Comparison of diagnostic tests in myasthenia gravis

Results of 3 tests, intravenous edrophonium chloride, EMG, and acetylcholine receptor antibody testing, were compared in patients with generalised and ocular myasthenia gravis. None of the 3 tests was positive in any patient with a diagnosis other than myasthenia. However, equivocal results were obtained with edrophonium and EMG testing in some patients with myasthenia gravis and in patients with other diseases. It is concluded from this survey that antibody and edrophonium testing were equally efficient in detecting generalised myasthenia gravis. Edrophonium testing was superior in ocular myasthenia gravis. Although the yields from each test varied, all 3 tests were needed for the evaluation of some myasthenia gravis patients as each test may provide additional information.

Malaria rapid diagnostic test performance : results of WHO product testing of malaria RDTs : round 5 (2013)

WHO estimates that half the world’s population is at risk of malaria. In 2012, there were an estimated 207 million cases (with an uncertainty range of 135 million to 287 million) and an estimated 627 000 deaths (with an uncertainty range of 473 000 to 789 000). Approximately 90% of all malaria deaths occur in sub-Saharan Africa, and 77% occur in children under 5 years. Malaria remains endemic in 104 countries, and, while parasite-based diagnosis is increasing, most suspected cases of malaria are still not properly confirmed, resulting in over-use of antimalarial drugs and poor disease monitoring (1)...

Diagnostic Tests Based on Quantile Residuals for Nonlinear Time Series Models

This thesis studies quantile residuals and uses different methodologies to develop test statistics that are applicable in evaluating linear and nonlinear time series models based on continuous distributions. Models based on mixtures of distributions are of special interest because it turns out that for those models traditional residuals, often referred to as Pearson's residuals, are not appropriate. As such models have become more and more popular in practice, especially with financial time series data there is a need for reliable diagnostic tools that can be used to evaluate them. The aim of the thesis is to show how such diagnostic tools can be obtained and used in model evaluation. The quantile residuals considered here are defined in such a way that, when the model is correctly specified and its parameters are consistently estimated, they are approximately independent with standard normal distribution. All the tests derived in the thesis are pure significance type tests and are theoretically sound in that they properly take the uncertainty caused by parameter estimation into account. -- In Chapter 2 a general framework based on the likelihood function and smooth functions of univariate quantile residuals is derived that can be used to obtain misspecification tests for various purposes. Three easy-to-use tests aimed at detecting non-normality, autocorrelation, and conditional heteroscedasticity in quantile residuals are formulated. It also turns out that these tests can be interpreted as Lagrange Multiplier or score tests so that they are asymptotically optimal against local alternatives. Chapter 3 extends the concept of quantile residuals to multivariate models. The framework of Chapter 2 is generalized and tests aimed at detecting non-normality, serial correlation, and conditional heteroscedasticity in multivariate quantile residuals are derived based on it. Score test interpretations are obtained for the serial correlation and conditional heteroscedasticity tests and in a rather restricted special case for the normality test. In Chapter 4 the tests are constructed using the empirical distribution function of quantile residuals. So-called Khmaladze s martingale transformation is applied in order to eliminate the uncertainty caused by parameter estimation. Various test statistics are considered so that critical bounds for histogram type plots as well as Quantile-Quantile and Probability-Probability type plots of quantile residuals are obtained. Chapters 2, 3, and 4 contain simulations and empirical examples which illustrate the finite sample size and power properties of the derived tests and also how the tests and related graphical tools based on residuals are applied in practice.

Impact of a Point-of-Care Rapid Influenza Test on Antibiotic Prescribing Patterns in Southern Sri Lanka

Background: Acute febrile respiratory illnesses, including influenza, account for a large proportion of ambulatory care visits worldwide. In the developed world, these encounters commonly result in unwarranted antibiotic prescriptions; data from more resource-limited settings are lacking. The purpose of this study was to describe the epidemiology of influenza among outpatients in southern Sri Lanka and to determine if access to rapid influenza test results was associated with decreased antibiotic prescriptions.

