The Interpretation of Test Results

2000 ◽  
Vol 4 (1) ◽  
pp. 19-25 ◽  
Author(s):  
Michael Binder ◽  
Stephan Dreiseitl
Keyword(s):  
Decision Making ◽  
Receiver Operating Characteristic ◽  
Diagnostic Tests ◽  
Operating Characteristic ◽  
Roc Curves ◽  
Test Results ◽  
Likelihood Ratios ◽  
Clinical Routine ◽  
Predictive Values ◽  
Sensitivity Specificity

Background: Dermatologists need to interpret an increasing number of research studies and diagnostic tests. Understanding the techniques for interpreting test results and making decisions based upon those tests represent important tools for decision making for both clinicians and researchers. Objective: This article focuses briefly on the key parameters of diagnostic tests: sensitivity, specificity, prevalence, predictive values, likelihood ratios, and the concept of receiver-operating-characteristic (ROC) curves. A simple example is presented in a step-by-step manner. Conclusion: The principles of interpreting test results are easy to learn and applicable in daily clinical routine. Therefore, dermatologists should be familiar with the concepts outlined in this paper.

scholarly journals El dilema del vigilante. Valoración de pruebas diagnósticas.

2018 ◽  
Vol 10 (8) ◽  
pp. 4
Author(s):  
Manuel Molina
Keyword(s):  
Diagnostic Tests ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
Significant Parameter ◽  
Quantitative Results ◽  
Sensitivity Specificity

Existen una serie de parámetros que caracterizan las pruebas diagnósticas, como son la sensibilidad, la especificidad, los valores predictivos y los cocientes de probabilidad. Solo estos últimos nos permiten el cálculo de la probabilidad del paciente de presentar la enfermedad, con independencia de la prevalencia en la población. Para caracterizar las pruebas con resultado cuantitativo se utilizan las curvas ROC, cuyo parámetro más significativo es el área bajo la curva. ABSTRACT There are a series of parameters that characterize the diagnostic tests, such as sensitivity, specificity, predictive values and likelihood ratios. Only the latter allow us to calculate the patient's probability of presenting the disease, regardless of the prevalence in the population. To characterize the tests with quantitative results, the ROC curves are used, whose most significant parameter is the area under the curve.

scholarly journals Diagnostic testing: an emergency medicine perspective

CJEM ◽  
2002 ◽  
Vol 4 (05) ◽  
pp. 348-354 ◽  
Author(s):  
Andrew Worster ◽  
Grant Innes ◽  
Riyad B. Abu-Laban
Keyword(s):  
Diagnostic Tests ◽  
Diagnostic Testing ◽  
Test Results ◽  
Emergency Physicians ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
The Core ◽  
Core Concepts ◽  
Sensitivity Specificity ◽  
Test Probability

ABSTRACT: Emergency physicians use diagnostic tests extensively, and the ability to order and interpret test results appropriately is a critical skill. An understanding of sensitivity, specificity, predictive values and likelihood ratios, as well as an awareness of the importance of pre-test probability, is essential. The purpose of this article is to explain, in a straightforward and clinically applicable manner, the core concepts related to diagnostic testing.

scholarly journals Diagnostic performances of manual and automated reticulocyte parameters in anaemic cats

2017 ◽  
Vol 20 (2) ◽  
pp. 122-127 ◽  
Author(s):  
Saverio Paltrinieri ◽  
Marco Fossati ◽  
Valentina Menaballi
Keyword(s):  
Receiver Operating Characteristic ◽  
Sensitivity And Specificity ◽  
Operating Characteristic ◽  
Positive Likelihood Ratio ◽  
Roc Curves ◽  
Blood Samples ◽  
Production Index ◽  
Instrumental Measurement ◽  
Sensitivity Specificity ◽  
Reticulocyte Production

