Medical Indications Research Articles

Impacts of pharmacist-led multi-faceted antimicrobial stewardship on antibiotic use and clinical outcomes in urology department of a tertiary hospital in Guangzhou, China: an interrupted time-series study

Research on the effectiveness of pharmacist-led antimicrobial stewardship programmes (ASPs) in the urology department is limited. To evaluate the impact of pharmacist-led multi-faceted ASPs on antibiotic use and clinical outcomes. A prescription review of inpatients receiving one or more antibiotics in the urology department of a large teaching hospital in Guangzhou, China, was conducted from April 2019 to March 2023. The pharmacist-led multi-faceted ASP intervention included guideline development, training, medication consultation, review of medical orders, indicator monitoring, and consultation. The primary outcome was antibiotic consumption. The data were analysed using interrupted time-series (ITS) analysis. Following the implementation of ASPs, an immediate decrease was observed in total antibiotic consumption, antibiotic use rate, second-generation cephalosporins, third-generation cephalosporins, fluoroquinolones, and WHO Watch category antibiotics. No differences were observed in mortality rate before and after the intervention, and no significant short- or long-term effects were found on length of hospital stay (LOS) using ITS. However, there was a significant short-term effect on average antibiotic cost. The implementation of pharmacist-led multi-faceted ASPs had positive impacts on reducing antimicrobial consumption without increasing LOS, antibiotic cost, or mortality rate.

Pharmacoeconomic study of anti-influenza virus drugs in Japan based on a network meta-analysis.

An analysis was conducted in Japan to determine the most cost-effective neuraminidase inhibitor for the treatment of influenza virus infections from the healthcare payer's standpoint. This study reanalysed the findings of a previous study that had some limitations (no probabilistic sensitivity analysis and quality of life scores measured by the EQ-5D-3L instead of the EQ-5D-5L) and used a decision tree model with only three health conditions. This study incorporated new data from a network meta-analysis study into the first examination. The second examination involved constructing a new decision tree model encompassing seven health conditions and identifying costs, which consisted of medical costs and drug prices based on the 2020 version of the Japanese medical fee index. Effectiveness outcomes were measured using EQ-5D-5L questionnaires for adult patients with a history of influenza virus infections within a 14-day time horizon. Deterministic and probabilistic sensitivity analyses were performed to examine the uncertainty. In the first examination, the base-case cost-effectiveness analysis confirmed that oseltamivir outperformed laninamivir, zanamivir and peramivir, making it the most cost-effective neuraminidase inhibitor. The second examination revealed that oseltamivir dominated the other agents. Both deterministic and probabilistic sensitivity analyses showed robust results that validated oseltamivir as the most cost effective among the four neuraminidase inhibitors. This study thus reaffirms oseltamivir's position as the most cost-effective neuraminidase inhibitor for the treatment of influenza virus infections in Japan from the perspective of healthcare payment. These findings can help decision makers and healthcare providers in Japan.

Epidural analgesia during labour and severe maternal morbidity: population based study

ObjectivesTo determine the effect of labour epidural on severe maternal morbidity (SMM) and to explore whether this effect might be greater in women with a medical indication for epidural analgesia...

The Price Trend of Polypropylene

Since the polypropylene (PP) is one of the most widely used plastics, the futures prices of polypropylene are of great significance for studying the Chinese plastic market and related investors. This paper analyzes the factors that influence the changes in PP futures prices during and before the pandemic period by examining the correlation between upstream raw materials, downstream product markets, and PP futures prices. The results show that the futures prices of the raw materials are positively correlated with PP futures prices. Additionally, during the COVID-19 pandemic, due to the reduction in domestic PP demand in China, blocked crude oil imports, and refinery closures caused by control measures, the impact of crude oil futures prices on PP futures prices is relatively diminished. Furthermore, the increased demand for plastic packaging during the pandemic led to abnormal fluctuations in the packaging stock index, making it less valuable for analyzing PP futures prices. Finally, a regression analysis is conducted to establish a generalized predictive model for PP futures prices during non-pandemic periods, which is 9.91469 * crude oil futures prices + (-1.22343) * packaging stock index + 3.96203 * textile stock index + (-0.26201) * medical devices stock index. Its reliability is tested using data tests, residual vs. fitted analysis, and K-fold cross-validation, among other methods.

