Minimum Set Of Data Research Articles

Core outcomes in nerve surgery: development of a core outcome set for common peroneal (fibular) neuropathy.

Common peroneal (fibular) neuropathy is the most common mononeuropathy of the lower extremity. Despite this, there are surprisingly few studies on the topic, and a knowledge gap remains in the literature. As one attempts to address this knowledge gap, a core outcome set (COS) is needed to guide the planning phases of future studies to allow synthesis and comparability of these studies. The objective of this study was to develop the COS-common peroneal neuropathy (CoPe) using a modified Delphi approach. A 5-stage approach was used to develop the COS-CoPe: 1) stage 1, consortium development; 2) stage 2, a literature review to identify potential outcome measures; 3) stage 3, a Delphi survey to develop consensus on outcomes for inclusion; 4) stage 4, a Delphi survey to develop definitions; and 5) stage 5, a consensus meeting to finalize COS and definitions. The study followed the COS-STAndards for Development (COS-STAD) recommendations. The Core Outcomes in Nerve Surgery (COINS) Consortium comprised 23 participants, all neurological surgeons, representing 13 countries. The final COS-CoPe consisted of 31 data points/outcomes covering domains of demographics, diagnostics, patient-reported outcomes, motor/sensory outcomes, and complications. Appropriate instruments, methods of testing, and definitions were set. The consensus minimum duration of follow-up was 12 months. The consensus optimal time points for assessment were preoperatively and 3, 6, 12, and 24 months postoperatively. The COINS Consortium developed a consensus COS and provided definitions, methods of implementation, and time points for assessment. The COS-CoPe should serve as a minimum set of data that should be collected in all future neurosurgical studies on common peroneal neuropathy. Incorporation of this COS should help improve consistency in reporting, data synthesis, and comparability, and should minimize outcome reporting bias.

Desarrollo y consenso de un cuadro de mando para evaluar la actividad investigadora en los servicios de farmacia hospitalaria en España

ObjectiveTo develop by consensus a dashboard model to standardize and promote the evaluation of research activity in Spanish Hospital Pharmacy Services. MethodsThe study was carried out in 5 phases following the modified Delphi methodology: constitution of the coordinating group, elaboration of a list of scenarios, selection of participating centers, evaluation of the list of scenarios, and analysis of the results.The coordinating group designed a questionnaire with 114 questions. General research questions and different scenarios (indicators) were included to form the dashboard. The Hospital Pharmacy Services with the highest number of publications were identified to participate in the Delphi consultation. Two rounds of consultations were conducted in which the "Need" and/or "Feasibility" of their measurement was evaluated for each of the scenarios, using a numerical scale from 1 (lowest score) to 9 (highest score). ResultsSixteen Hospital Pharmacy Services, belonging to 8 different autonomous communities, participated in the Delphi consultation. A total of 100% of them responded to all the questions in the 2 rounds of consultations. It was considered that the Hospital Pharmacy Services should have a research dashboard (need = 100%) with a basic structure and a common minimum set of data for all them (need = 87.5%). The consensus was reached on distinguishing research projects led by the Hospital Pharmacy Services from those led by other groups in which the Hospital Pharmacy Services collaborate (need = 87.5%), and a definition was approved on the leadership of these projects according to whether they are single-center or multicenter.A consensus was reached on 40 indicators to form the dashboard, which evaluates publications (13 indicators), human resources (12 indicators), research projects (9 indicators), doctoral theses (4 indicators), and patents and intellectual property registrations (2 indicators). ConclusionsThis is the first consensus dashboard developed to evaluate the research activity of the Hospital Pharmacy Services, which will help to analyze the productivity and impact of research systematically and continuously. In addition, it will allow comparison between them and will help to establish synergies and identify trends, patterns, and challenges.

