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Diagnostics, Volume 10, Issue 5 (May 2020) – 88 articles

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Cover Story (view full-size image) Magnetic lateral flow immunoassays (LFIAs) are emerging as powerful biosensors for diagnostics. On [...] Read more.
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Open AccessArticle
Proteomics-Based Identification of Diagnostic Biomarkers Related to Risk Factors and Pathogenesis of Ischemic Stroke
Diagnostics 2020, 10(5), 340; https://doi.org/10.3390/diagnostics10050340 - 25 May 2020
Viewed by 527
Abstract
Ischemic stroke is caused by blood clot formation and consequent vessel blockage. Proteomic approaches provide a cost-effective alternative to current diagnostic methods, including computerized tomography (CT) scans and magnetic resonance imaging (MRI). To identify diagnostic biomarkers associated with ischemic stroke risk factors, we [...] Read more.
Ischemic stroke is caused by blood clot formation and consequent vessel blockage. Proteomic approaches provide a cost-effective alternative to current diagnostic methods, including computerized tomography (CT) scans and magnetic resonance imaging (MRI). To identify diagnostic biomarkers associated with ischemic stroke risk factors, we performed individual proteomic analysis of serum taken from 20 healthy controls and 20 ischemic stroke patients. We then performed SWATH analysis, a data-independent method, to assess quantitative changes in protein expression between the two experimental conditions. Our analysis identified several candidate protein biomarkers, 11 of which were validated by multiple reaction monitoring (MRM) analysis as novel diagnostic biomarkers associated with ischemic stroke risk factors. Our study identifies new biomarkers associated with the risk factors and pathogenesis of ischemic stroke which, to the best of our knowledge, were previously unknown. These markers may be effective in not only the diagnosis but also the prevention and management of ischemic stroke. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
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Open AccessReview
Parkinson’s Disease: Available Clinical and Promising Omics Tests for Diagnostics, Disease Risk Assessment, and Pharmacotherapy Personalization
Diagnostics 2020, 10(5), 339; https://doi.org/10.3390/diagnostics10050339 - 25 May 2020
Viewed by 622
Abstract
Parkinson’s disease is the second most frequent neurodegenerative disease, representing a significant medical and socio-economic problem. Modern medicine still has no answer to the question of why Parkinson’s disease develops and whether it is possible to develop an effective system of prevention. Therefore, [...] Read more.
Parkinson’s disease is the second most frequent neurodegenerative disease, representing a significant medical and socio-economic problem. Modern medicine still has no answer to the question of why Parkinson’s disease develops and whether it is possible to develop an effective system of prevention. Therefore, active work is currently underway to find ways to assess the risks of the disease, as well as a means to extend the life of patients and improve its quality. Modern studies aim to create a method of assessing the risk of occurrence of Parkinson’s disease (PD), to search for the specific ways of correction of biochemical disorders occurring in the prodromal stage of Parkinson’s disease, and to personalize approaches to antiparkinsonian pharmacotherapy. In this review, we summarized all available clinically approved tests and techniques for PD diagnostics. Then, we reviewed major improvements and recent advancements in genomics, transcriptomics, and proteomics studies and application of metabolomics in PD research, and discussed the major metabolomics findings for diagnostics and therapy of the disease. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
Open AccessReview
Recent Advances: The Imbalance of Immune Cells and Cytokines in the Pathogenesis of Hepatocellular Carcinoma
Diagnostics 2020, 10(5), 338; https://doi.org/10.3390/diagnostics10050338 - 25 May 2020
Viewed by 630
Abstract
Recent advancement in the immunological understanding of genesis of hepatocellular carcinoma (HCC) has implicated a decline in anti-tumour immunity on the background of chronic inflammatory state of liver parenchyma. The development of HCC involves a network of immunological activity in the tumour microenvironment [...] Read more.
Recent advancement in the immunological understanding of genesis of hepatocellular carcinoma (HCC) has implicated a decline in anti-tumour immunity on the background of chronic inflammatory state of liver parenchyma. The development of HCC involves a network of immunological activity in the tumour microenvironment involving continuous interaction between tumour and stromal cells. The reduction in anti-tumour immunity is secondary to changes in various immune cells and cytokines, and the tumour microenvironment plays a critical role in modulating the process of liver fibrosis, hepatocarcinogenesis, epithelial-mesenchymal transition (EMT), tumor invasion and metastasis. Thus, it is considered as one of primary factor behind the despicable tumour behavior and observed poor survival; along with increased risk of recurrence following treatment in HCC. The primary intent of the present review is to facilitate the understanding of the complex network of immunological interactions of various immune cells, cytokines and tumour cells associated with the development and progression of HCC. Full article
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Open AccessReview
The Diagnostic Dilemma of Malignant Biliary Strictures
Diagnostics 2020, 10(5), 337; https://doi.org/10.3390/diagnostics10050337 - 25 May 2020
Viewed by 612
Abstract
The differential diagnosis for biliary strictures is broad. However, the likelihood of malignancy is high. Determining the etiology of a biliary stricture requires a comprehensive physical exam, laboratory evaluation, imaging, and ultimately tissue acquisition. Even then, definitive diagnosis is elusive, and many strictures [...] Read more.
The differential diagnosis for biliary strictures is broad. However, the likelihood of malignancy is high. Determining the etiology of a biliary stricture requires a comprehensive physical exam, laboratory evaluation, imaging, and ultimately tissue acquisition. Even then, definitive diagnosis is elusive, and many strictures remain indeterminant in origin. This literary review examines the diagnostic dilemma of biliary strictures and presents innovations in both histochemical and endoscopic techniques that have increased the diagnostic power of differentiating benign and malignant strictures. The field of tissue biopsy is revolutionizing with the advent of free DNA mutation profiling, fluorescence in situ hybridization (FISH), and methionyl t-RNA synthetase 1 (MARS 1), which allow for greater testing sensitivity. Endoscopic ultrasound, endoscopic retrograde cholangiopancreatography (ERCP), cholangioscopy, confocal laser endomicroscopy, and intraductal ultrasound build upon existing endoscopic technology to better characterize strictures that would otherwise be indeterminate in etiology. This review uses recent literature to insert innovative technology into the traditional framework of diagnostic methods for malignant biliary strictures. Full article
(This article belongs to the Special Issue Endoscopic Diagnostics for Pancreatobiliary Disorders)
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Open AccessArticle
Plasma Zinc Levels in Males with Androgenetic Alopecia as Possible Predictors of the Subsequent Conservative Therapy’s Effectiveness
Diagnostics 2020, 10(5), 336; https://doi.org/10.3390/diagnostics10050336 - 24 May 2020
Cited by 1 | Viewed by 890
Abstract
Androgenic alopecia (AGA) is the most common type of progressive hair loss in man. The search for reliable predictors of the conservative treatment’s effectiveness is an urgent problem today. Forty-eight patients with AGA, stages I–IV by the Norwood–Hamilton scale, were treated for 4 [...] Read more.