Method of non-drug pain relief during childbirth

In modern obstetrics it is possible to regulate pain perception during childbirth. There are methods of both drug and non-drug pain relief during childbirth. Up to 25–30 % of women characterize labor pain as severe and excessive. Adequate labor pain relief provides psychological comfort and eliminates stress caused by pain. After labor pain, many women experience depression, decide to terminate the next pregnancy, or (up to 30 %) request a caesarean section without medical indications. Pain relief during labor is one of the priorities in obstetric care.

Comparison of Bishop’s score with transvaginal sonographic cervical assessment to predict success of induction of labor

Induction of labor for medical or obstetric indications is a common practice in modern obstetrics. Evaluation of the cervix by Bishop’s score is universally used to predict the success of induction of labor. But it is a subjective method and many studies have shown that it is not a good indicator of success of induction. To compare Bishop’s scoring system and trans-vaginal sonographic assessment of cervix in predicting the successful outcome of induction of labor.This was an observational study conducted in a tertiary care center. 120 patients who met the selection criteria were included. Prior to the induction of labor the Bishop’s score and the sonographic scoring was assigned. Successful induction was defined as the patient entering the active phase of labor. 84% of participating women entered the active phase of labor. While 72.6% women had a normal vaginal delivery, 67.8% women delivered vaginally within 24 hours of induction. The TVS score (MGPICSS) of ≥2 predicted the successful induction with a specificity of 100% and sensitivity of 39.3% and AUC 0.74. In comparison, the Bishop score of ≥4 had a specificity of 75% and sensitivity of 44% and AUC 0.56. The prediction of delivery within 24 hours at the MGPICSS of ≥2 had a specificity of 100% and sensitivity of 42.9% and AUC 0.76. For the same, the Bishop’s score of ≥4 had specificity of 83.3% and sensitivity of 45.5% and AUC 0.71. TVS assessment of cervix is a better predictor of successful labor induction in comparison to Bishop’s score.

Value-Based Health Care for Prostate Cancer Centers by Implementing Specific Key Performance Indicators Using a Balanced Score Card.

Prostate cancer (PC) is the most common cancer in men in 112 countries, and accounts for 15% of cancers. Because it cannot be prevented, the rise in cases is inevitable, and improvements in diagnostic pathways and treatments are needed, as there is still a shortage of cost-effective diagnostics and widespread oncologically safe treatment options with measurable quality. As part of the implementation of a Full Cycle of Care, instruments have been developed to achieve value-based medicine, such as consistent commitment to measurability. One of these instruments is the Balanced Scorecard (BSC). Here, we propose the first BSC for prostate cancer (PC) treatment. BSCs are used to assess performance in healthcare organizations across four dimensions: financial, patient and referrer, process, and learning and development. This study aimed to identify Key Performance Indicators (KPIs) for each perspective. A systematic literature search was conducted according to PRISMA guidelines using multiple databases and specific search terms to identify KPIs for PC care, excluding case reports and conference abstracts. In total, 44 reports were included in analyses and development of the PC-specific BSC. In the present study, a PC-specific BSC and KPIs were defined for the four classic perspectives, as well as for a newly developed PC-Specific Disease and Outcome perspective, including patient-related parameters from the German Cancer Society and the International Consortium for Health Outcomes Measurement. In addition, the Process perspective includes KPIs of fulfillment of continuing education of residents and the metrics of structured training of the radical prostatectomy procedure in the Learning and Development perspective. The developed BSC provides a comprehensive set of perspectives for an Integrated Practice Unit or center in PC care, ensuring that the indicators remain manageable and applicable. The BSC facilitates value creation in line with Porter's Full Cycle of Care by systematically collecting and providing economic, personnel, and medical results, actions, and indicators. In particular, this BSC includes KPIs of structured training of practitioners and metrics of the German Cancer Society, that recently proved to improve PC patients outcomes.