Methods: In this pretest- posttest study, consecutive patients presenting from March 2013- April 2014 to the Outpatient Department of the largest tertiary care hospital in southern Sri Lanka were surveyed for influenza-like illness (ILI). Patients meeting World Health Organization criteria for ILI-- acute onset of fever ≥38.0°C and cough in the prior 7 days--were enrolled. Consenting patients were administered a structured questionnaire, physical examination, and nasal/nasopharyngeal sampling. Rapid influenza A/B testing (Veritor System, Becton Dickinson) was performed on all patients, but test results were only released to patients and clinicians during the second phase of the study (December 2013- April 2014).

Results: We enrolled 397 patients with ILI, with 217 (54.7%) adults ≥12 years and 188 (47.4%) females. A total of 179 (45.8%) tested positive for influenza by rapid testing, with April- July 2013 and September- November 2013 being the periods with the highest proportion of ILI due to influenza. A total of 310 (78.1%) patients with ILI received a prescription for an antibiotic from their outpatient provider. The proportion of patients prescribed antibiotics decreased from 81.4% in the first phase to 66.3% in the second phase (p=.005); among rapid influenza-positive patients, antibiotic prescriptions decreased from 83.7% in the first phase to 56.3% in the second phase (p=.001). On multivariable analysis, having a positive rapid influenza test available to clinicians was associated with decreased antibiotic use (OR 0.20, 95% CI 0.05- 0.82).

Conclusions: Influenza virus accounted for almost 50% of acute febrile respiratory illness in this study, but most patients were prescribed antibiotics. Providing rapid influenza test results to clinicians was associated with fewer antibiotic prescriptions, but overall prescription of antibiotics remained high. In this developing country setting, a multi-faceted approach that includes improved access to rapid diagnostic tests may help decrease antibiotic use and combat antimicrobial resistance.

Do You Want to Hear the Bad News? The Value of Diagnostic Tests for Alzheimer's Disease.

OBJECTIVE: The diagnosis of Alzheimer's disease (AD) remains difficult. Lack of diagnostic certainty or possible distress related to a positive result from diagnostic testing could limit the application of new testing technologies. The objective of this paper is to quantify respondents' preferences for obtaining AD diagnostic tests and to estimate the perceived value of AD test information. METHODS: Discrete-choice experiment and contingent-valuation questions were administered to respondents in Germany and the United Kingdom. Choice data were analyzed by using random-parameters logit. A probit model characterized respondents who were not willing to take a test. RESULTS: Most respondents indicated a positive value for AD diagnostic test information. Respondents who indicated an interest in testing preferred brain imaging without the use of radioactive markers. German respondents had relatively lower money-equivalent values for test features compared with respondents in the United Kingdom. CONCLUSIONS: Respondents preferred less invasive diagnostic procedures and tests with higher accuracy and expressed a willingness to pay up to €700 to receive a less invasive test with the highest accuracy.

Reduction in the use of diagnostic tests in infants with risk factors for early-onset neonatal sepsis does not delay antibiotic treatment.

Despite a low positive predictive value, diagnostic tests such as complete blood count (CBC) and C-reactive protein (CRP) are commonly used to evaluate whether infants with risk factors for early-onset neonatal sepsis (EOS) should be treated with antibiotics. We investigated the impact of implementing a protocol aiming at reducing the number of diagnostic tests in infants with risk factors for EOS in order to compare the diagnostic performance of repeated clinical examination with CBC and CRP measurement. The primary outcome was the time between birth and the first dose of antibiotics in infants treated for suspected EOS. Among the 11,503 infants born at ≥35 weeks during the study period, 222 were treated with antibiotics for suspected EOS. The proportion of infants receiving antibiotics for suspected EOS was 2.1% and 1.7% before and after the change of protocol (p = 0.09). Reduction of diagnostic tests was associated with earlier antibiotic treatment in infants treated for suspected EOS (hazard ratio 1.58; 95% confidence interval [CI] 1.20-2.07; p <0.001), and in infants with neonatal infection (hazard ratio 2.20; 95% CI 1.19-4.06; p = 0.01). There was no difference in the duration of hospital stay nor in the proportion of infants requiring respiratory or cardiovascular support before and after the change of protocol. Reduction of diagnostic tests such as CBC and CRP does not delay initiation of antibiotic treatment in infants with suspected EOS. The importance of clinical examination in infants with risk factors for EOS should be emphasised.