Androgenic alopecia (AGA) is the most common type of progressive hair loss in man. The search for reliable predictors of the conservative treatment’s effectiveness is an urgent problem today. Forty-eight patients with AGA, stages I–IV by the Norwood–Hamilton scale, were treated for 4 months with 5% topical minoxidil joints with corrections for trace element and vitamin imbalances. In most cases, the positive therapy’s effect was shown in the parietal but not in the occipital area, whereas that effect was observed in others. The attempts to associate the therapy’s effectiveness with initially defined genetic, hormonal, and metabolic parameters showed the absence of differences between groups with positive and negative outcomes. Among the studied nutrient parameters (Zn, Cu, Mg, Ca, Fe, and Se, as well as vitamins B12, E, D, and folic acid), differences between these groups was shown in zinc content only. The starting point from a zinc plasma level above 10 µmol/L likely provides the success of the subsequent conservative therapy and correlates with an increase in the hair density and diameter in the parietal area. The integral predictive value of the Zn plasma level was assessed as 72.3% (positive predictive value: −88%; and negative predictive value: −55%). Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
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Open AccessArticle
The Double-Edged Sword of T1-Mapping in Systemic Sclerosis—A Comparison with Infectious Myocarditis Using Cardiovascular Magnetic Resonance
Diagnostics 2020, 10(5), 335; https://doi.org/10.3390/diagnostics10050335 - 24 May 2020
Viewed by 593
Abstract
Aims: T1-mapping is considered a surrogate marker of acute myocardial inflammation. However, in diffuse cutaneous systemic sclerosis (dcSSc) this might be confounded by coexisting myocardial fibrosis. We hypothesized that T1-based indices should not by themselves be considered as indicators of myocardial inflammation in [...] Read more.
Aims: T1-mapping is considered a surrogate marker of acute myocardial inflammation. However, in diffuse cutaneous systemic sclerosis (dcSSc) this might be confounded by coexisting myocardial fibrosis. We hypothesized that T1-based indices should not by themselves be considered as indicators of myocardial inflammation in dcSSc patients. Methods/Results: A cohort of 59 dcSSc and 34 infectious myocarditis patients was prospectively evaluated using a 1.5-Tesla system for an indication of suspected myocardial inflammation and was compared with 31 healthy controls. Collectively, 33 (97%) and 57 (98%) of myocarditis and dcSSc patients respectively had ≥1 pathologic T2-based index. However, 33 (97%) and 45 (76%) of myocarditis and dcSSc patients respectively had ≥1 pathologic T2-based index. T2-signal ratio was significantly higher in myocarditis patients compared with dcSSc patients (2.5 (0.6) vs. 2.1 (0.4), p < 0.001). Early gadolinium enhancement, late gadolinium enhancement and T2-mapping did not differ significantly between groups. However, both native T1-mapping and extracellular volume fraction were significantly lower in myocarditis compared with dcSSc patients (1051.0 (1027.0, 1099.0) vs. 1120.0 (1065.0, 1170.0), p < 0.001 and 28.0 (26.0, 30.0) vs. 31.5 (30.0, 33.0), p < 0.001, respectively). The original Lake Louise criteria (LLc) were positive in 34 (100%) myocarditis and 40 (69%) dcSSc patients, while the updated LLc were positive in 32 (94%) and 44 (76%) patients, respectively. Both criteria had good agreement with greater but nonsignificant discordance in dcSSc patients. Conclusions: ~25% of dcSSc patients with suspected myocardial inflammation had no CMR evidence of acute inflammatory processes. T1-based indices should not be used by themselves as surrogates of acute myocardial inflammation in dcSSc patients. Full article
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Open AccessReview
Reporting Standards for a Bland–Altman Agreement Analysis: A Review of Methodological Reviews
Diagnostics 2020, 10(5), 334; https://doi.org/10.3390/diagnostics10050334 - 22 May 2020
Viewed by 644
Abstract
The Bland–Altman Limits of Agreement is a popular and widespread means of analyzing the agreement of two methods, instruments, or raters in quantitative outcomes. An agreement analysis could be reported as a stand-alone research article but it is more often conducted as a [...] Read more.
The Bland–Altman Limits of Agreement is a popular and widespread means of analyzing the agreement of two methods, instruments, or raters in quantitative outcomes. An agreement analysis could be reported as a stand-alone research article but it is more often conducted as a minor quality assurance project in a subgroup of patients, as a part of a larger diagnostic accuracy study, clinical trial, or epidemiological survey. Consequently, such an analysis is often limited to brief descriptions in the main report. Therefore, in several medical fields, it has been recommended to report specific items related to the Bland–Altman analysis. The present study aimed to identify the most comprehensive and appropriate list of items for such an analysis. Seven proposals were identified from a MEDLINE/PubMed search, three of which were derived by reviewing anesthesia journals. Broad consensus was seen for the a priori establishment of acceptability benchmarks, estimation of repeatability of measurements, description of the data structure, visual assessment of the normality and homogeneity assumption, and plotting and numerically reporting both bias and the Bland–Altman Limits of Agreement, including respective 95% confidence intervals. Abu-Arafeh et al. provided the most comprehensive and prudent list, identifying 13 key items for reporting (Br. J. Anaesth. 2016, 117, 569–575). An exemplification with interrater data from a local study accentuated the straightforwardness of transparent reporting of the Bland–Altman analysis. The 13 key items should be applied by researchers, journal editors, and reviewers in the future, to increase the quality of reporting Bland–Altman agreement analyses. Full article
(This article belongs to the Special Issue Planning and Evaluating Agreement and Reliability Studies)
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Open AccessCommunication
Optimization of the CDC Protocol of Molecular Diagnosis of COVID-19 for Timely Diagnosis
Diagnostics 2020, 10(5), 333; https://doi.org/10.3390/diagnostics10050333 - 21 May 2020
Viewed by 1157
Abstract
Coronavirus disease 2019 (COVID-19), the current uncontrolled outbreak of infectious disease, has caused significant challenges throughout the world. A reliable rapid diagnostic test for COVID-19 is demanded worldwide. The real-time reverse transcriptase polymerase chain was one of the most quickly established methods in [...] Read more.
