scholarly journals Integration of in vitro allergy test results and ratio analysis for the diagnosis and treatment of allergic patients (INTEGRA)

2021 ◽  
Vol 11 (7) ◽  
Author(s):  
Mariona Pascal ◽  
Carmen Moreno ◽  
Ignacio Dávila ◽  
Ana I. Tabar ◽  
Joan Bartra ◽  
...  
Keyword(s):  
Diagnosis And Treatment ◽  
Ratio Analysis ◽  
Test Results ◽  
Allergy Test

scholarly journals Positivity Rates of in Vitro Inhalant/ Respiratory and Food Allergy Tests in the Northern Midwestern United States

2018 ◽  
Vol 97 (9) ◽  
pp. 296-322 ◽  
Author(s):  
Michael S. Benninger ◽  
Thomas Daly ◽  
Kevin Graffmiller
Keyword(s):  
United States ◽  
Cleveland Clinic ◽  
The United States ◽  
Test Results ◽  
Dust Mites ◽  
Upper Midwest ◽  
Allergy Test ◽  
Wide Variability ◽  
Very High

Rates of allergy-test positivity vary by country and by regions within countries. Several studies have looked at allergy test results to determine the most common allergens. Many of these studies have been based on surveys or on studies of small numbers of tests. Positivity rates for allergy tests are poorly defined in the northern midwestern region of the United States. We conducted a study to identify the rates of positive allergy tests for both inhalant/respiratory allergens and food allergens in the upper Midwest. We extracted from our laboratory database the results of all test samples sent for one of eight allergen panels that had been analyzed between Sept. 1, 2014, and Sept. 1, 2015. All testing was performed at The Cleveland Clinic with the Phadia ImmunoCAP system. The percentage of positive tests, the distribution of the most frequently positive tests, and the class of in vitro responses were identified. A total of 148,628 test results for 63 different allergens were identified. Of the 125,190 tests for inhalant/respiratory allergens, the most frequently positive were dog dander (24% of tests), cat dander (23%), dust mites (23% for both Dermatophagoides pteronyssinus and Dermatophagoides farinae), and June grass (21%). Of the 23,438 food tests, the most frequently positive test results were for milk (18%), peanut (17%), wheat (16%), and egg white (15%). Most of the results fell into classes 1 through 3, although there was still a notable number of very high responses (class 5 and 6). These findings suggest that there is wide variability in the positivity of in vitro allergy tests and that the likelihood of a positive result in screening panels can be estimated. Evaluating such rates will help identify the most and least common allergens and will help to cost-effectively refine allergy screening panels.

The Association of Allergic Sensitization with Radiographic Sinus Opacification

2017 ◽  
Vol 31 (1) ◽  
pp. 12-15 ◽  
Author(s):  
Christopher D. Brook ◽  
Jacob E. Kuperstock ◽  
Samuel J. Rubin ◽  
Matthew W. Ryan ◽  
Michael P. Platt
Keyword(s):  
Linear Regression ◽  
Nasal Polyps ◽  
Immunoglobulin E ◽  
Allergic Sensitization ◽  
Test Results ◽  
Allergy Test ◽  
History Of ◽  
Male Sex ◽  
Specific Allergen

Background The relationship between allergic sensitization and radiographic sinus inflammation remains unclear. Objectives To determine whether specific allergen sensitization is correlated with sinonasal radiographic opacification. Methods Patients with chronic sinonasal symptoms were selected and included if they had allergy testing and a computed tomography (CT) of the paranasal sinuses. Data regarding demographic characteristics, in vitro allergy test results, and comorbidities were collected. CTs were reviewed, and an overall Lund-Mackay score (LMS) was calculated for each patient. A two-sample t-test was used to compare mean LMS between patients who were sensitized and patients who were not sensitized. A multiple linear regression model was used to determine whether a relationship existed among LMS and allergy results, asthma, nasal polyps, immunoglobulin E (IgE) level, medication usage, in-season versus out-of-season CTs, age, and sex. Significance was determined at an alpha level of 0.05. Results There were 437 patients included, of whom, 251 had positive specific allergen test results and 186 had negative test results. A total of 282 patients had allergic rhinitis symptoms without a documented diagnosis of sinusitis, and 155 carried a diagnosis of chronic rhinosinusitis. The mean LMS did not differ between patients who were sensitized and patients who were not sensitized (5.56 versus 5.28; p = 0.61). Linear regression demonstrated an increase in LMS in patients with asthma (p = 0.02), male sex (p < 0.01), elevated IgE (p < 0.01), a history of anaphylaxis (p = 0.03), and nasal polyps (p < 0.01). There was a statistically significant decrease in LMS in patients with an in-season CT (p = 0.02). Conclusions Patients with a positive specific in vitro allergen test result did not have higher overall rates of radiographic sinus inflammation. Asthma, male sex, polyps, elevated IgE, and a history of anaphylaxis were associated with higher LMS.