A capture–recapture approach for screening using two diagnostic tests with availability of disease status for the test positives only

The article considers screening human populations with two screening tests. If any of the two tests is positive, then full evaluation of the disease status is undertaken; however, if both diagnostic tests are negative, then disease status remains unknown. This procedure leads to a data constellation in which, for each disease status, the 2 × 2 table associated with the two diagnostic tests used in screening has exactly one empty, unknown cell. To estimate the unobserved cell counts, previous approaches assume independence of the two diagnostic tests and use specific models, including the special mixture model of Walter or unconstrained capture–recapture estimates. Often, as is also demonstrated in this article by means of a simple test, the independence of the two screening tests is not supported by the data. Two new estimators are suggested that allow associations of the screening test, although the form of association must be assumed to be homogeneous over disease status. These estimators are modifications of the simple capture–recapture estimator and easy to construct. The estimators are investigated for several screening studies with fully evaluated disease status in which the superior behavior of the new estimators compared to the previous conventional ones can be shown. Finally, the performance of the new estimators is compared with maximum likelihood estimators, which are more difficult to obtain in these models. The results indicate the loss of efficiency as minor.

Chlorophyll fluorescence technique as a rapid diagnostic test of the effects of the photosynthetic inhibitor chlorotoluron on two winter wheat cultivars

A modified chlorophyll fluorescence technique was evaluated as a rapid diagnostic test of the susceptibility of wheat cultivars to chlorotoluron. Two winter wheat cultivars (Maris Huntsman and Mercia) exhibited differential response to the herbicide. All of the parameters of chlorophyll fluorescence examined were strongly influenced by herbicide concentration. Additionally, the procedure adopted here for the examination of winter wheat cultivar sensitivity to herbicide indicated that the area above the fluorescence induction curve and the ratio F-V/F-M are appropriate chlorophyll fluorescence parameters for detection of differential herbicide response between wheat cultivars. The potential use of this technique as an alternative to traditional methods of screening new winter wheat cultivars for their response to photosynthetic inhibitor herbicide is demonstrated here.

A capture-recapture approach for screening using two diagnostic tests with availability of disease status for the test positives only

The article considers screening human populations with two screening tests. If any of the two tests is positive, then full evaluation of the disease status is undertaken; however, if both diagnostic tests are negative, then disease status remains unknown. This procedure leads to a data constellation in which, for each disease status, the 2 x 2 table associated with the two diagnostic tests used in screening has exactly one empty, unknown cell. To estimate the unobserved cell counts, previous approaches assume independence of the two diagnostic tests and use specific models, including the special mixture model of Walter or unconstrained capture-recapture estimates. Often, as is also demonstrated in this article by means of a simple test, the independence of the two screening tests is not supported by the data. Two new estimators are suggested that allow associations of the screening test, although the form of association must be assumed to be homogeneous over disease status. These estimators are modifications of the simple capture-recapture estimator and easy to construct. The estimators are investigated for several screening studies with fully evaluated disease status in which the superior behavior of the new estimators compared to the previous conventional ones can be shown. Finally, the performance of the new estimators is compared with maximum likelihood estimators, which are more difficult to obtain in these models. The results indicate the loss of efficiency as minor.

Chlorophyll fluorescence technique as a rapid diagnostic test of the effects of the photosynthetic inhibitor chlorotoluron on two winter wheat cultivars

A modified chlorophyll fluorescence technique was evaluated as a rapid diagnostic test of the susceptibility of wheat cultivars to chlorotoluron. Two winter wheat cultivars (Maris Huntsman and Mercia) exhibited differential response to the herbicide. All of the parameters of chlorophyll fluorescence examined were strongly influenced by herbicide concentration. Additionally, the procedure adopted here for the examination of winter wheat cultivar sensitivity to herbicide indicated that the area above the fluorescence induction curve and the ratio F-V/F-M are appropriate chlorophyll fluorescence parameters for detection of differential herbicide response between wheat cultivars. The potential use of this technique as an alternative to traditional methods of screening new winter wheat cultivars for their response to photosynthetic inhibitor herbicide is demonstrated here.