Coronavirus disease 2019 (COVID-19), the current uncontrolled outbreak of infectious disease, has caused significant challenges throughout the world. A reliable rapid diagnostic test for COVID-19 is demanded worldwide. The real-time reverse transcriptase polymerase chain was one of the most quickly established methods in the novel viral pandemic and was considered as the gold standard for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this report, we illustrate our experience of applying a protocol from the Taiwan CDC and achieving assay optimization in the immediate circumstances to meet the urgent medical and public health needs. Full article
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Open AccessArticle
Diagnosis of Parkinson’s Disease by A Metabolomics-Based Laboratory-Developed Test (LDT)
Diagnostics 2020, 10(5), 332; https://doi.org/10.3390/diagnostics10050332 - 21 May 2020
Viewed by 643
Abstract
A laboratory-developed test (LDT) is a type of in vitro diagnostic test that is designed, manufactured and used in the same laboratory (i.e., an in-house test). In this study, a metabolomics-based LDT was developed. This test involves a blood plasma preparation, direct-infusion mass [...] Read more.
A laboratory-developed test (LDT) is a type of in vitro diagnostic test that is designed, manufactured and used in the same laboratory (i.e., an in-house test). In this study, a metabolomics-based LDT was developed. This test involves a blood plasma preparation, direct-infusion mass spectrometry analysis with a high-resolution mass spectrometer, alignment and normalization of mass peaks using original algorithms, metabolite annotation by a biochemical context-driven algorithm, detection of overrepresented metabolic pathways and results in a visualization in the form of a pathway names cloud. The LDT was applied to detect early stage Parkinson’s disease (PD)—the diagnosis of which currently requires great effort due to the lack of available laboratory tests. In a case–control study (n = 56), the LDT revealed a statistically sound pattern in the PD-relevant pathways. Usage of the LDT for individuals confirmed its ability to reveal this pattern and thus diagnose PD at the early-stage (1–2.5 stages, according to Hoehn and Yahr scale). The detection of this pattern by LDT could diagnose PD with a specificity of 64%, sensitivity of 86% and an accuracy of 75%. Thus, this LDT can be used for further widespread testing. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
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Open AccessArticle
Subjective Versus Quantitative Methods of Assessing Breast Density
Diagnostics 2020, 10(5), 331; https://doi.org/10.3390/diagnostics10050331 - 21 May 2020
Viewed by 586
Abstract
In order to find a consistent, simple and time-efficient method of assessing mammographic breast density (MBD), different methods of assessing density comparing subjective, quantitative, semi-subjective and semi-quantitative methods were investigated. Subjective MBD of anonymized mammographic cases (n = 250) from a national [...] Read more.
In order to find a consistent, simple and time-efficient method of assessing mammographic breast density (MBD), different methods of assessing density comparing subjective, quantitative, semi-subjective and semi-quantitative methods were investigated. Subjective MBD of anonymized mammographic cases (n = 250) from a national breast-screening programme was rated by 49 radiologists from two countries (UK and USA) who were voluntarily recruited. Quantitatively, three measurement methods, namely VOLPARA, Hand Delineation (HD) and ImageJ (IJ) were used to calculate breast density using the same set of cases, however, for VOLPARA only mammographic cases (n = 122) with full raw digital data were included. The agreement level between methods was analysed using weighted kappa test. Agreement between UK and USA radiologists and VOLPARA varied from moderate (κw = 0.589) to substantial (κw = 0.639), respectively. The levels of agreement between USA, UK radiologists, VOLPARA with IJ were substantial (κw = 0.752, 0.768, 0.603), and with HD the levels of agreement varied from moderate to substantial (κw = 0.632, 0.680, 0.597), respectively. This study found that there is variability between subjective and objective MBD assessment methods, internationally. These results will add to the evidence base, emphasising the need for consistent, simple and time-efficient MBD assessment methods. Additionally, the quickest method to assess density is the subjective assessment, followed by VOLPARA, which is compatible with a busy clinical setting. Moreover, the use of a more limited two-scale system improves agreement levels and could help minimise any potential country bias. Full article
(This article belongs to the Special Issue Multimodality Breast Imaging)
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Open AccessArticle
Detection and Diagnosis of Breast Cancer Using Artificial Intelligence Based Assessment of Maximum Intensity Projection Dynamic Contrast-Enhanced Magnetic Resonance Images
Diagnostics 2020, 10(5), 330; https://doi.org/10.3390/diagnostics10050330 - 20 May 2020
Cited by 1 | Viewed by 901
Abstract
We aimed to evaluate an artificial intelligence (AI) system that can detect and diagnose lesions of maximum intensity projection (MIP) in dynamic contrast-enhanced (DCE) breast magnetic resonance imaging (MRI). We retrospectively gathered MIPs of DCE breast MRI for training and validation data from [...] Read more.
We aimed to evaluate an artificial intelligence (AI) system that can detect and diagnose lesions of maximum intensity projection (MIP) in dynamic contrast-enhanced (DCE) breast magnetic resonance imaging (MRI). We retrospectively gathered MIPs of DCE breast MRI for training and validation data from 30 and 7 normal individuals, 49 and 20 benign cases, and 135 and 45 malignant cases, respectively. Breast lesions were indicated with a bounding box and labeled as benign or malignant by a radiologist, while the AI system was trained to detect and calculate possibilities of malignancy using RetinaNet. The AI system was analyzed using test sets of 13 normal, 20 benign, and 52 malignant cases. Four human readers also scored these test data with and without the assistance of the AI system for the possibility of a malignancy in each breast. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were 0.926, 0.828, and 0.925 for the AI system; 0.847, 0.841, and 0.884 for human readers without AI; and 0.889, 0.823, and 0.899 for human readers with AI using a cutoff value of 2%, respectively. The AI system showed better diagnostic performance compared to the human readers (p = 0.002), and because of the increased performance of human readers with the assistance of the AI system, the AUC of human readers was significantly higher with than without the AI system (p = 0.039). Our AI system showed a high performance ability in detecting and diagnosing lesions in MIPs of DCE breast MRI and increased the diagnostic performance of human readers. Full article
(This article belongs to the Special Issue Advances in Breast MRI)
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Open AccessArticle
Deep Learning Based Automatic Malaria Parasite Detection from Blood Smear and Its Smartphone Based Application
Diagnostics 2020, 10(5), 329; https://doi.org/10.3390/diagnostics10050329 - 20 May 2020
Viewed by 1017
Abstract
Malaria is a life-threatening disease that is spread by the Plasmodium parasites. It is detected by trained microscopists who analyze microscopic blood smear images. Modern deep learning techniques may be used to do this analysis automatically. The need for the trained personnel can [...] Read more.
