scholarly journals Point-of-care serodiagnostic test for early-stage Lyme disease using a multiplexed paper-based immunoassay and machine learning

2019 ◽  
Author(s):  
Hyou-Arm Joung ◽  
Zachary S. Ballard ◽  
Jing Wu ◽  
Derek K. Tseng ◽  
Hailemariam Teshome ◽  
...  
Keyword(s):  
Lyme Disease ◽  
Early Stage ◽  
Point Of Care ◽  
Area Under The Curve ◽  
Diagnostic Algorithm ◽  
Cost Effective ◽  
Optimal Subset ◽  
Antigen Peptide ◽  
Vector Borne ◽  
Threshold Tuning

ABSTRACTCaused by the tick-borne spirochete, Borrelia burgdorferi, Lyme disease (LD) is the most common vector-borne infectious disease in North America and Europe. Though timely diagnosis and treatment are effective in preventing disease progression, current tests are insensitive in early-stage LD, with a sensitivity <50%. Additionally, the serological testing currently recommended by the US Center for Disease Control has high costs (>$400/test) and extended sample-to-answer timelines (>24 hours). To address these challenges, we created a cost-effective and rapid point-of-care (POC) test for early-stage LD that assays for antibodies specific to seven Borrelia antigens and a synthetic peptide in a paper-based multiplexed vertical flow assay (xVFA). We trained a deep learning-based diagnostic algorithm to select an optimal subset of antigen/peptide targets, and then blindly-tested our xVFA using human samples (N(+) = 42, N(−)= 54), achieving an area-under-the-curve (AUC), sensitivity, and specificity of 0.950, 90.5%, and 87.0% respectively, outperforming previous LD POC tests. With batch-specific standardization and threshold tuning, the specificity of our blind-testing performance improved to 96.3%, with an AUC and sensitivity of 0.963 and 85.7%, respectively.

scholarly journals Point-of-Care Serodiagnostic Test for Early-Stage Lyme Disease Using a Multiplexed Paper-Based Immunoassay and Machine Learning

ACS Nano ◽  
2019 ◽  
Vol 14 (1) ◽  
pp. 229-240 ◽  
Author(s):  
Hyou-Arm Joung ◽  
Zachary S. Ballard ◽  
Jing Wu ◽  
Derek K. Tseng ◽  
Hailemariam Teshome ◽  
...  
Keyword(s):  
Machine Learning ◽  
Lyme Disease ◽  
Early Stage ◽  
Point Of Care

scholarly journals LYME BORRELIOSIS: CLINICAL MANIFESTATIONS AND ADVANCES IN DIAGNOSIS AND CONTROL

2020 ◽  
Vol 8 (6) ◽  
pp. 721-729
Author(s):  
Sandip Kumar Khurana ◽  
◽  
Anju Sehrawat ◽  
Ruchi Tiwari ◽  
Khan Sharun ◽  
...  
Keyword(s):  
Lyme Disease ◽  
Early Stage ◽  
Erythema Migrans ◽  
Clinical Manifestations ◽  
Neurological Involvement ◽  
Vector Borne Diseases ◽  
Clinical Syndromes ◽  
Clinical Presentations ◽  
Vector Borne ◽  
And Control

Lyme disease or borreliosis is presumed one of the most significant vector-borne diseases globally. The disease is re-emerging in numerous parts of world. It has expanded dramatically in newer areas in recent decades. Lyme disease is caused by Borrelia burgdorferi yet additionally by other borrelial species, B. afzelii and B. garini which cause diverse clinical syndromes. Spatial distribution and clinical presentations differ depending on the causative species. Clinical manifestations of Lyme disease can be delineated in three stages. The first stage is presented in the form of erythema migrans at the site of tick bite. Early dispersed stage can lead to multiple lesions of erythema migrans, neuroborreliosis, lymphocytoma, arthritis or carditis. The manifestation at later stage shows acordermatitis chronica atrophicans, arthritis and neurological involvement. Diagnosis is challenging owing the several clinical presentations and could require multiple tests. The antibiotics that are currently under use, help in the clearance of bacteria from the affected host and stop further spread of the disease. Although several antibiotics are being used for Lyme disease, doxycycline is the widely used antimicrobial in early stage of the disease. Several attempts have been made to develop a vaccine against Lyme disease, however, none of them have been successfully marketed. The present review discusses clinical manifestations, and advances in diagnosis and control of Lyme disease.