scholarly journals Advancing Healthcare Outcomes for Sickle Cell Disease in Nigeria Using Mobile Health Tools

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 2173-2173
Author(s):  
Arwa Fraiwan ◽  
Muhammad Noman Hasan ◽  
Ran An ◽  
Amy J. Rezac ◽  
Nicholas J. Kocmich ◽  
...  
Keyword(s):  
Sickle Cell Disease ◽  
Sickle Cell ◽  
Mobile Health ◽  
Sub Saharan Africa ◽  
Diagnosis And Treatment ◽  
Test Results ◽  
Cell Disease ◽  
The World ◽  
Equity Ownership ◽  
Sub Saharan

Nigeria leads the world in the number of cases of sickle cell disease (SCD). An estimated 150,000 babies are born annually in Nigeria with SCD, a heredity disorder, and 70-90% die before age 5. Only a small portion of affected infants and children in sub Saharan Africa (SSA) reach adolescence. Over 650 children die per day in sub-Saharan Africa from SCD. These dismal statistics are in sharp contrast to outcomes in high-income countries (HICs) where more than 90% of SCD patients reach adulthood. The World Health Organization (WHO) estimates that 70% of deaths could be prevented with a low cost diagnostic and treatment plan. Meaningful preventive care and treatment cannot be implemented without a structured plan for early diagnosis and patient tracking.Early diagnosis requires improved access to parents and guardians of children with SCD, and gaining this access remains a challenge in most of SSA. In 2015, Nigeria's Kano state government, with support from foreign partners, established a community-based program for newborn registration. This platform provides unique access to newborn babies in one of Nigeria's most populous cities, but still lacks a functioning patient testing, tracking, and monitoring system, which we plan to address in our ongoing study. This study will introduce mobile health in a low-income country with low literacy rate and hopefully accustom that segment of the population to more varied mobile health applications that will ultimately improve their health in the long run. Our current operational platform in Kano, Nigeria provides access to a large population with a high prevalence of SCD. We have previously completed pilot testing of 315 subjects for SCD using our microchip electrophoresis test. We are planning to test up to 4,500 additional subjects less than 5 years of age at Murtala Muhammed Specialist Hospital. The hospital staff includes 97 physicians and 415 nurses and outpatient clinics serve about 30,000 patients monthly. The maternity department has a 200-bed capacity and the antenatal clinic performs about 1,000 deliveries and serves an average of 3,000 mothers monthly. Enrollment is planned to start on September 15, 2019 and medical staff are currently being trained to run the tests. Our study is registered in the United States National Library of Medicine's ClinicalTrials.gov (Identifier: NCT03948516). Our technology is uniquely paired with an automatic reader and an Electronic Medical Record (EMR) and patient management solution to record POC test results, register new cases, and track patients for follow-up (Fig. 1). The reader enables automated interpretation of test results, local and remote test data storage, and includes geolocation (Global Positioning System) (Fig. 2). The system will generate reports for all cases of SCD, track hospital visits, appointments, lab tests, and will have mobile and dashboard applications for tracking patients and samples. The application will be installed on mobile devices provided to users. The proposed system will be compliant with the existing privacy standards to handle medical data (e.g., HIPAA in the US and GDPR in the EU). All communications between the parties will be secured via end-to-end encryption as a safeguard. We anticipate that our project will increase the rates of screening, diagnosis and timely treatment of SCD in Kano State of Nigeria. The project's broader impact will likely be the ability to track and monitor screening, disease detection, diagnosis and treatment, which can be scaled up to the whole nation of Nigeria, then to sub-Saharan Africa. The data obtained and analyzed will be the first of their kind and will be used to inform the design of programs to improve access to, and availability of, effective care for this underserved populations. The importance of increased access to diagnosis and treatment should not be underestimated - it is crucial for realizing effective management of people with SCD. The impact can be enhanced by complementing diagnosis and patient tracking with education for the families so they can provide or seek the necessary preventative treatment. Identification of the location of the patients in need would help identify the areas where family, parent, caregiver education should be provided. Disclosures Fraiwan: Hemex Health, Inc.: Equity Ownership, Patents & Royalties. Hasan:Hemex Health, Inc.: Equity Ownership, Patents & Royalties. An:Hemex Health, Inc.: Patents & Royalties. Thota:Hemex Health, Inc.: Employment. Gurkan:Hemex Health, Inc.: Consultancy, Employment, Equity Ownership, Patents & Royalties, Research Funding.