Malaria is a life-threatening disease that is spread by the Plasmodium parasites. It is detected by trained microscopists who analyze microscopic blood smear images. Modern deep learning techniques may be used to do this analysis automatically. The need for the trained personnel can be greatly reduced with the development of an automatic accurate and efficient model. In this article, we propose an entirely automated Convolutional Neural Network (CNN) based model for the diagnosis of malaria from the microscopic blood smear images. A variety of techniques including knowledge distillation, data augmentation, Autoencoder, feature extraction by a CNN model and classified by Support Vector Machine (SVM) or K-Nearest Neighbors (KNN) are performed under three training procedures named general training, distillation training and autoencoder training to optimize and improve the model accuracy and inference performance. Our deep learning-based model can detect malarial parasites from microscopic images with an accuracy of 99.23% while requiring just over 4600 floating point operations. For practical validation of model efficiency, we have deployed the miniaturized model in different mobile phones and a server-backed web application. Data gathered from these environments show that the model can be used to perform inference under 1 s per sample in both offline (mobile only) and online (web application) mode, thus engendering confidence that such models may be deployed for efficient practical inferential systems. Full article
(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)
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Open AccessArticle
Improving Access to Diagnostics for Schistosomiasis Case Management in Oyo State, Nigeria: Barriers and Opportunities
Diagnostics 2020, 10(5), 328; https://doi.org/10.3390/diagnostics10050328 - 20 May 2020
Cited by 1 | Viewed by 622
Abstract
Schistosomiasis is one of the Neglected Tropical Diseases that affects over 200 million people worldwide, of which 29 million people in Nigeria. The principal strategy for schistosomiasis in Nigeria is a control and elimination program which comprises a school-based Mass Drug Administration (MDA) [...] Read more.
Schistosomiasis is one of the Neglected Tropical Diseases that affects over 200 million people worldwide, of which 29 million people in Nigeria. The principal strategy for schistosomiasis in Nigeria is a control and elimination program which comprises a school-based Mass Drug Administration (MDA) with limitations of high re-infection rates and the exclusion of high-risk populations. The World Health Organization (WHO) recommends guided case management of schistosomiasis (diagnostic tests or symptom-based detection plus treatment) at the Primary Health Care (PHC) level to ensure more comprehensive morbidity control. However, these require experienced personnel with sufficient knowledge of symptoms and functioning laboratory equipment. Little is known about where, by whom and how diagnosis is performed at health facilities within the case management of schistosomiasis in Nigeria. Furthermore, there is a paucity of information on patients’ health-seeking behaviour from the onset of disease symptoms until a cure is obtained. In this study, we describe both perspectives in Oyo state, Nigeria and address the barriers using adapted health-seeking stages and access framework. The opportunities for improving case management were identified, such as a prevalence study of high-risk groups, community education and screening, enhancing diagnostic capacity at the PHC through point-of-care diagnostics and strengthening the capability of health workers. Full article
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Open AccessReview
Electronic Health Information Systems to Improve Disease Diagnosis and Management at Point-of-Care in Low and Middle Income Countries: A Narrative Review
Diagnostics 2020, 10(5), 327; https://doi.org/10.3390/diagnostics10050327 - 20 May 2020
Cited by 1 | Viewed by 840
Abstract
The purpose of an electronic health information system (EHIS) is to support health care workers in providing health care services to an individual client and to enable data exchange among service providers. The demand to explore the use of EHIS for diagnosis and [...] Read more.
The purpose of an electronic health information system (EHIS) is to support health care workers in providing health care services to an individual client and to enable data exchange among service providers. The demand to explore the use of EHIS for diagnosis and management of communicable and non-communicable diseases has increased dramatically due to the volume of patient data and the need to retain patients in care. In addition, the advent of Coronavirus disease 2019 (COVID-19) pandemic in high disease burdened low and middle income countries (LMICs) has increased the need for robust EHIS to enable efficient surveillance of the pandemic. EHIS has potential to enable efficient delivery of disease diagnostics services at point-of-care (POC) and reduce medical errors. This review provides an overview of literature on EHIS’s with a focus on describing the key components of EHIS and presenting evidence on enablers and barriers to implementation of EHISs in LMICs. With guidance from the presented evidence, we proposed EHIS key stakeholders’ roles and responsibilities to ensure efficient utility of EHIS for disease diagnosis and management at POC in LMICs. Full article
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Open AccessReview
Role of Body-Fluid Biomarkers in Alzheimer’s Disease Diagnosis
Diagnostics 2020, 10(5), 326; https://doi.org/10.3390/diagnostics10050326 - 20 May 2020
Viewed by 597
Abstract
Alzheimer’s disease (AD) is a complex neurodegenerative disease that requires extremely specific biomarkers for its diagnosis. For current diagnostics capable of identifying AD, the development and validation of early stage biomarkers is a top research priority. Body-fluid biomarkers might closely reflect synaptic dysfunction [...] Read more.
Alzheimer’s disease (AD) is a complex neurodegenerative disease that requires extremely specific biomarkers for its diagnosis. For current diagnostics capable of identifying AD, the development and validation of early stage biomarkers is a top research priority. Body-fluid biomarkers might closely reflect synaptic dysfunction in the brain and, thereby, could contribute to improving diagnostic accuracy and monitoring disease progression, and serve as markers for assessing the response to disease-modifying therapies at early onset. Here, we highlight current advances in the research on the capabilities of body-fluid biomarkers and their role in AD pathology. Then, we describe and discuss current applications of the potential biomarkers in clinical diagnostics in AD. Full article
(This article belongs to the Special Issue Alzheimer’s Disease Pathophysiology)
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Open AccessArticle
Deep Learning-Based Morphological Classification of Human Sperm Heads
Diagnostics 2020, 10(5), 325; https://doi.org/10.3390/diagnostics10050325 - 20 May 2020
Viewed by 555
Abstract
Human infertility is considered as a serious disease of the reproductive system that affects more than 10% of couples across the globe and over 30% of the reported cases are related to men. The crucial step in the assessment of male infertility and [...] Read more.
Human infertility is considered as a serious disease of the reproductive system that affects more than 10% of couples across the globe and over 30% of the reported cases are related to men. The crucial step in the assessment of male infertility and subfertility is semen analysis that strongly depends on the sperm head morphology, i.e., the shape and size of the head of a spermatozoon. However, in medical diagnosis, the morphology of the sperm head is determined manually, and heavily depends on the expertise of the clinician. Moreover, this assessment as well as the morphological classification of human sperm heads are laborious and non-repeatable, and there is also a high degree of inter and intra-laboratory variability in the results. In order to overcome these problems, we propose a specialized convolutional neural network (CNN) architecture to accurately classify human sperm heads based on sperm images. It is carefully designed with several layers, and multiple filter sizes, but fewer filters and parameters to improve efficiency and effectiveness. It is demonstrated that our proposed architecture outperforms state-of-the-art methods, exhibiting 88% recall on the SCIAN dataset in the total agreement setting and 95% recall on the HuSHeM dataset for the classification of human sperm heads. Our proposed method shows the potential of deep learning to surpass embryologists in terms of reliability, throughput, and accuracy. Full article
(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)
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Open AccessReview
Sonographic Pearls for Imaging the Brachial Plexus and Its Pathologies
Diagnostics 2020, 10(5), 324; https://doi.org/10.3390/diagnostics10050324 - 20 May 2020
Cited by 1 | Viewed by 900
Abstract
The brachial plexus (BP) is a complicated neural network, which may be affected by trauma, irradiation, neoplasm, infection, and autoimmune inflammatory diseases. Magnetic Resonance Imaging is the preferred diagnostic modality; however, it has the limitations of high cost and lack of portability. High-resolution [...] Read more.
