboratories verify PPA and NPA and utilize a the “Clinician’s Probability Calculator” to verify acceptable test performance and create reports to help guide clinicians with estimation of post-test probability of COVID-19.

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Performance of the 2016 diagnostic criteria for fibromyalgia in a tertiary care pain rehabilitation setting: a diagnostic accuracy study

Scandinavian Journal of Pain ◽

10.1515/sjpain-2021-0081 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Karin Due Bruun ◽

Hanne Irene Jensen ◽

Morten Rune Blichfeldt-Eckhardt ◽

Henrik Bjarke Vaegter ◽

Palle Toft ◽

...

Keyword(s):

Diagnostic Accuracy ◽

Diagnostic Criteria ◽

Tertiary Care ◽

Survey Questionnaire ◽

Diagnostic Accuracy Study ◽

Rehabilitation Centers ◽

Post Test ◽

Accuracy Study ◽

Post Test Probability ◽

Test Probability

Abstract Objectives With the International Classification of Diseases 11th revision (classifying fibromyalgia as a primary pain disorder) soon to be implemented, the importance of pain physicians being able to identify patients with fibromyalgia is emphasized. The diagnostic criteria proposed in 2016 are based on self-reported pain distribution and symptom severity. The study aimed to evaluate the diagnostic accuracy of the 2016 diagnostic criteria for fibromyalgia applied in a population of patients with high impact chronic pain referred for pain rehabilitation. Methods The study was performed as a diagnostic accuracy study at two Danish interdisciplinary pain rehabilitation centers, including 215 participants. All participants were evaluated clinically to identify patients with fibromyalgia. The diagnosis was based on expert opinion, but the minimum requirements were: (1) pain in all four body quadrants and axially for at least three months and (2) minimum 8 of 18 positive tender points. Participants filled in the fibromyalgia survey questionnaire, the patient version of the 2016 diagnostic criteria. Sensitivity, specificity, likelihood ratios, and positive and negative post-test probabilities were calculated using a clinical diagnosis of fibromyalgia as the reference standard. Results Based on clinical diagnosis 45% of the participants were diagnosed with fibromyalgia; of these, only 19% had been diagnosed previously. The 2016 diagnostic criteria demonstrated a sensitivity of 88.5%, a specificity of 81.5%, a positive likelihood ratio of 4.79, a negative likelihood ratio of 0.14, a positive post-test probability of 79.4%, and a negative post-test probability of 10.2%. Conclusions Fibromyalgia was severely under-diagnosed among patients with high impact chronic pain referred to tertiary care in two pain rehabilitation centers in Denmark. The 2016 diagnostic criteria showed sufficient discriminatory properties suggesting that the fibromyalgia survey questionnaire can be used as a screening tool assisting the identification of fibromyalgia in this patient population.

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Stratum-specific likelihood ratios of two versions of the General Health Questionnaire

Psychological Medicine ◽

10.1017/s0033291701003713 ◽

2001 ◽

Vol 31 (3) ◽

pp. 519-529 ◽

Cited By ~ 36

Author(s):

T. A. FURUKAWA ◽

D. P. GOLDBERG, ◽

S. RABE-HESKETH ◽

T. B. ÜSTÜN

Keyword(s):

General Health ◽

Meta Analysis ◽

General Health Questionnaire ◽

Likelihood Ratios ◽

Random Samples ◽

Post Test ◽

Meta Regression ◽

Post Test Probability ◽

Threshold Approach ◽

Test Probability

Background. In other branches of epidemiology, stratum specific likelihood ratios (SSLRs) have been found to be preferable to fixed best threshold approaches to screening instruments. This paper presents SSLRs of GHQ-12 and GHQ-28 and compares the SSLR method with the traditional optimal threshold approach.Methods. Random effects meta-analysis and meta-regression were used to obtain pooled estimates of SSLRs of the two questionnaires for the 15 centres participating in the WHO study of Psychological Problems in General Health Care. We illustrated the use of SSLRs by applying them to random samples of patients from centres with different backgrounds.Results. For developed and urban centres, the estimates of SSLRs were homogeneous for 10 out of 12 strata of the GHQ-12 and GHQ-28. For other centres, the overall results, which were heterogeneous for six out of 12 strata, were deemed the currently available best estimates. When we applied these results to centres with different prevalences of mental disorders and backgrounds, the estimates matched the actually observed closely. These examples showed how the SSLR approach is more informative than the traditional threshold approach.Conclusions. Those working in developed urban settings can use the corresponding SSLRs with reasonable confidence. Those working in non-urban or developing areas may wish to use the overall results, while acknowledging that they must remain less certain until further research can explicate heterogeneity. These SSLRs have been incorporated into nomograms and spreadsheet programmes so that future researchers can swiftly derive the post-test probability for a patient or a group of patients from a pre-test probability and GHQ score.

