Next Issue

Table of Contents

Diagnostics, Volume 1, Issue 1 (December 2011), Pages 1-76

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
View options order results:
result details:
Displaying articles 1-4
Export citation of selected articles as:

Editorial

Jump to: Research, Review

Open AccessEditorial Welcome to Diagnostics: a New Open Access Journal for the Fast-Growing Field of Medical Diagnostics
Diagnostics 2011, 1(1), 36-37; doi:10.3390/diagnostics1010036
Received: 23 November 2011 / Accepted: 23 November 2011 / Published: 23 November 2011
PDF Full-text (117 KB) | HTML Full-text | XML Full-text
Abstract
Diagnostic methods in medicine are currently rapidly evolving and constantly improving. This is true for areas such as molecular diagnostics, biomarkers, as well as medical imaging. As one example, positron emission tomography (PET) has been called the fastest growing medical technology ever. Also,
[...] Read more.
Diagnostic methods in medicine are currently rapidly evolving and constantly improving. This is true for areas such as molecular diagnostics, biomarkers, as well as medical imaging. As one example, positron emission tomography (PET) has been called the fastest growing medical technology ever. Also, molecular diagnostics, at both the gene and protein levels, are developing rapidly due to advances in technology and, thereby, creating new possibilities. Early and valid diagnosis is crucial for proper treatment of patients. Moreover, advanced diagnostic methods are crucial for the upcoming era of tailored therapy. From an economic viewpoint, the cost of advanced treatments are increasingly indicating the need for better stratification and therapy monitoring of treatment, in order that these advanced treatments are limited to patients able to respond favorably. Collectively, the exciting area of medical diagnostics seems never to have been more important for patients and society. [...] Full article

Research

Jump to: Editorial, Review

Open AccessArticle Flow-Mediated Vasodilatation and Intima-Media Thickness in Patients with Coexisting Heart Failure and Diabetes Receiving Medical Therapy
Diagnostics 2011, 1(1), 38-52; doi:10.3390/diagnostics1010038
Received: 25 November 2011 / Accepted: 5 December 2011 / Published: 8 December 2011
PDF Full-text (247 KB) | HTML Full-text | XML Full-text
Abstract
Objective: Intensive medical treatment of heart failure (HF) patients with diabetes may reduce the endothelial dysfunction and the accelerated atherosclerotic process seen in these patients. To study this, we investigated the endothelial function and the presence of atherosclerosis as measured by flow-mediated vasodilatation
[...] Read more.
Objective: Intensive medical treatment of heart failure (HF) patients with diabetes may reduce the endothelial dysfunction and the accelerated atherosclerotic process seen in these patients. To study this, we investigated the endothelial function and the presence of atherosclerosis as measured by flow-mediated vasodilatation (FMD) and intima-media thickness (IMT) in intensively treated patients with coexisting HF and diabetes. Research Design and Method: FMD of the brachial artery and IMT of the common carotid arteries were determined in 26 patients with systolic HF and diabetes who were in intensive medical therapy, as well as in 19 healthy controls. The two groups were matched according to age and sex. In all subjects left ventricular ejection fraction was measured by two-dimensional echocardiography. Biochemical parameters including serum cholesterol, HDL and LDL, triglyceride, glucose, hemoglobin/hemoglobin-A1C (HbA1C), brain natriuretic peptide (BNP) and N-terminal pro-BNP were also assessed. Results: Mean FMD and IMT did not differ significantly between patients and controls. Left ventricular ejection fraction was lower in patients compared to controls (P < 0.001). The patients had a higher mean BNP, NT pro-BNP, triglyceride, HbA1C and glucose in comparison to controls. Cholesterol, HDL-cholesterol and LDL-cholesterol were lower in patients compared to controls. Conclusions: Intensively treated patients with coexisting systolic HF and diabetes seem to have normal endothelial function as measured by FMD and they have no sign of accelerated atherosclerosis as measured by IMT. This suggests a positive effect of medication on the cardiovascular alterations in this group of patients. Full article
Open AccessArticle Bayesian Estimation of Combined Accuracy for Tests with Verification Bias
Diagnostics 2011, 1(1), 53-76; doi:10.3390/diagnostics1010053
Received: 31 October 2011 / Revised: 30 November 2011 / Accepted: 5 December 2011 / Published: 15 December 2011
PDF Full-text (1614 KB) | HTML Full-text | XML Full-text
Abstract
This presentation will emphasize the estimation of the combined accuracy of two or more tests when verification bias is present. Verification bias occurs when some of the subjects are not subject to the gold standard. The approach is Bayesian where the estimation of
[...] Read more.
This presentation will emphasize the estimation of the combined accuracy of two or more tests when verification bias is present. Verification bias occurs when some of the subjects are not subject to the gold standard. The approach is Bayesian where the estimation of test accuracy is based on the posterior distribution of the relevant parameter. Accuracy of two combined binary tests is estimated employing either “believe the positive” or “believe the negative” rule, then the true and false positive fractions for each rule are computed for two tests. In order to perform the analysis, the missing at random assumption is imposed, and an interesting example is provided by estimating the combined accuracy of CT and MRI to diagnose lung cancer. The Bayesian approach is extended to two ordinal tests when verification bias is present, and the accuracy of the combined tests is based on the ROC area of the risk function. An example involving mammography with two readers with extreme verification bias illustrates the estimation of the combined test accuracy for ordinal tests. Full article

Review

Jump to: Editorial, Research

Open AccessReview Bayesian Methods for Medical Test Accuracy
Diagnostics 2011, 1(1), 1-35; doi:10.3390/diagnostics1010001
Received: 18 February 2011 / Revised: 12 April 2011 / Accepted: 20 April 2011 / Published: 5 May 2011
Cited by 1 | PDF Full-text (177 KB) | HTML Full-text | XML Full-text
Abstract
Bayesian methods for medical test accuracy are presented, beginning with the basic measures for tests with binary scores: true positive fraction, false positive fraction, positive predictive values, and negative predictive value. The Bayesian approach is taken because of its efficient use of prior
[...] Read more.
Bayesian methods for medical test accuracy are presented, beginning with the basic measures for tests with binary scores: true positive fraction, false positive fraction, positive predictive values, and negative predictive value. The Bayesian approach is taken because of its efficient use of prior information, and the analysis is executed with a Bayesian software package WinBUGS®. The ROC (receiver operating characteristic) curve gives the intrinsic accuracy of medical tests that have ordinal or continuous scores, and the Bayesian approach is illustrated with many examples from cancer and other diseases. Medical tests include X-ray, mammography, ultrasound, computed tomography, magnetic resonance imaging, nuclear medicine and tests based on biomarkers, such as blood glucose values for diabetes. The presentation continues with more specialized methods suitable for measuring the accuracies of clinical studies that have verification bias, and medical tests without a gold standard. Lastly, the review is concluded with Bayesian methods for measuring the accuracy of the combination of two or more tests. Full article

Journal Contact

MDPI AG
Diagnostics Editorial Office
St. Alban-Anlage 66, 4052 Basel, Switzerland
diagnostics@mdpi.com
Tel. +41 61 683 77 34
Fax: +41 61 302 89 18
Editorial Board
Contact Details Submit to Diagnostics
Back to Top