The brachial plexus (BP) is a complicated neural network, which may be affected by trauma, irradiation, neoplasm, infection, and autoimmune inflammatory diseases. Magnetic Resonance Imaging is the preferred diagnostic modality; however, it has the limitations of high cost and lack of portability. High-resolution ultrasound has recently emerged as an unparalleled diagnostic tool for diagnosing postganglionic lesions of the BP. Existing literature describes the technical skills needed for prompt ultrasound imaging and guided injections for the BP. However, it remains particularly challenging for beginners to navigate easily while scanning its different parts. To address this, we share several “clinical pearls” for the sonographic examination of the BP as well as its common pathologies. Full article
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Open AccessCase Report
Biphasic Thyroid-Like Low-Grade Nasopharyngeal Papillary Adenocarcinoma with a Prominent Spindle Cell Component: A Case Report
Diagnostics 2020, 10(5), 323; https://doi.org/10.3390/diagnostics10050323 - 19 May 2020
Viewed by 569
Abstract
Thyroid-like low-grade nasopharyngeal papillary adenocarcinoma (TLLG-NPPA) is a distinctly rare malignancy of the nasopharynx. Morphologically and immunophenotypically, TLLG-NPPA resembles papillary thyroid carcinoma (PTC) and is characterized by a papillary architecture with PTC-like nuclear features and thyroid transcription factor-1 expression. Recently, some cases of [...] Read more.
Thyroid-like low-grade nasopharyngeal papillary adenocarcinoma (TLLG-NPPA) is a distinctly rare malignancy of the nasopharynx. Morphologically and immunophenotypically, TLLG-NPPA resembles papillary thyroid carcinoma (PTC) and is characterized by a papillary architecture with PTC-like nuclear features and thyroid transcription factor-1 expression. Recently, some cases of TLLG-NPPA with a spindle cell component have been reported. In this study, we report a very interesting case of biphasic TLLG-NPPA that was predominantly composed of spindle cells, with comprehensive analyses of its clinical, pathological, and immunophenotypical features. A 50-year-old woman presented with a sensation of a foreign body in the nasopharynx. Nasopharyngoscopy and computed tomography demonstrated a pedunculated mass arising from the nasopharyngeal roof. Based on the clinical impression of a nasopharyngeal tumor, an excisional biopsy was performed. At low-power magnification, the nasopharyngeal mass consisted of papillary tumor tissue, the growth pattern and architecture of which resembled those of PTC. The papillae were complex and packed tightly with fibrovascular cores. At high-power magnification, each papillary structure was lined with a pseudostratified cuboidal-to-columnar epithelium. The tumor cell nuclei frequently showed a ground-glass appearance, intranuclear grooves, pseudoinclusions, and membrane thickening and irregularity, resembling the characteristic nuclear morphology of PTC. These histological features were compatible with TLLG-NPPA. Intriguingly, in between the papillary components were spindle cells that appeared very similar to the glandular epithelial cells that imperceptibly merged with the papillary component. This spindle cell component comprised two-thirds of the entire tumor volume. The nuclear morphology of the spindle cell component was similar to that of the papillary component. On immunostaining, both the papillary and spindle cell components were diffusely and strongly positive for thyroid transcription factor-1, cytokeratin 7, cytokeratin 19, vimentin, and Hector Battifora mesothelial-1. In contrast, the tumor cells tested negative for p63, p40, smooth muscle actin, S-100, cytokeratin 5/6, thyroglobulin, BRAF V600E, and Epstein–Barr virus-encoded small RNAs. Only two cases of biphasic TLLG-NPPA exhibiting a prominent spindle cell component had been reported previously in the English literature. When the pathologist receives a primary nasopharyngeal mass with the aforementioned histological features, particularly biopsy specimens with predominant spindle cells, biphasic TLLG-NPPA should be considered in the differential diagnosis. By describing its detailed clinicopathological characteristics, we anticipate that this report will expand the existing knowledge on the spindle cell component associated with TLLG-NPPA. Full article
(This article belongs to the Special Issue Biomarkers of Oral Cancer)
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Open AccessArticle
Cardio-Diagnostic Assisting Computer System
Diagnostics 2020, 10(5), 322; https://doi.org/10.3390/diagnostics10050322 - 19 May 2020
Cited by 1 | Viewed by 593
Abstract
The mathematical analysis and the assessment of heart rate variability (HRV) based on computer systems can assist the diagnostic process with determining the cardiac status of patients. The new cardio-diagnostic assisting computer system created uses the classic Time-Domain, Frequency-Domain, and Time-Frequency analysis indices, [...] Read more.
The mathematical analysis and the assessment of heart rate variability (HRV) based on computer systems can assist the diagnostic process with determining the cardiac status of patients. The new cardio-diagnostic assisting computer system created uses the classic Time-Domain, Frequency-Domain, and Time-Frequency analysis indices, as well as the nonlinear methods (Poincaré plot, Recurrence plot, Hurst R/S method, Detrended Fluctuation Analysis (DFA), Multi-Fractal DFA, Approximate Entropy and Sample Entropy). To test the feasibility of the software developed, 24-hour Holter recordings of four groups of people were analysed: healthy subjects and patients with arrhythmia, heart failure and syncope. Time-Domain (SDNN < 50 ms, SDANN < 100 ms, RMSSD < 17 ms) and Frequency-Domain (the spectrum of HRV in the LF < 550 ms2, and HF < 540 ms2) parameter values decreased in the cardiovascular disease groups compared to the control group as a result of lower HRV due to decreased parasympathetic and increased sympathetic activity. The results of the nonlinear analysis showed low values of (SD1 < 56 ms, SD2 < 110 ms) at Poincaré plot (Alpha < 90 ms) at DFA in patients with diseases. Significantly reducing these parameters are markers of cardiac dysfunction. The examined groups of patients showed an increase in the parameters (DET% > 95, REC% > 38, ENTR > 3.2) at the Recurrence plot. This is evidence of a pathological change in the regulation of heart rhythm. The system created can be useful in making the diagnosis by the cardiologist and in bringing greater accuracy and objectivity to the treatment. Full article
(This article belongs to the Section Point-of-Care Diagnostics and Devices)
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Open AccessArticle
Diagnostic Value of Imaging Methods in the Histological Four Grading of Hepatocellular Carcinoma
Diagnostics 2020, 10(5), 321; https://doi.org/10.3390/diagnostics10050321 - 19 May 2020
Viewed by 513
Abstract
We attempted to establish an ultrasound (US) imaging-diagnostic system for histopathological grades of differentiation of hepatocellular carcinoma (HCC). We conducted a retrospective study of histopathologically confirmed 200 HCCs, classified as early (45 lesions), well- (31 lesions), moderately (68 lesions) or poorly differentiated (diff.) [...] Read more.