scholarly journals Revisiting the Lyme Disease Serodiagnostic Algorithm: the Momentum Gathers

2018 ◽  
Vol 56 (8) ◽  
Author(s):  
Adriana R. Marques
Keyword(s):  
Lyme Disease ◽  
Point Of Care ◽  
High Specificity ◽  
The United States ◽  
Immunofluorescence Assay ◽  
Rapid Diagnostics ◽  
Content Type ◽  
Vector Borne ◽  
Second Tier ◽  
Low Sensitivity

ABSTRACT Lyme disease is a tick-borne illness caused by Borreliella (Borrelia) burgdorferi, and it is the most common vector-borne disease in the United States, with an estimated incidence of 300,000 cases per year. The currently recommended approach for laboratory support of the diagnosis of Lyme disease is a standard two-tiered (STT) algorithm comprised of an enzyme-linked immunoassay (EIA) or immunofluorescence assay (IFA), followed by Western blotting (WB). The STT algorithm has low sensitivity in early infection, and there are drawbacks associated with the WB use in practice. Modified two-tiered (MTT) algorithms have been shown to improve the sensitivity of the testing in early disease while maintaining high specificity. In this issue of the Journal of Clinical Microbiology, A. Pegalajar-Jurado et al. (J Clin Microbiol 56:e01943-17, 2018, https://doi.org/10.1128/JCM.01943-17) report the results of their evaluation of the Liaison VlsE CLIA, the Captia B. burgdorferi IgG/IgM EIA, and the C6 B. burgdorferi (Lyme) EIA as MTT algorithms compared with results with the STT algorithm using the same tests as the first-tier test and the ViraStripe IgM and IgG WBs as the second-tier test. The results showed that all MTT algorithms had higher sensitivities than STT algorithms and were highly specific. These results showed that MTT approaches are a valid alternative to the currently recommended STT algorithm for serodiagnosis of Lyme disease, opening the door for the development of rapid diagnostics and point-of-care testing that can provide diagnostic information during the initial patient visit.

Review of Various Tasks Performed in the Preprocessing Phase of a Diabetic Retinopathy Diagnosis System

2020 ◽  
Vol 16 (4) ◽  
pp. 397-426
Author(s):  
Muhammad Nadeem Ashraf ◽  
Muhammad Hussain ◽  
Zulfiqar Habib
Keyword(s):  
Diabetic Retinopathy ◽  
Blood Vessels ◽  
Early Stage ◽  
Spherical Shape ◽  
Cost Effective ◽  
Lesion Detection ◽  
Diabetic Patients ◽  
Cad System ◽  
Non Invasive ◽  
Optic Discs

Diabetic Retinopathy (DR) is a major cause of blindness in diabetic patients. The increasing population of diabetic patients and difficulty to diagnose it at an early stage are limiting the screening capabilities of manual diagnosis by ophthalmologists. Color fundus images are widely used to detect DR lesions due to their comfortable, cost-effective and non-invasive acquisition procedure. Computer Aided Diagnosis (CAD) of DR based on these images can assist ophthalmologists and help in saving many sight years of diabetic patients. In a CAD system, preprocessing is a crucial phase, which significantly affects its performance. Commonly used preprocessing operations are the enhancement of poor contrast, balancing the illumination imbalance due to the spherical shape of a retina, noise reduction, image resizing to support multi-resolution, color normalization, extraction of a field of view (FOV), etc. Also, the presence of blood vessels and optic discs makes the lesion detection more challenging because these two artifacts exhibit specific attributes, which are similar to those of DR lesions. Preprocessing operations can be broadly divided into three categories: 1) fixing the native defects, 2) segmentation of blood vessels, and 3) localization and segmentation of optic discs. This paper presents a review of the state-of-the-art preprocessing techniques related to three categories of operations, highlighting their significant aspects and limitations. The survey is concluded with the most effective preprocessing methods, which have been shown to improve the accuracy and efficiency of the CAD systems.

scholarly journals Aptamer-Based Diagnostic Systems for the Rapid Screening of TB at the Point-of-Care