Studying eruption patterns of mandibular third molars for forensic age assessment: Introducing current reference data from a population of black South Africans

IntroductionEvaluation of the eruption of mandibular third molars in orthopantomograms (OPGs) is a method of forensic age assessment. The objective of our study was to provide valid reference data for this trait within a population of black South Africans. The study was guided by the criteria for reference studies in age assessment.Materials and methodsA study population from Pretoria, South Africa comprising 670 OPGs obtained from 338 black females and 332 black males aged between 15.00 and 25.97 years was analysed. All OPGs were performed for medical indication during the period from 2011 to 2022 and were retrospectively evaluated. From the 670 OPGs, a total of 1021 mandibular third molars were evaluated. The assessment of mandibular third molars was conducted using the staging scale presented by Olze et al. in 2012. Two experienced dentists evaluated the OPGs independently of each other. If the two examiners diverged in their assessments, a consensus stage was assigned.ResultsAs expected, the mean, median and minimal age increased with higher stages for both teeth and both sexes. The minimum age recorded for stage D, indicating complete tooth eruption, was 15.79 years in females and 16.62 years in males.ConclusionAs it is the case for previous reference studies in other countries, placing exclusive reliance on the evaluation of mandibular third molar eruption is inadequate for ascertaining the age of majority among Black South Africans. Future studies need to examine if our results are transferable to other countries in Sub-Saharan Africa.

Age-related patterns in mandibular third molar eruption: presenting new forensic age assessment reference data from a Chinese population.

Valid reference data are essential for reliable forensic age assessment procedures in the living, a fact that extends to the trait of mandibular third molar eruption in dental panoramic radiographs (PAN). The objective of this study was to acquire valid reference data for a northern Chinese population. The study was guided by the criteria for reference studies in age assessment.To this end, a study population from China comprising 917 panoramic radiographs obtained from 430 females and 487 males aged between 15.00 and 25.99 years was analysed. Of the 917 PANs, a total of 1230 mandibular third molars were evaluated.The PANs, retrospectively evaluated, were performed for medical indication during the period from 2016 to 2021. The assessment of mandibular third molars was conducted using the staging scale presented by Olze et al. in 2012. Two independent examiners, trained in assessing PANs for forensic age estimation, evaluated the images. In instances where the two examiners diverged in their assessments these were subsequently deliberated, and a consensus stage was assigned.The mean age increased with higher stages for both teeth and both sexes. The minimum age recorded for stage D, indicating complete tooth eruption, was 15.6 years in females and 16.1 years in males. Consequently, the completion of mandibular third molar eruption was observed in both sexes well before reaching the age of 18. In light of our results, it is evident that relying solely on the assessment of mandibular third molar eruption may not be sufficient for accurately determining the age of majority. Contrary to previous literature, this finding of a completed eruption of the mandibular third molars in northern Chinese individuals is only suitable for detecting the completion of the 16th year of life in males according to our results. However, as the results are inconsistent compared to other studies in the literature, the trait should not be used as the only decisive marker to prove this age threshold in males from northern China.

Long-term exposure to PM2.5 and mortality in a national cohort in South Korea: effect modification by community deprivation, medical infrastructure, and greenness

BackgroundLong-term exposure to PM2.5 has been linked to increased mortality risk. However, limited studies have examined the potential modifying effect of community-level characteristics on this association, particularly in Asian contexts. This study aimed to estimate the effects of long-term exposure to PM2.5 on mortality in South Korea and to examine whether community-level deprivation, medical infrastructure, and greenness modify these associations.MethodsWe conducted a nationwide cohort study using the National Health Insurance Service-National Sample Cohort. A total of 394,701 participants aged 30 years or older in 2006 were followed until 2019. Based on modelled PM2.5 concentrations, 1 to 3-year and 5-year moving averages of PM2.5 concentrations were assigned to each participant at the district level. Time-varying Cox proportional-hazards models were used to estimate the association between PM2.5 and non-accidental, circulatory, and respiratory mortality. We further conducted stratified analysis by community-level deprivation index, medical index, and normalized difference vegetation index to represent greenness.ResultsPM2.5 exposure, based on 5-year moving averages, was positively associated with non-accidental (Hazard ratio, HR: 1.10, 95% Confidence Interval, CI: 1.01, 1.20, per 10 µg/m3 increase) and circulatory mortality (HR: 1.22, 95% CI: 1.01, 1.47). The 1-year moving average of PM2.5 was associated with respiratory mortality (HR: 1.33, 95% CI: 1.05, 1.67). We observed higher associations between PM2.5 and mortality in communities with higher deprivation and limited medical infrastructure. Communities with higher greenness showed lower risk for circulatory mortality but higher risk for respiratory mortality in association with PM2.5.ConclusionsOur study found mortality effects of long-term PM2.5 exposure and underlined the role of community-level factors in modifying these association. These findings highlight the importance of considering socio-environmental contexts in the design of air quality policies to reduce health disparities and enhance overall public health outcomes.