Objectives The objective of this study was to evaluate the diagnostic performances of manual and instrumental measurement of reticulocyte percentage (Ret%), reticulocyte number (Ret#) and reticulocyte production index (RPI) to differentiate regenerative anaemia (RA) from non-regenerative anaemia (NRA) in cats. Methods Data from 106 blood samples from anaemic cats with manual counts (n = 74; 68 NRA, six RA) or instrumental counts of reticulocytes (n = 32; 25 NRA, seven RA) collected between 1995 and 2013 were retrospectively analysed. Sensitivity, specificity and positive likelihood ratio (LR+) were calculated using either cut-offs reported in the literature or cut-offs determined from receiver operating characteristic (ROC) curves. Results All the reticulocyte parameters were significantly higher in cats with RA than in cats with NRA. All the ROC curves were significantly different ( P <0.001) from the line of no discrimination, without significant differences between the three parameters. Using the cut-offs published in literature, the Ret% (cut-off: 0.5%) was sensitive (100%) but not specific (<75%), the RPI (cut-off: 1.0) was specific (>92%) but not sensitive (<15%), and the Ret# (cut-off: 50 × 10³/µl) had a sensitivity and specificity >80% and the highest LR+ (manual count: 14; instrumental count: 6). For all the parameters, sensitivity and specificity approached 100% using the cut-offs determined by the ROC curves. These cut-offs were higher than those reported in the literature for Ret% (manual: 1.70%; instrumental: 3.06%), lower for RPI (manual: 0.39; instrumental: 0.59) and variably different, depending on the method (manual: 41 × 10³/µl; instrumental: 57 × 10³/µl), for Ret#. Using these cut-offs, the RPI had the highest LR+ (manual: 22.7; instrumental: 12.5). Conclusions and relevance This study indicated that all the reticulocyte parameters may confirm regeneration when the pretest probability is high, while when this probability is moderate, RA should be identified using the RPI providing that cut-offs <1.0 are used.

Clinical Epidemiology

2016 ◽  
pp. 285-290
Author(s):  
Scott C. Litin ◽  
John B. Bundrick
Keyword(s):  
Diagnostic Test ◽  
Diagnostic Tests ◽  
Clinical Decision Making ◽  
Clinical Epidemiology ◽  
Clinical Decision ◽  
Test Results ◽  
Specific Patient ◽  
Predictive Values ◽  
Test Sensitivity ◽  
Sensitivity Specificity

Diagnostic tests are tools that either increase or decrease the likelihood of disease. The sensitivity, specificity, and predictive values of normal and abnormal test results can be calculated with even a limited amount of information. Some physicians prefer interpreting diagnostic test results by using the likelihood ratio. This ratio takes properties of a diagnostic test (sensitivity and specificity) and makes them more helpful in clinical decision making. It helps the clinician determine the probability of disease in a specific patient after a diagnostic test has been performed.

Diagnostic Tests Distinguishing Good Tests From Bad and Even Ugly Ones

2000 ◽  
Vol 21 (4) ◽  
pp. 278-284 ◽  
Author(s):  
David Birnbaum ◽  
Barry M. Farr ◽  
David E. Shapiro
Keyword(s):  
Positive Result ◽  
Diagnostic Tests ◽  
Roc Analysis ◽  
Operating Characteristic ◽  
Bloodstream Infections ◽  
Roc Curves ◽  
Optimal Cutoff ◽  
Overall Performance ◽  
Sensitivity Specificity ◽  
Catheter Related Bloodstream Infection

This article focuses on the selection and interpretation of diagnostic tests, emphasizing the importance of understanding how their mathematical parameters affect the information they provide in various settings. The utility and limitations of sensitivity, specificity, predictive value, and receiver operating characteristic (ROC) curves are discussed using catheter-related bloodstream infections as an example. ROC curves have been used for selecting optimal cutoff values for a positive result and for selecting among several alternative diagnostic tests. For example, 16 different tests have been proposed for diagnosis of catheter-related bloodstream infection; ROC analysis provides an effective way to determine which test offers the best overall performance.