We attempted to establish an ultrasound (US) imaging-diagnostic system for histopathological grades of differentiation of hepatocellular carcinoma (HCC). We conducted a retrospective study of histopathologically confirmed 200 HCCs, classified as early (45 lesions), well- (31 lesions), moderately (68 lesions) or poorly differentiated (diff.) (56 lesions) HCCs. We performed grayscale US to estimate the presence/absence of halo and mosaic signs, Sonazoid contrast-enhanced US (CEUS) to determine vascularity (hypo/iso/hyper) of lesion in arterial and portal phase (PP), and echogenicity of lesion in post-vascular phase (PVP). All findings were of significance for the diagnosis of some (but not all) histological grades (p < 0.001–0.05). Combined findings with a relatively high diagnostic efficacy for early, poorly and moderately diff. HCC were a combination of absence of halo sign and isoechogenicity in PVP of CEUS (accuracy: 93.0%, AUC: 0.908), hypovascularity in PP (accuracy: 78.0%, area under the curve (AUC): 0.750), and a combination of isovascularity in PP and hypoechogenicity in PVP (accuracy: 75.0%, AUC: 0.739), respectively. On the other hand, neither any individual finding nor any combination of findings yielded an AUC of over 0.657 for the diagnosis of well-diff. HCC. Our study provides encouraging data on Sonazoid CEUS in the histological differential diagnosis of HCC, especially in early HCC, and the effectiveness of this imaging method should be further proved by prospective, large sample, multicenter studies. Full article
(This article belongs to the Section Medical Imaging)
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Open AccessArticle
Clinical Validation of Integrated Point-of-Care Devices for the Management of Non-Communicable Diseases
Diagnostics 2020, 10(5), 320; https://doi.org/10.3390/diagnostics10050320 - 19 May 2020
Viewed by 509
Abstract
Non-communicable diseases are the leading cause of death and disability across India, including in the poorest states. Effective disease management, particularly for cardiovascular diseases, requires the tracking of several biochemical and physiological parameters over an extended period of time. Currently, patients must go [...] Read more.
Non-communicable diseases are the leading cause of death and disability across India, including in the poorest states. Effective disease management, particularly for cardiovascular diseases, requires the tracking of several biochemical and physiological parameters over an extended period of time. Currently, patients must go to diagnostic laboratories and doctors’ clinics or invest in individual point-of-care devices for measuring the required parameters. The cost and inconvenience of current options lead to inconsistent monitoring, which contribute to suboptimal outcomes. Furthermore, managing multiple individual point-of-devices is challenging and helps track some parameters to the exclusion of others. To address these issues, HealthCubed, a primary care technology company, has designed integrated devices that measure blood glucose, hemoglobin, cholesterol, uric acid, blood pressure, capillary oxygen saturation and pulse rate. Here we report data from clinical studies undertaken in healthy subjects establishing the validity of an integrated device for monitoring multiple parameters. Full article
(This article belongs to the Section Diagnostic Microbiology and Infectious Disease)
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Open AccessArticle
Antibody Tests in Detecting SARS-CoV-2 Infection: A Meta-Analysis
Diagnostics 2020, 10(5), 319; https://doi.org/10.3390/diagnostics10050319 - 19 May 2020
Cited by 5 | Viewed by 2810
Abstract
The emergence of Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 made imperative the need for diagnostic tests that can identify the infection. Although Nucleic Acid Test (NAT) is considered to be the gold standard, serological tests based on antibodies could be very helpful. [...] Read more.
The emergence of Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 made imperative the need for diagnostic tests that can identify the infection. Although Nucleic Acid Test (NAT) is considered to be the gold standard, serological tests based on antibodies could be very helpful. However, individual studies are usually inconclusive, thus, a comparison of different tests is needed. We performed a systematic review and meta-analysis in PubMed, medRxiv and bioRxiv. We used the bivariate method for meta-analysis of diagnostic tests pooling sensitivities and specificities. We evaluated IgM and IgG tests based on Enzyme-linked immunosorbent assay (ELISA), Chemiluminescence Enzyme Immunoassays (CLIA), Fluorescence Immunoassays (FIA), and the Lateral Flow Immunoassays (LFIA). We identified 38 studies containing data from 7848 individuals. Tests using the S antigen are more sensitive than N antigen-based tests. IgG tests perform better compared to IgM ones and show better sensitivity when the samples were taken longer after the onset of symptoms. Moreover, a combined IgG/IgM test seems to be a better choice in terms of sensitivity than measuring either antibody alone. All methods yield high specificity with some of them (ELISA and LFIA) reaching levels around 99%. ELISA- and CLIA-based methods perform better in terms of sensitivity (90%–94%) followed by LFIA and FIA with sensitivities ranging from 80% to 89%. ELISA tests could be a safer choice at this stage of the pandemic. LFIA tests are more attractive for large seroprevalence studies but show lower sensitivity, and this should be taken into account when designing and performing seroprevalence studies. Full article
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Open AccessArticle
Costs of Providing HIV Self-Test Kits to Pregnant Women Living with HIV for Secondary Distribution to Male Partners in Uganda
Diagnostics 2020, 10(5), 318; https://doi.org/10.3390/diagnostics10050318 - 19 May 2020
Viewed by 495
Abstract
Background: Secondary distribution of HIV self-testing kits (HIVST) to pregnant women attending antenatal care (ANC) clinics to give to their male partners is a promising strategy to increase testing coverage among men, but its costs are unknown. Methods: We conducted micro-costing of a [...] Read more.