Diagnostics of the influence of medical and demographic indicators on regional socio-economic systems

The article presents approaches to monitoring and assessing social aspects of regional systems with identification of elements of the health system and demographic components that potentially affect the economic efficiency of functioning of territories. The relevance of the article is determined by objective features of the development of mesoterritories. The analysis of spatial features of the systems’ functioning was conducted on the materials of the Central Federal District. The purpose of the study is to assess the features of the regional genesis using regression analysis and the resulting indicator – gross regional product (hereinafter referred to as GRP), which allows us to give a more reliable characterisation of the mesoterritorial transformation. The subjects were grouped according to the quality of medical and demographic characteristics on the basis of the cluster analysis with further allocation of flagship, catching-up and lagging regions. To substantiate the reliability of the territories’ affiliation to a specific cluster group, a statistical analysis was performed on average values with consideration to identification of the level of medical and demographic development. The conclusion is made about the influence of some factor criteria on the regional space with the construction of a scatter plot. It displays the affiliation to the selected confidence interval and distribution of the elements of the set in the plane between the resulting and factor values, describing the dependence of the GRP on the medical and demographic indicator. These econometric and analytical models can be used by regional governments in the process of strategic planning.

Medical mistrust, discrimination and healthcare experiences in a rural Namibian community

ABSTRACT Substantial evidence indicates that medical mistrust, resulting from experiences with discrimination and marginalisation, is a determinant of health disparities in minority populations. However, this research is largely limited to the US and other industrialised countries. To broaden our understanding of the role of medical mistrust on health-care decision making, we conducted a study on healthcare experiences and perceptions in a rural, underserved indigenous community in northwest Namibia (n = 86). Mixing semi-structured interview questions with the medical mistrust index (MMI), we aim to determine the relevance of the MMI in a non-industrialised population and compare index scores with reports of healthcare experiences. We find that medical mistrust is a salient concept in this community, mapping onto negative healthcare experiences and perceptions of discrimination. Reported healthcare experiences indicate that perceived incompetence, maltreatment and discrimination drive mistrust of medical personnel. However, reporting of recent healthcare experiences are generally positive. Our results indicate that the concept of medical mistrust can be usefully applied to communities in the Global South. These populations, like minority communities in the US, translate experiences of discrimination and marginalisation into medical mistrust. Understanding these processes can help address health disparities and aid in effective public health outreach in underserved populations.

Revision Cochlear Implantation With Device Manufacturer Conversion: Surgical Outcomes and Speech Perception Performance.

Describe the clinical profile of revision cochlear implantation (RCI) cases involving device manufacturer conversion (RCImc+), compare them to cases without manufacturer conversion (RCImc-), and classify the reasons for manufacturer conversion (MC). Retrospective case review. Tertiary academic center. Data on demographics, RCI indications, medical background, surgical details, and the reasons for MC were collected for all RCIs from 1989 to 2020. Post-RCI speech perception performance was categorized as unchanged, improved, or declined, according to clinically based criteria. Of 185 RCIs, 39 (21%) involved MC, mostly in pediatric patients (67%). The leading RCImc+ indications were device-related (59%) and medical (31%) failures. Initial implant manufacturers were Advanced Bionics (49%), Cochlear (25.5%), or Medel (25.5%). Most MC reasons were patient-driven (64%) versus CI team recommendations (36%). The RCImc+ group demonstrated a 3-fold higher rate of medical indications than RCImc- (31% vs11.5%, P = .007). The time interval from symptom onset to RCI was longer in RCImc+ (43 vs20.3 months, P = .001), and the rate of multiple revisions in the same ear was higher (25.6% vs8.2%, P = .009). Complete reinsertion rates were high in both RCImc+ and RCImc- (94.8% vs94.5%, P = 1) without any complications. Speech perception improved or remained unchanged in most (84%) cases, with no significant difference between the groups (P = .183). This retrospective study showed that RCI involving MC is safe and beneficial. Although RCImc+ patients exhibited distinct clinical characteristics, MC did not impact surgical or speech perception outcomes. This provides evidence-based data to support informed decision-making by CI teams and patients.