Using Receiver Operating Characteristic (ROC) Analysis to Evaluate Information-Based Decision-Making

2019 ◽  
pp. 764-776 ◽  
Author(s):  
Nan Hu
Keyword(s):  
Decision Making ◽  
Receiver Operating Characteristic ◽  
Roc Analysis ◽  
Operating Characteristic ◽  
Decision Rules ◽  
Scoring Systems ◽  
Roc Curves ◽  
Decision Tools ◽  
Classification Tool ◽  
Receiver Operating

Business operators and stakeholders often need to make decisions such as choosing between A and B, or between yes and no, and these decisions are often made by using a classification tool or a set of decision rules. Decision tools usually include scoring systems, predictive models, and quantitative test modalities. In this chapter, the authors introduce the receiver operating characteristic (ROC) curves and demonstrate, through an example of bank decision on granting loans to customers, how ROC curves can be used to evaluate decision making for information-based decision making. In addition, an extension to time-dependent ROC analysis is introduced in this chapter. The authors conclude this chapter by illustrating the application of ROC analysis in information-based decision making and providing the future trends of this topic.

scholarly journals Clinicians' guide to evaluating diagnostic and screening tests in psychiatry

2004 ◽  
Vol 10 (6) ◽  
pp. 446-454 ◽  
Author(s):  
James Warner
Keyword(s):  
Diagnostic Tests ◽  
Critical Appraisal ◽  
Evidence Base ◽  
Psychiatric Practice ◽  
Screening Tests ◽  
Clinical Settings ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
Incorrect Diagnosis ◽  
Sensitivity Specificity

The emphasis on the evidence base of treatments may diminish awareness that critical appraisal of research into other aspects of psychiatric practice is equally important. There is a risk that diagnostic tests may be inappropriate in some clinical settings or the results of a particular test may be over-interpreted, leading to incorrect diagnosis. This article outlines the method of critically evaluating the validity of articles about diagnostic and screening tests in psychiatry and discusses concepts of sensitivity, specificity and predictive values. The use of likelihood ratios in improving clinical certainty that a disease is present or absent is examined.

scholarly journals Sensitivity, Specificity, Predictive Values, and Accuracy of Three Diagnostic Tests to Predict Inferior Alveolar Nerve Blockade Failure in Symptomatic Irreversible Pulpitis

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Daniel Chavarría-Bolaños ◽  
Laura Rodríguez-Wong ◽  
Danny Noguera-González ◽  
Vicente Esparza-Villalpando ◽  
Mauricio Montero-Aguilar ◽  
...  
Keyword(s):  
Diagnostic Tests ◽  
Inferior Alveolar Nerve ◽  
Roc Curves ◽  
Cross Sectional Study ◽  
Anesthetic Technique ◽  
Cross Sectional ◽  
Predictive Values ◽  
Anesthetic Failure ◽  
Sensitivity Specificity ◽  
Irreversible Pulpitis

Introduction.The inferior alveolar nerve block (IANB) is the most common anesthetic technique used on mandibular teeth during root canal treatment. Its success in the presence of preoperative inflammation is still controversial. The aim of this study was to evaluate the sensitivity, specificity, predictive values, and accuracy of three diagnostic tests used to predict IANB failure in symptomatic irreversible pulpitis (SIP).Methodology.A cross-sectional study was carried out on the mandibular molars of 53 patients with SIP. All patients received a single cartridge of mepivacaine 2% with 1 : 100000 epinephrine using the IANB technique. Three diagnostic clinical tests were performed to detect anesthetic failure. Anesthetic failure was defined as a positive painful response to any of the three tests. Sensitivity, specificity, predictive values, accuracy, and ROC curves were calculated and compared and significant differences were analyzed.Results.IANB failure was determined in 71.7% of the patients. The sensitivity scores for the three tests (lip numbness, the cold stimuli test, and responsiveness during endodontic access) were 0.03, 0.35, and 0.55, respectively, and the specificity score was determined as 1 for all of the tests. Clinically, none of the evaluated tests demonstrated a high enough accuracy (0.30, 0.53, and 0.68 for lip numbness, the cold stimuli test, and responsiveness during endodontic access, resp.). A comparison of the areas under the curve in the ROC analyses showed statistically significant differences between the three tests (p<0.05).Conclusion.None of the analyzed tests demonstrated a high enough accuracy to be considered a reliable diagnostic tool for the prediction of anesthetic failure.

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