Background: Secondary distribution of HIV self-testing kits (HIVST) to pregnant women attending antenatal care (ANC) clinics to give to their male partners is a promising strategy to increase testing coverage among men, but its costs are unknown. Methods: We conducted micro-costing of a trial evaluating secondary distribution of HIVST on pregnant women living with HIV (PWLHIV) in an ANC in Kampala, Uganda. Costs (2019 USD) were collected from program budgets, expenditure records, time and motion observations, and staff interviews and estimated for three scenarios: as-studied, reflecting full costs of the research intervention, Ministry of Health (MOH) implementation, reflecting the research intervention if implemented by the MOH, and MOH roll-out, the current strategy being used to roll out HIVST distribution. Results: In the as-studied scenario, cost of HIVST provision was $13.96/PWLHIV reached, and $11.89 and $10.55 per HIV-positive and HIV-negative male partner, respectively, who linked to a clinic for facility-based testing. In the MOH implementation scenario, costs were $9.45/PWLHIV, and $7.87 and $6.99, respectively, per HIV-positive and HIV-negative male partner linking to the clinic. In the MOH roll-out scenario, the cost of HIVST provision to pregnant women regardless of HIV status was $3.70/woman, and $6.65/HIV-positive male partner. Conclusion: Secondary distribution of HIVST from pregnant women can be implemented at reasonable cost to increase testing among men in Uganda and similar settings in Africa. Full article
(This article belongs to the Special Issue HIV Diagnosis, Treatment, and Care)
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Open AccessArticle
Clustering and Kernel Density Estimation for Assessment of Measurable Residual Disease by Flow Cytometry
Diagnostics 2020, 10(5), 317; https://doi.org/10.3390/diagnostics10050317 - 18 May 2020
Viewed by 557
Abstract
Standardization, data mining techniques, and comparison to normality are changing the landscape of multiparameter flow cytometry in clinical hematology. On the basis of these principles, a strategy was developed for measurable residual disease (MRD) assessment. Herein, suspicious cell clusters are first identified at [...] Read more.
Standardization, data mining techniques, and comparison to normality are changing the landscape of multiparameter flow cytometry in clinical hematology. On the basis of these principles, a strategy was developed for measurable residual disease (MRD) assessment. Herein, suspicious cell clusters are first identified at diagnosis using a clustering algorithm. Subsequently, automated multidimensional spaces, named “Clouds”, are created around these clusters on the basis of density calculations. This step identifies the immunophenotypic pattern of the suspicious cell clusters. Thereafter, using reference samples, the “Abnormality Ratio” (AR) of each Cloud is calculated, and major malignant Clouds are retained, known as “Leukemic Clouds” (L-Clouds). In follow-up samples, MRD is identified when more cells fall into a patient’s L-Cloud compared to reference samples (AR concept). This workflow was applied on simulated data and real-life leukemia flow cytometry data. On simulated data, strong patient-dependent positive correlation (R2 = 1) was observed between the AR and spiked-in leukemia cells. On real patient data, AR kinetics was in line with the clinical evolution for five out of six patients. In conclusion, we present a convenient flow cytometry data analysis approach for the follow-up of hematological malignancies. Further evaluation and validation on more patient samples and different flow cytometry panels is required before implementation in clinical practice. Full article
(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)
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Open AccessCase Report
Thyrotoxic Periodic Paralysis—A Misleading Challenge in the Emergency Department
Diagnostics 2020, 10(5), 316; https://doi.org/10.3390/diagnostics10050316 - 18 May 2020
Cited by 1 | Viewed by 641
Abstract
Despite its’ life-threatening potential due to cardiac severe dysrhythmia in the context of severe hypokalemia, thyrotoxic periodic paralysis (TPP) often goes unrecognized. Although classically confined to young Asian men, it can occur irrespective of age, sex, and race. We report a short series [...] Read more.
Despite its’ life-threatening potential due to cardiac severe dysrhythmia in the context of severe hypokalemia, thyrotoxic periodic paralysis (TPP) often goes unrecognized. Although classically confined to young Asian men, it can occur irrespective of age, sex, and race. We report a short series of three cases of TPP as first presentation of Graves’ disease in a young Caucasian male and in two Caucasian elderly and middle-aged women, respectively. The first patient developed malignant ventricular arrhythmias due to severe hypokalemia and was defibrillated, with recovery after prompt potassium correction and administration of antithyroid agents and propranolol. The other two cases developed persistent hypokalemia despite adequate potassium chloride (KCl) repletion, with slow recovery of motor deficit and serum potassium normalization up to day 5. In the first case, long-term euthyroid state was achieved via total thyroidectomy due to the presence of a suspicious nodule that proved to be malignant. In the other two cases, medical treatment was the choice of therapy for thyrotoxicosis. None experienced recurrent TPP. Thyroid hormone evaluation is mandatory in the presence of hypokalemic paralysis, even in the absence of clinical signs of thyrotoxicosis. If TPP is confirmed, initial therapy should comprise antithyroid drugs and propranolol, besides hypokalemia correction. Full article
(This article belongs to the Special Issue New Insights in Thyroid Diagnostics)
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Open AccessArticle
The Over-Expression of E2F3 Might Serve as Prognostic Marker for Neuroblastoma Patients with Stage 4S Disease
Diagnostics 2020, 10(5), 315; https://doi.org/10.3390/diagnostics10050315 - 16 May 2020
Viewed by 586
Abstract
Stage 4S neuroblastoma is a childhood cancer occurring in infants (<12 months at diagnosis) with metastases limited to liver, skin, and bone marrow (<10%). It is associated with an excellent outcome, due to its notable ability to undergo spontaneous regression without any therapeutic [...] Read more.
Stage 4S neuroblastoma is a childhood cancer occurring in infants (<12 months at diagnosis) with metastases limited to liver, skin, and bone marrow (<10%). It is associated with an excellent outcome, due to its notable ability to undergo spontaneous regression without any therapeutic intervention. However, a subgroup of patients is doomed to relapse and eventually to die in spite of aggressive therapies. Stage 4S neuroblastoma shows characteristic hypermethylation of genes involved in the telomere maintenance, indicating that the dysregulation of these genes might serve as prognostic marker. The retinoblastoma tumor suppressor protein (RB)-E2F transcription factors pathway is one of the critical tumor-suppressor/oncogene pathways involved in regulating telomerase expression. We have interrogated in silicopublic neuroblastoma databases for regulators involved in the RB-E2F pathway especially for E2F factors themselves, and we identified the E2F transcription factor 3 (E2F3) expression as a potential prognostic marker in stage 4S neuroblastoma. In order to confirm this finding, we screened 38 paraffin-embedded tissue samples stage 4S neuroblastoma for E2F3 protein expression using immunofluorescence, and we observed that augmented expression was strongly associated with impaired event-free survival. These results indicate that E2F3 expression might serve as prognostic marker in patients with stage 4S disease. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
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Open AccessReview
Current Data Regarding the Relationship between Type 2 Diabetes Mellitus and Cardiovascular Risk Factors
Diagnostics 2020, 10(5), 314; https://doi.org/10.3390/diagnostics10050314 - 16 May 2020
Cited by 1 | Viewed by 1122
Abstract
Reducing cardiovascular risk (CVR) is the main focus of diabetes mellitus (DM) management nowadays. Complex pathogenic mechanisms that are the subject of this review lead to early and severe atherosclerosis in DM patients. Although it is not a cardiovascular disease equivalent at the [...] Read more.