Computational drug repositioning with attention walking

Drug repositioning aims to identify new therapeutic indications for approved medications. Recently, the importance of computational drug repositioning has been highlighted because it can reduce the costs, development time, and risks compared to traditional drug discovery. Most approaches in this area use networks for systematic analysis. Inferring drug-disease associations is then defined as a link prediction problem in a heterogeneous network composed of drugs and diseases. In this article, we present a novel method of computational drug repositioning, named drug repositioning with attention walking (DRAW). DRAW proceeds as follows: first, a subgraph enclosing the target link for prediction is extracted. Second, a graph convolutional network captures the structural features of the labeled nodes in the subgraph. Third, the transition probabilities are computed using attention mechanisms and converted into random walk profiles. Finally, a multi-layer perceptron takes random walk profiles and predicts whether a target link exists. As an experiment, we constructed two heterogeneous networks with drug-drug similarities based on chemical structures and anatomical therapeutic chemical classification (ATC) codes. Using 10-fold cross-validation, DRAW achieved an area under the receiver operating characteristic (ROC) curve of 0.903 and outperformed state-of-the-art methods. Moreover, we demonstrated the results of case studies for selected drugs and diseases to further confirm the capability of DRAW to predict drug-disease associations.

Antithrombotic therapy after heart valve surgery: contemporary practice in the UK.

There is a lack of high-quality data informing the optimal antithrombotic drug strategy following bioprosthetic heart valve replacement or valve repair. Disparity in recommendations from international guidelines reflects this. This study aimed to document current patterns of antithrombotic prescribing after heart valve surgery in the UK. All UK consultant cardiac surgeons were e-mailed a custom-designed survey. The use of oral anticoagulant (OAC) and/or antiplatelet drugs following bioprosthetic aortic valve replacement or mitral valve replacement, or mitral valve repair (MVrep), for patients in sinus rhythm, without additional indications for antithrombotic medication, was assessed. Additionally, we evaluated anticoagulant choice following MVrep in patients with atrial fibrillation. We identified 260 UK consultant cardiac surgeons from 36 units, of whom 103 (40%) responded, with 33 units (92%) having at least 1 respondent. The greatest consensus was for patients undergoing bioprosthetic aortic valve replacement, in which 76% of surgeons favour initial antiplatelet therapy and 53% prescribe lifelong treatment. Only 8% recommend initial OAC. After bioprosthetic mitral valve replacement, 48% of surgeons use an initial OAC strategy (versus 42% antiplatelet), with 66% subsequently prescribing lifelong antiplatelet therapy. After MVrep, recommendations were lifelong antiplatelet agent alone (34%) or following 3 months OAC (20%), no antithrombotic agent (20%), or 3 months OAC (16%). After MVrep for patients with established atrial fibrillation, surgeons recommend warfarin (38%), a direct oral anticoagulant (37%) or have no preference between the 2 (25%). There is considerable variation in the use of antithrombotic drugs after heart valve surgery in the UK and a lack of high-quality evidence to guide practice, underscoring the need for randomized studies.

Совершенствование медико-социальных мер по охране психического здоровья подростков в системе первичной медико-санитарной помощи (обзор литературы).

