Preparation of test cells for the antiglobulin test

Erythrocytes may be coated with blood group antibodies with or without reacting complement or sometimes apparently with complement alone. This may occur in vivo in such conditions as autoimmune acquired haemolytic anaemia, haemolytic disease of the newborn, or after transfusions of incompatible blood. It may occur in vitro also by the deliberate sensitization of erythrocytes during laboratory serological investigations.Blood group antibodies may be of immunoglobulin types gammaM, gammaA, or gammaG; we have never seen gammaD antibodies. The presence of these antibodies on the erythrocyte surface, together with complement components or the presence of complement components alone, may be detected by the direct antiglobulin test where sensitization occurs in vivo or by the indirect antiglobulin test where there is sensitization in vitro.     

Comparison of test results obtained with two neuropsychological test batteries

Compared test results of two neuropsychological test batteries, the Hakstead-Reitan Neuropsychological Test Battery (HRNTB) and Luria's Neuropsycho-logical Investigation (LNI), to investigate the possibility of coming to the same conclusions concerning the brain-behavior relationships with the help of neuropsychological methods based on controversial theoretical assumptions. Test data were obtained from a sample of 31 inpatients of a psychiatric hospital. The concordance concerning the presence of brain dysfunction, its lateralization, and main localization was evaluated. A high degree of agreement was found supporting the construct validity of the tests for neuropsychological assessment of psychiatric patients.     

An experimental study of the hand test situation: effects of test definition during instruction on hand test performance

The purpose of this study was to examine how Hand Test performance is affected by test definition included with task instructions. The Hand Test was administered to male college students equally divided into three groups which differed in terms of the type of test definition included with the task instruction as follows: (1) Emotionally disturbed test definition (ED Group); (2) Imagery test definition (IM Group); and, (3) Standard instruction with no test definition (N Group). The MMPI was subsequently administered to all subjects with the following results. The ED Group revealed higher DES and lower ACQ scores than the N Group. The IM Group obtained higher DES and TEN scores and lower ACQ and ICP (CRIP) scores than the N Group. The ED Group exhibited positive correlations between PASS, ACQ and ICP (CRIP) scores and psychopathological MMPI scales while the IM Group revealed negative correlations between ACQ, PASS, TEN, ICP (CRIP), FEAR and DES scores and psychopathological MMPI scales. These results indicated in general that Hand Test performance is sensitive to the test situation and that this factor should be taken into account when Hand Test responses are interpreted.     

Unusual test score combinations and unusual test score differences

Vocabulary and Abstraction scores on the Shipley Institute of Living Scale are used to illustrate the relation between unusual test score combinations and unusual test score differences. It is demonstrated that a combination of two scores can be unusual even though the corresponding difference is not and that a difference between two scores can be unusual even though the corresponding combination is not. Clinicians should be aware that although the two methods of pattern analysis generally will lead to the same conclusion, they need not do so.     

Reducing bias from test misclassification in burden of disease studies: use of test to actual positive ratio--new test parameter

Aim

To address the problem of estimating disease frequency identified by a diagnostic test, which may not represent the actual number of persons with disease in a community, but rather the number of persons who tested positive. Those two values may be very different, their relationship depending on the properties of the diagnostic test applied and true prevalence of the disease in a population.

Methods

We defined a new test parameter, the ratio of Test to Actual Positives (TAP), which summarizes the properties of the diagnostic test applied and true prevalence of the disease in a population, and propose that is the most useful summary measure of the potential for bias in disease frequency estimates.

Results

A consideration of the relationship between the sensitivity (Se) and specificity (Sp) of the diagnostic test and the true prevalence of disease in a population can inform study design by highlighting the potential for disease misclassification bias. The effects of a decrease in Sp on the TAP ratio at very low disease prevalence are dramatic, as at 80% Sp (and any Se value including 100%), the measured disease frequency will represent a 25-fold overestimate. At a disease prevalence of 0.10, the Sp needs to be 90% or greater to achieve a TAP ratio of 1.0. However, unlike at lower levels of disease prevalence, the test Se is also an important determinant of the TAP ratio. A TAP ratio of 1.0 can be achieved by a Sp of 95% and intermediate Se (40%-60%); or a Sp of 99% and very high Se (over 90%). This illustrates how a test with poor performance characteristics in a clinical setting can perform well in a disease burden study in a population. In circumstances in which the TAP ratio suggests a potential for a large bias, we suggest correction procedures that limit disease misclassification bias and which are often counter-intuitive. We also illustrate how these methods can improve the power of intervention studies which define outcomes by use of a diagnostic test.

Conclusions

Optimal screening test characteristics for use in a population-based survey are likely to be different to those when the test is utilized in a clinical setting. Calibrating the test a priori to bring the TAP ratio closer to unity deals with the possible large bias in disease burden estimates based on application of diagnostic (screening) test.Observational studies estimate burden of disease and are increasingly used to inform health planning and resource allocation decisions at both the global and local level (1-4). However, measures of disease frequency (eg, prevalence and incidence) reported in these studies typically do not represent the actual number of persons with disease in a community, rather they show the number of persons who tested positive for a diagnostic test (including verbal autopsies). Those two values may be very similar, but may also be very different, depending on the properties of the diagnostic test applied (5).Evaluations of diagnostic or screening tests within public health programs have concentrated on the test parameters – sensitivity (Se) and specificity (Sp) – since these describe performance within the overall program. They are independent of disease prevalence and thus estimates of these parameters in one setting may retain relevance in a variety of settings. Evaluations of diagnostic tests within clinical settings often focus on positive and negative predictive values and likelihood ratios of the test, as these guide the interpretation of the test to individual patients (6). However, in this paper we consider a different use of a test, where the primary aim is estimating the prevalence or incidence of disease in a population.In our recent review which aimed to produce global burden estimate of a specific childhood disease (pneumonia) for the World Health Organization (WHO) (7), we realized that large potential problems exist when diagnostic tests designed for use in clinical settings are applied in community settings to measure disease frequencies (5,8-10). In this study, we aimed to define the relationships between diagnostic test validity, disease prevalence, and accuracy of disease frequency estimates. We considered potential implications of these relationships on study design and interpretation and illustrated these with examples from the literature and our own work. We also generalized these findings to discuss the impact of an imperfect screening or diagnostic test in:1) yielding inaccurate estimates of disease prevalence and incidence (as well as invalid comparisons across groups); and2) limiting the power of a study to detect differences in disease prevalence and incidence across groups.