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Viewpoint: Diagnosis in primary care: probabilistic reasoning

Journal of Primary Health Care ◽

10.1071/hc12166 ◽

2012 ◽

Vol 4 (2) ◽

pp. 166 ◽

Cited By ~ 6

Author(s):

Bruce Arroll ◽

GM Allan ◽

C Raina Elley ◽

Tim Kenealy ◽

James McCormack ◽

...

Keyword(s):

Primary Care ◽

Diagnostic Accuracy ◽

False Positive ◽

Probabilistic Reasoning ◽

False Negative ◽

Post Test ◽

Low Prevalence ◽

Post Test Probability ◽

Test Probability ◽

Rule Out

This article develops the concept of probabilistic reasoning as one of the techniques clinicians use in making a diagnosis. We develop the concept that every question and every examination is a diagnostic test ultimately leading to a rule in or rule out of a diagnosis. We also develop the concept of pre-test probability pointing out that false positive tests are an issue in low-prevalence settings and false negative tests are a problem. Investigative tests work best in medium-prevalence settings. The purpose of taking a history and conducting an examination is to increase the pre-test probability to a point where either treatment is commenced or more expensive/time-consuming/dangerous tests are indicated. Pre-test probabilities on their own can be used to rule out conditions. We also show how pre-test probabilities relate to the Fagan nomogram which enables visualisation of large changes in post-test probabilities which can lead to treatment/further investigation. KEYWORDS: Likelihood ratio; pre-test and post-test probability; diagnostic accuracy; probabilistic reasoning

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The Diagnostic Accuracy of Сoronary Сomputed Tomography Angiography in the Diagnosis of Stable Coronary Artery Disease in Patients Aged 70 Years and Older

Kardiologiia ◽

10.18087/cardio.2019.12.n565 ◽

2019 ◽

Vol 59 (12) ◽

pp. 28-34

Author(s):

S. G. Kozlov ◽

O. V. Chernova ◽

T. N. Veselova ◽

S. K. Ternovoy

Keyword(s):

Chest Pain ◽

Coronary Artery ◽

Diagnostic Accuracy ◽

Positive Result ◽

Likelihood Ratio ◽

Stable Coronary Artery Disease ◽

Post Test ◽

Artery Disease ◽

Post Test Probability ◽

Test Probability

Aim: The purpose of this study was to evaluate the diagnostic accuracy of сoronary сomputed tomography angiography (CCTA) in the diagnosis of stable coronary artery disease (CAD) in patients aged ≥70 years. Materials and methods: The study included 390 patients aged ≥70 years with symptoms suggested stable CAD which underwent elective coronary artery angiography (CAG). Initially the prevalence of angiographically significant CAD was estimated according to the gender and chest pain character, and identifications of patients in whom CCTA was appropriate. After that diagnostic accuracy and сost-efficiency of CCTA in the diagnosis of stable CAD in 82 patients with atypical angina and non-anginal chest pain were evaluated. Results: The prevalence of obstructive CAD in patients with typical angina was very high and they were excluded from the final analysis. Among 82 patients with atypical angina and non-anginal pain which underwent CCTA 48 (59%) patients had obstructive CAD. CСTA data matched with results of CAG in all cases. Among 34 patients that had non-obstructive CAD the results of CCTA and CAG matched in 88% cases. CCTA has sensitivity, specificity, positive predictive value, negative predictive value of 100%, 88%, 92% and 100% respectively. The likelihood ratio for positive result was 8.3, likelihood ratio for negative result was 0.3. Positive result increased post-test probability of obstructive CAD from 42% to 86%, negative result reduced post-test probability of obstructive CAD to 0%. Conclusion: negative CCTA result in patients aged 70 years and older with atypical angina and non-anginal pain allows to exclude the presence of obstructive CAD. The likelihood ratio for positive result indicates a moderately difference between the pre-test and post-test probability of the presence of obstructive CAD. In patients aged ≥70 years with atypical angina or non-anginal chest pain which have inconclusive results of functional testing or unable undergo functional testing CCTA allows to increase diagnostic yield of CAG and reduce the frequency of minor complications and diagnostic evaluation costs.

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