Actuality. To develop effective tools for protecting the mental health of adolescents, medical workers need to clarify the leading reasons for its formation in modern conditions, predictors and criteria for the risk of its deterioration. Currently, there are no integrated medicalpsychological- social monitoring studies of adolescent mental health, including dynamic monitoring of psychological, pedagogical, social and medical indicative indicators. The purpose of the study is to review scientific publications devoted to the analysis of the state of mental health of children and adolescents in the Russian Federation. Research methods. Using the search image: («mental health of children and adolescents», «organization of psychiatric care for children and adolescents», «addictive behavior of children and adolescents», «risk factors for mental health of children and adolescents»), a collection of 63 relevant articles published by domestic and foreign authors over the past 15 years (2013–2023) have been formed, indexed in the bibliometric databases WoS, Scopus, RSCI, and in the search engines PubMed, Google Scholar. Research results. The performed analysis allows us to note that such issues as the manifestation of clinical mental disorders, their predictors with age-related detail, and the development of integral indicators of mental health deterioration have not been sufficiently studied. Studies indicating the presence of problems in the system of mental health protection of minors during their studies in general education organizations do not provide specific recommendations for their solution.. Conclusion. To develop effective tools for the protection of adolescent mental health, medical professionals need to clarify the leading causes of its formation in modern conditions, predictors and criteria for the risk of its deterioration. This will make it possible to fill the existing deficit in the algorithms of medical support for adolescents during their studies in general education organizations and medical, psychological and pedagogical integration.

Медико-демографические показатели населения села старше трудоспособного возраста в Республике Татарстан.

Demographic aging of the population is especially pronounced in rural areas and has regional differences. Purpose of the study: based on the analysis of medical and demographic indicators of mortality and morbidity of the rural population over working age in the Republic of Tatarstan (RT), to develop proposals for the health of rural residents. Methods and materials: analytical, statistical, Rosstat data and statistical materials from the Federal State Budgetary Institution “TsNIIOIZ” of the Russian Ministry of Health (2019–2022). Results. During the years of pension reform (2019–2023), the number of rural population in the Republic of Tatarstan increased slightly – from 922,3 to 930,3 thousand (0,9%), while the share of the rural population over working age decreased from 28,6 up to 27,5% (in the Russian Federation the figure is lower – 25,5%). The mortality rates of the rural population in the Republic of Tatarstan were significantly higher for all years of analysis: in 2013 they were 15,5‰ for the rural population, 11,0 for the urban population. During the years of COVID‑19, mortality rates increased and amounted to 18,9‰ for the rural population in 2021, 14,4‰ for the urban population, and decreased in 2022 and amounted to 14.1 and 10,3‰, respectively. The primary morbidity rate of the rural population in the Russian Federation (2022) was 64755,2 per 100 thousand rural population, in the Republic of Tatarstan it was lower – 52598,4‰îî. There is a large difference in the indicators in the constituent entities of the Russian Federation – 13,6 times. The newly identified morbidity in the rural population over working age in the Republic of Tatarstan is lower than 48996,2‰îî than in the entire rural population 52598,4‰îî, while the older population has the highest rates of primary morbidity due to diseases of the circulatory system, diseases of the bones, muscular system and connective tissue, diseases of the genitourinary system, diseases of the nervous system, neoplasms, etc. In this age group, the incidence of COVID‑19 is higher. The results of the study should be taken into account for the development of management decisions at the regional level, as well as when implementing programs for rehabilitation and medical examination of older patients.

Artificial intelligence-based classification of breast nodules: a quantitative morphological analysis of ultrasound images.

Accurate classification of breast nodules into benign and malignant types is critical for the successful treatment of breast cancer. Traditional methods rely on subjective interpretation, which can potentially lead to diagnostic errors. Artificial intelligence (AI)-based methods using the quantitative morphological analysis of ultrasound images have been explored for the automated and reliable classification of breast cancer. This study aimed to investigate the effectiveness of AI-based approaches for improving diagnostic accuracy and patient outcomes. In this study, a quantitative analysis approach was adopted, with a focus on five critical features for evaluation: degree of boundary regularity, clarity of boundaries, echo intensity, and uniformity of echoes. Furthermore, the classification results were assessed using five machine learning methods: logistic regression (LR), support vector machine (SVM), decision tree (DT), naive Bayes, and K-nearest neighbor (KNN). Based on these assessments, a multifeature combined prediction model was established. We evaluated the performance of our classification model by quantifying various features of the ultrasound images and using the area under the receiver operating characteristic (ROC) curve (AUC). The moment of inertia achieved an AUC value of 0.793, while the variance and mean of breast nodule areas achieved AUC values of 0.725 and 0.772, respectively. The convexity and concavity achieved AUC values of 0.988 and 0.987, respectively. Additionally, we conducted a joint analysis of multiple features after normalization, achieving a recall value of 0.98, which surpasses most medical evaluation indexes on the market. To ensure experimental rigor, we conducted cross-validation experiments, which yielded no significant differences among the classifiers under 5-, 8-, and 10-fold cross-validation (P>0.05). The quantitative analysis can accurately differentiate between benign and malignant breast nodules.