GNG5 is a novel oncogene associated with cell migration, proliferation, and poor prognosis in glioma

2021 ◽  
Author(s):  
Wang Zhang ◽  
Zhendong Liu ◽  
Binchao Liu ◽  
Miaomiao Jiang ◽  
Shi Yan ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Clinical Data ◽  
Poor Prognosis ◽  
Glioma Cells ◽  
Diagnosis And Treatment ◽  
And Migration ◽  
The Relationship ◽  
Proliferation And Migration

Abstract Background: Although many biomarkers have been reported for detecting glioma, the prognosis for the disease remains poor, and therefore, new biomarkers need to be identified. GNG5, which is part of the G-protein family, has been associated with different malignant tumors, though the role of GNG5 in glioma has not been studied. Therefore, we aimed to identify the relationship between GNG5 and glioma prognosis and identify a new biomarker for the diagnosis and treatment of gliomas.Methods: We used data on more than a thousand gliomas from multiple databases and clinical data to determine the expression of GNG5 in glioma. Based on clinical data and CGGA database, we identified the correlation between GNG5 and multiple molecular and clinical features and prognosis using various analytical methods. Co-expression analysis and GSEA were performed to detect GNG5-related genes in glioma and possible signaling pathways involved. ESTIMATE, ssGSEA, and TIMER were used to detect the relationship between GNG5 and the immune microenvironment. Functional experiments were performed to explore the function of GNG5 in glioma cells.Results: GNG5 is highly expressed in gliomas, and its expression level is positively correlated with pathological grade, histological type, age, and tumor recurrence and negatively correlated with isocitrate dehydrogenase mutation, 1p/19 co-deletion, and chemotherapy. Moreover, GNG5 as an independent risk factor was negatively correlated with the overall survival time. GSEA revealed the potential signaling pathways involved in GNG5 function in gliomas, including cell adhesion molecules signaling pathway. The ssGSEA, ESTIMATE, and TIMER based analysis indicated a correlation between GNG5 expression and various immune cells in glioma. In vivo and in vitro experiments showed that GNG5 could participate in glioma cell proliferation and migration.Conclusions: Based on the large data platform and the use of different databases to corroborate results obtained using various datasets, as well as in vitro and in vivo experiments, our study reveals for the first time that GNG5, as an oncogene, is overexpressed in gliomas and can inhibit the proliferation and migration of glioma cells and lead to poor prognosis of patients. Thus, GNG5 is a potential novel biomarker for the clinical diagnosis and treatment of gliomas.

Transformer + GAN based Traditional Chinese Medicine inpatient prescription recommendation (Preprint)

2021 ◽  
Author(s):  
Hong Zhang
Keyword(s):  
Decision Making ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Electronic Medical Records ◽  
Clinical Diagnosis ◽  
Medical Records ◽  
Training Data ◽  
Diagnosis And Treatment ◽  
Test Results ◽  
Treatment Scheme

BACKGROUND Clinical diagnosis and treatment decision making support is at the core of medical artificial intelligent research, in which Traditional Chinese Medicine (TCM) decision making is an important part. Traditional Chinese Medicine is a traditional medical system originated from China, of which the main clinical model is to conduct individualized diagnosis and treatment by relying on the four-diagnosis information. One of the key tasks of the TCM artificial intelligence research is to develop techniques and methods of clinical prescription decision making which takes all the relevant information of a patient as input, and produces a diagnosis and treatment scheme as output. Given the complexity of TCM clinical diagnosis and treatment schemes, decision making support of clinical diagnosis and treatment schemes remains as a research challenge for lacking of an effective solution. Fortunately, as the volume of the massive clinical data in the form of electronic medical records increases rapidly, it becomes possible for the computer to produce personalized diagnosis and treatment scheme recommendation through machine learning on the basis of the clinical big data. OBJECTIVE The objective of this research is to develop a real-time diagnosis and treatment scheme recommendation model for TCM inpatients. This is accomplished by using historical clinical medical records as training data to train a Transformer network. Furthermore, to alleviate the issue of overfitting, a Generative Adversarial Network is used to generate noise-added samples from the original training data. These noise-added samples along with the original samples form the complete train data set. METHODS valid information, such as the patient’s current sickness situation, medicines taken, nursing care given, vital signs, examinations and test results, is extracted from the patient’s electronic medical records, then the obtained information is sorted chronically, to produce a sequence of data of each patient. These time-sequence data is then used as input to the Transformer network. The output of the network would be the prescription information a physician would give. Overfitting is a common problem in machine learning, and becomes especially server when the network is complex with insufficient training data. In this research, a Generative Adversarial Network, is used to double the number of training samples by producing noise-added samples from the original samples. This, to a great extent, lessens the overfitting problem. RESULTS A total of 21,295 copies of inpatient electronic medical records from Guang’anmen traditional Chinese medicine hospital was used in this research. These records were created between January 2017 and December 2018, covering a total of 6352 kinds of medicines. These medicines were sorted into 829 types of first category medicines based on the class relationships among medicines. As shown by the test results, the performance of a fully trained Transformer model can have an average precision rate of 80.58%，and an average recall rate of 68.49%. CONCLUSIONS As shown by the preliminary test results, the Transformer-based TCM prescription recommendation model outperforms the existing conventional methods. The extra training samples generated by the GAN network helps to overcome the overfitting issue, leading a further improved recall rate and precision rate.