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1352
Author(s):  
Darius Riziki Martin ◽  
Nicole Remaliah Sibuyi ◽  
Phumuzile Dube ◽  
Adewale Oluwaseun Fadaka ◽  
Ruben Cloete ◽  
...  
Keyword(s):  
Low Income ◽  
Point Of Care ◽  
Health Care Systems ◽  
Cost Effective ◽  
Rapid Screening ◽  
Low Income Countries ◽  
Sputum Smear ◽  
Diagnostic Systems ◽  
Molecular Tests ◽  
Rapid Tests

The transmission of Tuberculosis (TB) is very rapid and the burden it places on health care systems is felt globally. The effective management and prevention of this disease requires that it is detected early. Current TB diagnostic approaches, such as the culture, sputum smear, skin tuberculin, and molecular tests are time-consuming, and some are unaffordable for low-income countries. Rapid tests for disease biomarker detection are mostly based on immunological assays that use antibodies which are costly to produce, have low sensitivity and stability. Aptamers can replace antibodies in these diagnostic tests for the development of new rapid tests that are more cost effective; more stable at high temperatures and therefore have a better shelf life; do not have batch-to-batch variations, and thus more consistently bind to a specific target with similar or higher specificity and selectivity and are therefore more reliable. Advancements in TB research, in particular the application of proteomics to identify TB specific biomarkers, led to the identification of a number of biomarker proteins, that can be used to develop aptamer-based diagnostic assays able to screen individuals at the point-of-care (POC) more efficiently in resource-limited settings.

scholarly journals Longitudinal remotely mentored self-performed lung ultrasound surveillance of paucisymptomatic Covid-19 patients at risk of disease progression

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Andrew W. Kirkpatrick ◽  
Jessica L. McKee ◽  
John M. Conly
Keyword(s):  
At Risk ◽  
Lung Ultrasound ◽  
Point Of Care ◽  
Human Life ◽  
Vital Signs ◽  
Home Monitoring ◽  
Cost Effective ◽  
Care Providers ◽  
Vital Signs Monitoring ◽  
Ultrasound Probes

AbstractCOVID-19 has impacted human life globally and threatens to overwhelm health-care resources. Infection rates are rapidly rising almost everywhere, and new approaches are required to both prevent transmission, but to also monitor and rescue infected and at-risk patients from severe complications. Point-of-care lung ultrasound has received intense attention as a cost-effective technology that can aid early diagnosis, triage, and longitudinal follow-up of lung health. Detecting pleural abnormalities in previously healthy lungs reveal the beginning of lung inflammation eventually requiring mechanical ventilation with sensitivities superior to chest radiographs or oxygen saturation monitoring. Using a paradigm first developed for space-medicine known as Remotely Telementored Self-Performed Ultrasound (RTSPUS), motivated patients with portable smartphone support ultrasound probes can be guided completely remotely by a remote lung imaging expert to longitudinally follow the health of their own lungs. Ultrasound probes can be couriered or even delivered by drone and can be easily sterilized or dedicated to one or a commonly exposed cohort of individuals. Using medical outreach supported by remote vital signs monitoring and lung ultrasound health surveillance would allow clinicians to follow and virtually lay hands upon many at-risk paucisymptomatic patients. Our initial experiences with such patients are presented, and we believe present a paradigm for an evolution in rich home-monitoring of the many patients expected to become infected and who threaten to overwhelm resources if they must all be assessed in person by at-risk care providers.

scholarly journals A MYC-Driven Plasma Polyamine Signature for Early Detection of Ovarian Cancer

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 913
Author(s):  
Johannes Fahrmann ◽  
Ehsan Irajizad ◽  
Makoto Kobayashi ◽  
Jody Vykoukal ◽  
Jennifer Dennison ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Early Stage ◽  
Area Under The Curve ◽  
Polyamine Metabolism ◽  
Healthy Controls ◽  
Test Set ◽  
Exact Test ◽  
Oncogenic Driver ◽  
Characteristic Area ◽  
Validation Set

