Tehran University Medical Journal

Considering the advancement of medical sciences, diagnostic tests have been developed to distinguish patients from healthy population. Therefore, Determining and evaluation of the diagnostic accuracy tests is of great importance. The accuracy of a test under evaluation is determined through the amount of agreement between its results with the results of the gold standard, and this test accuracy can be defined based on sensitivity, specificity, positive predictive value, negative predictive value and the area under the receiver operative characteristic curve (AUC). Gold standard is an accurate and error- free method to determine the presence or absence of disease of interest and classify patients, which is not available in some diseases and situations as this method is costly or invasive. In these cases, reference standard is a best available replacement method to be used by physicians to diagnostic disease. However, in some situation, the acceptable reference standard is invasive or costly and does not exist or unreliable. It can be imperfect and results of the reference standard method are not necessarily error- free and cannot be applied to everyone in the study; all these cases point to the conditions in which the gold standard is not available. The use of reference standard including error causes to incorrect separation of patients from healthy population and thus, it cannot be a comparing measure for other diagnostic tests and its results are inaccurate. Therefore, other alternatives methods are needed for evaluation and determine the diagnostic accuracy tests when the gold standard does not exist. Imputation method, correct imperfect reference standard method, the construct reference standard method, latent class models, differential verification, composite reference standard and discrepant analysis are of these alternative methods. Each of these methods, considering its features, advantages, and limitations can be used to evaluate the accuracy of diagnostic test in the absence of gold standard. The present study gave an overview of methods to evaluation of diagnostic accuracy tests when there is no gold standard and the focus of this study was on explain the concept of these solutions, review and compare them and their strengths and weaknesses.

The purpose of prenatal diagnosis tests is insisting of diagnosis of neonatal disorders, preparing a range of informed choices and making couples at risk to be ready for having children with genetic disorders as well. The aim of this article is to investigate all of the tests in order to determine the best one which has the lowest risk and the highest sensitivity. Screening tests (maternal blood test and ultrasonography for first and second trimester) are testing patients without symptoms who are at low risk. These tests are carried out in the early stages of pregnancy, and the risk of genetic diseases would be estimated. They are safe and also might be helpful in determining whether invasive prenatal genetic tests including chorionic villus sampling, amniocentesis, and percutaneous umbilical blood sampling are needed. Diagnostic test is insisting of invasive tests: amniocentesis, chorionic villus sampling (CVS), cordocentesis, and preimplantation genetic diagnosis (PGD), which is a genetic test on cells removed from embryos to help select the best ones to avoid some of genetic diseases, fluorescence in situ hybridization (FISH), QF-PCR, multiplex ligation probe amplification (MLPA), next generation sequencing (NGS), comparative genomic hybridization (CGH), and non-invasive tests: ultrasound, prenatal sonography, cell free fetal DNA, triple and quadruple screen: alpha fetoprotein (AFP), human chorionic gonadotropin (hCG), unconjugated estriol (uE3), inhibin-A). These tests are intended for patients who have apparent symptoms and the results of their early stages of pregnancy have been positive. Non-invasive prenatal tests (NIPT), sometimes called noninvasive prenatal screening (NIPS), have features of both screening and diagnostic tests, but, now screening test is more considerable. Small fragments of DNA would be analyzed by this testing in which they are circulating in a pregnant woman’s blood. While most DNA is found inside a cell’s nucleus, these fragments are free-floating and not within cells, at this point, they are called cell-free DNA (cfDNA) which usually contain fewer than 200 DNA building blocks (base pairs). Non-invasive prenatal tests is more sensitive with the high degree of specify to determine trisomy 13, 18 and 21 in women who are at increased risk of having offspring with genetic disorders.

Background: Rotator cuff injuries are the most common causes of shoulder pain and supraspinatus muscle is usually involved. Clinical tests are available and inexpensive tools for assessment of shoulder dysfunctions. The empty can (EC) and full can (FC) tests are considered as shoulder gold standard tests. Recently, hug up (HU) test has been developed to assess the supraspinatus. So far, no ultrasonographic study has compared supraspinatus muscle thickness in these testing positions. The present study aimed to compare the supraspinatus muscle thickness in the hug up testing position with the full can and empty can testing positions in young and healthy women.
Methods: Forty healthy women (mean age 21.62±2.4 years) participated in this cross-sectional-comparative study from April to June 2018 in the Biomechanic Laboratory of Rehabilitation School, Shahid Beheshti University of Medical Sciences in Tehran, Iran. The supraspinatus muscle thickness was scanned during rest and contracted states with a 0.5 Kg weight cuff. For contracted states, (A) EC testing position: the arm was at 90º abduction in the scaption plane with the thumb-down, (B) FC testing position: the arm was maintained at 90º abduction in the scaption plane with the thumb-up, (C) HU testing position: the palm of hand was placed on the opposite shoulder with the elbow flexed.
Results: The Bonferroni test showed significant differences (P<0.001) between the muscle thickness in the rest and the testing positions. The muscle thickness in the empty can testing position was significantly less than the full can testing position (P=0.001), no significant difference was found between the muscle thickness in the hug up testing position compared to the full can and empty can testing positions.
Conclusion: All of the empty can, full can and hug up testing positions demonstrated increased mean muscle thickness when compared to the rest position and the greatest muscle thickness was in the full can testing position. It seems that supraspinatus muscle thickness in hug up testing position is similar with empty can and full can testing positions.