scholarly journals In Vitro Corrosion and Cell Response of Hydroxyapatite Coated Mg Matrix in Situ Composites for Biodegradable Material Applications

Materials ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 3474 ◽  
Author(s):  
Cao ◽  
Le ◽  
Pham ◽  
Nguyen ◽  
Hiromoto ◽  
...  
Keyword(s):  
Cell Culture ◽  
Corrosion Resistance ◽  
Solution Treatment ◽  
Potential Candidate ◽  
Test Results ◽  
Biodegradable Implant ◽  
Culture Test ◽  
Sintering Time ◽  
Cell Culture Test

In this study, hydroxyapatite (HAp) coated Mg matrix composites were fabricated for biodegradable implant applications. Spark plasma sintering was employed to fabricate the Mg-10 wt% ZnO composite substrates. HAp was coated on the surface of the sintered composites and pure Mg by a chemical solution treatment. SEM and optical micrographs of coated samples showed that HAp grew homogeneously and formed a layer on the entire surface of both pure sintered Mg and Mg composites. The immersion and polarization test results demonstrated that the HAp coating significantly improved the corrosion resistance of the sintered composites. While the HAp coating layer is not effective in the improvement of the pure Mg substrate, cell culture test results revealed that the HAp coating improved cell adhesion and proliferation on the composites effectively through 72 h, while no cell could survive on the uncoated composites after 72 h. In addition, the corrosion tests and cell culture test results indicated that the composite with longer sintering time has better corrosion resistance and cell viability than those of the composite with shorter sintering time. The findings suggested that the HAp-coated Mg-10 wt% ZnO-2.5 h + 10 min composite is a high-potential candidate for biodegradable implant applications.

scholarly journals Leveraging Extraction Testing to Predict Patient Exposure to Polymeric Medical Device Leachables Using Physics-based Models

2020 ◽  
Vol 178 (1) ◽  
pp. 201-211
Author(s):  
Paul Turner ◽  
Robert M Elder ◽  
Keaton Nahan ◽  
Anne Talley ◽  
Saloni Shah ◽  
...  
Keyword(s):  
Medical Device ◽  
Chemical Constituents ◽  
A Priori ◽  
Exposure Dose ◽  
Test Results ◽  
Animal Testing ◽  
Patient Exposure ◽  
Extraction Test ◽  
Routine Basis

Abstract Toxicological risk assessment approaches are increasingly being used in lieu of animal testing to address toxicological concerns associated with release of chemical constituents from polymeric medical device components. These approaches currently rely on in vitro extraction testing in aggressive environments to estimate patient exposure to these constituents, but the clinical relevance of the test results is often ambiguous. Physics-based mass transport models can provide a framework to interpret extraction test results to provide more clinically relevant exposure estimates. However, the models require system-specific material properties, such as diffusion (D) and partition coefficients (K), to be established a priori for the extraction conditions. Using systems comprised high-density polyethylene and 4 different additives, we demonstrate that these properties can be quantified through standard extraction testing in hexane and isopropyl alcohol. The values of D and K derived in this manner were consistent with theoretical predictions for these quantities. Based on these results, we discuss both the challenges and benefits to leveraging extraction data to parameterize physics-based exposure models. Our observations suggest that clinically relevant, yet still conservative, exposure dose estimates provided by applying this approach to a single extraction measurement can be more than 100 times lower than would be measured under typical aggressive extraction conditions. However, to apply the framework on a routine basis, limiting values of D and K must be established for device-relevant systems either through the aggregation and analysis of more extensive extraction test data and/or advancements in theoretical and computational modeling efforts to predict these quantities.

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