Detection of Autoantibodies Against the Acetylcholine Receptor, Evaluation of Commercially Available Methodologies: Fixed Cell-Based Assay, Radioimmunoprecipitation Assay and Enzyme-Linked Immunosorbent Assay1.

Myasthenia Gravis (MG) is an autoimmune disorder characterized by pathogenic autoantibodies (AAbs) targeting nicotinic acetylcholine receptors (AChR), disrupting neuromuscular communication. RadioImmunoPrecipitation Assay (RIPA) is recommended to detect AChR AAbs, but its complexity and radioactive requirements limit widespread use. We compare non-RIPA anti-AChR immunoassays, including Cell-Based Assay (CBA) and two ELISA kits, against the gold standard RIPA. 145 samples were included with medical indication for anti-AChR testing. By the RIPA method, 63 were negative (RIPA-Neg < 0.02 nmol/L), 18 were classified as Borderline (≥0.02 -1 nmol/L), and 64 were positive (RIPA-Pos > 1 nmol/L). The competitive ELISA showed poor agreement with RIPA (Kappa = 0.216). The indirect ELISA demonstrated substantial agreement with RIPA (Kappa = 0.652), with ∼76% sensitivity and ∼94% specificity for MG diagnostic. The CBA, where fixed cells expressing clustered AChR were used as substrate, exhibited almost perfect agreement with RIPA (Kappa = 0.984), yielding ∼98% sensitivity and 96% specificity for MG. In addition, a semiquantitative analysis showed a strong correlation between CBA titration, indirect ELISA, and RIPA levels (r = 0.793 and r = 0.789, respectively). The CBA displayed excellent analytical performance for MG diagnostic when compared to RIPA, making it a potential replacement for RIPA in clinical laboratories. Some solid-phase assays (such as the indirect ELISA applied here), as well as CBA titration, offer reliable options to estimate anti-AChR AAb levels after confirming positivity by the CBA.∥.

CARDIO PREDICT: HARNESSING MACHINE LEARNING FOR ADVANCED HEART DISEASE RISK ASSESSMENT

Heart disease prediction using machine learning algorithms has gained significant attention due to its potential to improve diagnosis and treatment. This study explores various machine learning techniques and an algorithm applied to heart disease prediction. We analyze the performance of popular algorithms such as logistic regression, decision trees, random forests, support vector machines, and artificial neural networks on heart disease datasets. Additionally, we investigate the impact of feature selection, data preprocessing techniques, and model evaluation metrics on the predictive performance. The results demonstrate the heart disease risk, providing valuable insights for medical practitioner and researchers in the field of Cardiovascular health. The datasets used comprises a collection of patient data, including age, gender, blood pressure, cholesterol levels, and other relevant medical indicators. Neural networks are trained and evaluated to assess their performance in predicting the presence investigates the impact feature selection hyper parameter tuning. The results obtained provide insights into the strengths and limitations of different machine learning approaches for heart disease prediction, offering valuable guidance for healthcare practitioners and researchers in the field. Heart disease is prevalent and life-threatening condition worldwide. We analyze the performance of these algorithms using relevant metrics such as accuracy, precision, recall, and Fr-score. Additionally, we investigate feature importance to understand the factors contributing most to heart disease prediction. Our findings demonstrate the potential of machine learning in assisting healthcare professionals in early detection and prevention of heart disease, ultimately improving penitent outcomes and quality of life.