Bayesian Estimation for Performance Measures of Two Diagnostic Tests in the Presence of Verification Bias

Sensitivity and specificity are measures that allow us to evaluate the performance of a diagnostic test. In practice, it is common to have situations where a proportion of selected individuals cannot have the real state of the disease verified, since the verification could be an invasive procedure, as occurs with biopsy. This happens, as a special case, in the diagnosis of prostate cancer, or in any other situation related to risks, that is, not practicable, nor ethical, or in situations with high cost. For this case, it is common to use diagnostic tests based only on the information of verified individuals. This procedure can lead to biased results or workup bias. In this paper, we introduce a Bayesian approach to estimate the sensitivity and the specificity for two diagnostic tests considering verified and unverified individuals, a result that generalizes the usual situation based on only one diagnostic test.

Comparing diagnostic tests with missing data

When missing data occur in studies designed to compare the accuracy of diagnostic tests, a common, though naive, practice is to base the comparison of sensitivity, specificity, as well as of positive and negative predictive values on some subset of the data that fits into methods implemented in standard statistical packages. Such methods are usually valid only under the strong missing completely at random (MCAR) assumption and may generate biased and less precise estimates. We review some models that use the dependence structure of the completely observed cases to incorporate the information of the partially categorized observations into the analysis and show how they may be fitted via a two-stage hybrid process involving maximum likelihood in the first stage and weighted least squares in the second. We indicate how computational subroutines written in R may be used to fit the proposed models and illustrate the different analysis strategies with observational data collected to compare the accuracy of three distinct non-invasive diagnostic methods for endometriosis. The results indicate that even when the MCAR assumption is plausible, the naive partial analyses should be avoided.

Accuracy of routine diagnostic tests used in paracoccidioidomycosis patients at a university hospital

The identification of appropriate laboratory measures to confirm clinical hypotheses is important in routine paracoccidioidomycosis medical care. The clinical records and laboratory reports of 401 paracoccidioidomycosis patients attended at the Tropical Diseases Area, Faculdade de Medicina de Botucatu, from 1974 to 2008 were reviewed. Direct mycological (DM), cell block (CB), histopathological (HP), and double immunodiffusion (DID) tests were evaluated before treatment. Typical Paracoccidioides brasiliensis yeast forms were observed in clinical specimens of 86% of the patients, but 14% were detected only by serological test. DM of 51 different tissue specimens produced 74.5% sensitivity, and 62.5% sensitivity was observed in 112 sputum samples. CB in 483 sputum samples generated 55.3% sensitivity. HP performed in 239 samples from different tissues revealed 96.7% sensitivity. Serology carried out in 351 patients and 200 healthy controls provided 90.0% sensitivity, 100.0% specificity, 100.0% positive predictive value, 85.1% negative predictive value and 93.6% accuracy. Comparisons of laboratory measurements performed in the same patient showed that sensitivity decreases from HP to DID to CB and DM, with the last two assays providing similar sensitivities. This study demonstrated that P. brasiliensis identification by HP, CB, and/or DM associated with DID is sufficient to establish the laboratorial diagnosis of paracoccidioidomycosis in practically all cases. (C) 2011 Royal Society of Tropical Medicine and Hygiene. Published by Elsevier Ltd. All rights reserved.

Comparison of diferent diagnostic tests in dogs uninfected and naturally infected with visceral leishmaniasis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A General Latent Class Model for Performance Evaluation of Diagnostic Tests in the Absence of a Gold Standard: An Application to Chagas Disease

We propose a new general Bayesian latent class model for evaluation of the performance of multiple diagnostic tests in situations in which no gold standard test exists based on a computationally intensive approach. The modeling represents an interesting and suitable alternative to models with complex structures that involve the general case of several conditionally independent diagnostic tests, covariates, and strata with different disease prevalences. The technique of stratifying the population according to different disease prevalence rates does not add further marked complexity to the modeling, but it makes the model more flexible and interpretable. To illustrate the general model proposed, we evaluate the performance of six diagnostic screening tests for Chagas disease considering some epidemiological variables. Serology at the time of donation (negative, positive, inconclusive) was considered as a factor of stratification in the model. The general model with stratification of the population performed better in comparison with its concurrents without stratification. The group formed by the testing laboratory Biomanguinhos FIOCRUZ-kit (c-ELISA and rec-ELISA) is the best option in the confirmation process by presenting false-negative rate of 0.0002% from the serial scheme. We are 100% sure that the donor is healthy when these two tests have negative results and he is chagasic when they have positive results.