MYC is an oncogenic driver in the pathogenesis of ovarian cancer. We previously demonstrated that MYC regulates polyamine metabolism in triple-negative breast cancer (TNBC) and that a plasma polyamine signature is associated with TNBC development and progression. We hypothesized that a similar plasma polyamine signature may associate with ovarian cancer (OvCa) development. Using mass spectrometry, four polyamines were quantified in plasma from 116 OvCa cases and 143 controls (71 healthy controls + 72 subjects with benign pelvic masses) (Test Set). Findings were validated in an independent plasma set from 61 early-stage OvCa cases and 71 healthy controls (Validation Set). Complementarity of polyamines with CA125 was also evaluated. Receiver operating characteristic area under the curve (AUC) of individual polyamines for distinguishing cases from healthy controls ranged from 0.74–0.88. A polyamine signature consisting of diacetylspermine + N-(3-acetamidopropyl)pyrrolidin-2-one in combination with CA125 developed in the Test Set yielded improvement in sensitivity at >99% specificity relative to CA125 alone (73.7% vs 62.2%; McNemar exact test 2-sided P: 0.019) in the validation set and captured 30.4% of cases that were missed with CA125 alone. Our findings reveal a MYC-driven plasma polyamine signature associated with OvCa that complemented CA125 in detecting early-stage ovarian cancer.

scholarly journals Fabry Cardiomyopathy: Current Practice and Future Directions

Cells ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1532
Author(s):  
Jeffrey Yim ◽  
Olivia Yau ◽  
Darwin F. Yeung ◽  
Teresa S. M. Tsang
Keyword(s):  
Fabry Disease ◽  
Early Stage ◽  
Point Of Care ◽  
Left Ventricular ◽  
The Body ◽  
Cardiac Biomarkers ◽  
Dried Blood Spot ◽  
Point Of Care Ultrasound ◽  
Enzyme Replacement ◽  
Blood Spot

Fabry disease (FD) is an X-linked lysosomal storage disorder caused by mutations in the galactosidase A (GLA) gene that result in deficient galactosidase A enzyme and subsequent accumulation of glycosphingolipids throughout the body. The result is a multi-system disorder characterized by cutaneous, corneal, cardiac, renal, and neurological manifestations. Increased left ventricular wall thickness represents the predominant cardiac manifestation of FD. As the disease progresses, patients may develop arrhythmias, advanced conduction abnormalities, and heart failure. Cardiac biomarkers, point-of-care dried blood spot testing, and advanced imaging modalities including echocardiography with strain imaging and magnetic resonance imaging (MRI) with T1 mapping now allow us to detect Fabry cardiomyopathy much more effectively than in the past. While enzyme replacement therapy (ERT) has been the mainstay of treatment, several promising therapies are now in development, making early diagnosis of FD even more crucial. Ongoing initiatives involving artificial intelligence (AI)-empowered interpretation of echocardiographic images, point-of-care dried blood spot testing in the echocardiography laboratory, and widespread dissemination of point-of-care ultrasound devices to community practices to promote screening may lead to more timely diagnosis of FD. Fabry disease should no longer be considered a rare, untreatable disease, but one that can be effectively identified and treated at an early stage before the development of irreversible end-organ damage.

scholarly journals Learning health systems in primary care: a systematic scoping review

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Danielle M. Nash ◽  
Zohra Bhimani ◽  
Jennifer Rayner ◽  
Merrick Zwarenstein
Keyword(s):  
Primary Care ◽  
Quality Improvement ◽  
Health Systems ◽  
Scoping Review ◽  
Early Stage ◽  
Point Of Care ◽  
The United States ◽  
Stage Of Development ◽  
Integrated Health ◽  
Google Search

Abstract Background Learning health systems have been gaining traction over the past decade. The purpose of this study was to understand the spread of learning health systems in primary care, including where they have been implemented, how they are operating, and potential challenges and solutions. Methods We completed a scoping review by systematically searching OVID Medline®, Embase®, IEEE Xplore®, and reviewing specific journals from 2007 to 2020. We also completed a Google search to identify gray literature. Results We reviewed 1924 articles through our database search and 51 articles from other sources, from which we identified 21 unique learning health systems based on 62 data sources. Only one of these learning health systems was implemented exclusively in a primary care setting, where all others were integrated health systems or networks that also included other care settings. Eighteen of the 21 were in the United States. Examples of how these learning health systems were being used included real-time clinical surveillance, quality improvement initiatives, pragmatic trials at the point of care, and decision support. Many challenges and potential solutions were identified regarding data, sustainability, promoting a learning culture, prioritization processes, involvement of community, and balancing quality improvement versus research. Conclusions We identified 21 learning health systems, which all appear at an early stage of development, and only one was primary care only. We summarized and provided examples of integrated health systems and data networks that can be considered early models in the growing global movement to advance learning health systems in primary care.

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