Reducing cardiovascular risk (CVR) is the main focus of diabetes mellitus (DM) management nowadays. Complex pathogenic mechanisms that are the subject of this review lead to early and severe atherosclerosis in DM patients. Although it is not a cardiovascular disease equivalent at the moment of diagnosis, DM subjects are affected by numerous cardiovascular complications, such as acute coronary syndrome, stroke, or peripheral artery disease, as the disease duration increases. Therefore, early therapeutic intervention is mandatory and recent guidelines focus on intensive CVR factor management: hyperglycaemia, hypertension, and dyslipidaemia. Most important, the appearance of oral or injectable antidiabetic medication such as SGLT-2 inhibitors or GLP-1 agonists has proven that an antidiabetic drug not only reduces glycaemia, but also reduces CVR by complex mechanisms. A profound understanding of intimate mechanisms that generate atherosclerosis in DM and ways to inhibit or delay them are of the utmost importance in a society where cardiovascular morbidity and mortality are predominant. Full article
(This article belongs to the Section Pathology and Molecular Diagnostics)
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Open AccessArticle
Two-Dimensional Shear Wave Elastography versus Transient Elastography: A Non-Invasive Comparison for the Assessment of Liver Fibrosis in Patients with Chronic Hepatitis C
Diagnostics 2020, 10(5), 313; https://doi.org/10.3390/diagnostics10050313 - 16 May 2020
Viewed by 509
Abstract
In recent years, several non-invasive methods have been developed for staging liver fibrosis in patients with chronic hepatitis C. A 2D-Shear wave elastography (SWE) technique has been recently introduced on the EPIQ 7 US system (ElastQ), but its accuracy has not been validated [...] Read more.
In recent years, several non-invasive methods have been developed for staging liver fibrosis in patients with chronic hepatitis C. A 2D-Shear wave elastography (SWE) technique has been recently introduced on the EPIQ 7 US system (ElastQ), but its accuracy has not been validated in patients with chronic hepatitis C virus (HCV) infection. We enrolled 178 HCV patients to assess their liver fibrosis stage with ElastQ software using transient elastography as a reference standard. The best cut-off values to diagnose ≥ F2, ≥ F3, and F4 were 8.15, 10.31, and 12.65 KPa, respectively. Liver stiffness values had a positive correlation with transient elastography (r = 0.57; p < 0.001). The area under the receiver operating characteristics (AUROC) was 0.899 for ≥ F2 (moderate fibrosis), 0.900 for ≥ F3 (severe fibrosis), and 0.899 for cirrhosis. 2D-SWE has excellent accuracy in assessing liver fibrosis in patients with chronic hepatitis C and an excellent correlation with transient elastography. Full article
(This article belongs to the Special Issue Elastography)
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Open AccessArticle
Biomarkers of Muscle Metabolism in Peripheral Artery Disease: A Dynamic NIRS-Assisted Study to Detect Adaptations Following Revascularization and Exercise Training
Diagnostics 2020, 10(5), 312; https://doi.org/10.3390/diagnostics10050312 - 16 May 2020
Viewed by 545
Abstract
We assessed whether muscle metabolism biomarkers (MMb) identified by near-infrared spectroscopy (NIRS) are valid for determining adaptations following revascularization or exercise training in peripheral artery disease (PAD). Eighteen patients (males n = 13; 69 ± 7 years) were randomized to receive revascularization (Rev [...] Read more.
We assessed whether muscle metabolism biomarkers (MMb) identified by near-infrared spectroscopy (NIRS) are valid for determining adaptations following revascularization or exercise training in peripheral artery disease (PAD). Eighteen patients (males n = 13; 69 ± 7 years) were randomized to receive revascularization (Rev = 6) or pain-free home-based exercise (Ex = 12). MMb were safely collected via a NIRS-assisted treadmill test as area-under-curve for the spectra of oxygenated (-oxy), deoxygenated (-deoxy), differential (-diff) and total (-tot) hemoglobin traces. MMb, ankle–brachial index (ABI), pain-free (PFWD) and 6-min (6MWD) walking distances were assessed at baseline and after four months. MMb were correlated at baseline with ABI (MMb-oxy r = 0.46) and 6MWD (MMb-tot r = 0.51). After treatments, MMb-oxy showed an expected increase, which was more relevant for Rev group than the Ex (56% vs. 20%), with trends towards normalization for the other MMb. These changes were significantly correlated with variations in ABI (MMb-oxy r = 0.71; p = 0.002) and 6MWD (MMb-tot r = 0.58; p = 0.003). The MMb-diff in Rev group and MMb-deoxy in Ex group at baseline predicted clinical outcomes being correlated with PFWD improvements after 4-month (r = −0.94; p = 0.005 and r = −0.57; p = 0.05, respectively). A noninvasive NIRS-based test, feasible in a clinical setting, identified muscle metabolism biomarkers in PAD. The novel MMb were associated with validated outcome measures, selectively modified after different interventions and able to predict long-term functional improvements after surgery or exercise training. Full article
(This article belongs to the collection Biomarkers in Medicine)
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Open AccessReview
Urinary Extracellular Vesicles as Biomarkers of Kidney Disease: From Diagnostics to Therapeutics
Diagnostics 2020, 10(5), 311; https://doi.org/10.3390/diagnostics10050311 - 16 May 2020
Viewed by 659
Abstract
Cell-derived extracellular vesicles (EVs) can be isolated from various body fluids, including urine. Urinary EVs have gained important recognition as potential diagnostic biomarkers in renal disease since their cargo includes nucleic acids, proteins, and other cellular components, which likely mirror the physiological and [...] Read more.
Cell-derived extracellular vesicles (EVs) can be isolated from various body fluids, including urine. Urinary EVs have gained important recognition as potential diagnostic biomarkers in renal disease since their cargo includes nucleic acids, proteins, and other cellular components, which likely mirror the physiological and possibly pathophysiological state of cells along the nephron. Accumulating evidence highlights the feasibility of using EVs as biomarkers for diagnostic, prognostic, and therapeutic purposes in several forms of renal disease, such as acute kidney injury, glomerulonephritis, and renal transplantation. Additionally, exogenous delivery of EVs released in vitro by cells in culture may have salutary benefits for renal diseases. In this review, we introduce recent studies that attempt to identify urinary EVs as candidate biomarkers for human kidney diseases and consider their potential implication as a therapeutic option in key kidney diseases. Full article
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