[Translated article] Development and consensus of a dashboard model to evaluate research activity in Spanish Hospital Pharmacy Services

ObjectiveTo develop by consensus a dashboard model to standardise and promote the evaluation of research activity in Spanish Hospital Pharmacy Services. MethodsThe study was carried out in 5 phases following the modified Delphi methodology: constitution of the coordinating group, elaboration of a list of scenarios, selection of participating centres, evaluation of the list of scenarios, and analysis of the results.The coordinating group designed a questionnaire with 114 questions. General research questions and different scenarios (indicators) were included to form the dashboard. The Hospital Pharmacy Services with the highest number of publications were identified to participate in the Delphi consultation. Two rounds of consultations were conducted in which the “Need” and/or “Feasibility” of their measurement was evaluated for each of the scenarios, using a numerical scale from 1 (lowest score) to 9 (highest score). ResultsSixteen Hospital Pharmacy Services, belonging to 8 different Autonomous Communities, participated in the Delphi consultation. A total of 100% of them responded to all the questions in the 2 rounds of consultations. It was considered that the Hospital Pharmacy Services should have a research dashboard (Need=100%) with a basic structure and a common minimum set of data for all them (Need=87.5%). The consensus was reached on distinguishing research projects led by the Hospital Pharmacy Services from those led by other groups in which the Hospital Pharmacy Services collaborate (Need=87.5%), and a definition was approved on the leadership of these projects according to whether they are single-centre or multicentre.A consensus was reached on 40 indicators to form the dashboard, which evaluates publications (13 indicators), human resources (12 indicators), research projects (9 indicators), doctoral theses (4 indicators), and patents and intellectual property registrations (2 indicators). ConclusionsThis is the first consensus dashboard developed to evaluate the research activity of the Hospital Pharmacy Services, which will help to analyse the productivity and impact of research systematically and continuously. In addition, it will allow comparison between them and will help to establish synergies and identify trends, patterns, and challenges.

Corn Cropping Systems in Agricultural Soils from the Bajio Region of Guanajuato: Soil Quality Indexes (SQIs)

Agriculture is a sector of great importance for Mexico’s economy, generating employment and contributing significantly to the country’s gross domestic product. The Bajio stands out as one of the most productive agricultural regions in Mexico. However, intensive agricultural practices in this area have caused a progressive deterioration and loss of soil fertility. This study focused on evaluating the quality of soils used for agriculture in the Bajio region of the State of Guanajuato, Mexico. This evaluation, utilised soil quality indexes (SQIs) based on a total of 27 physicochemical, biological and enzymatic indicators. These indicators were selected by means of a principal component analysis (PCA), which allowed for the identification of a minimum set of data. The SQIs developed in this study categorised soils into different quality levels, ranging from low to high, mainly based on the values observed in the biological indicators (SMR and qCO2), which comprised the established SQIs. The inclusion of these biological indicators provides the developed SQIs with greater sensitivity to detect minor disturbances in agricultural soils due to human activity, compared with SQIs consisting only of physicochemical indicators. The developed SQIs can be used to ensure high-quality food production in soils used for corn cultivation under similar conditions, both nationally and internationally.

Electronic Health Records for Predicting Outcomes to Work-Related Musculoskeletal Disorders: A Scoping Review.

Through electronic health records (EHRs), musculoskeletal (MSK) therapists such as chiropractors and physical therapists, as well as occupational medicine physicians could collect data on many variables that can be traditionally challenging to collect in managing work-related musculoskeletal disorders (WMSDs). The review's objectives were to explore the extent of research using EHRs in predicting outcomes of WMSDs by MSK therapists. A systematic search was conducted in Medline, PubMed, CINAHL, and Embase. Grey literature was searched. 2156 unique papers were retrieved, of which 38 were included. Three themes were explored, the use of EHRs to predict outcomes to WMSDs, data sources for predicting outcomes to WMSDs, and adoption of standardised information for managing WMSDs. Predicting outcomes of all MSK disorders using EHRs has been researched in 6 studies, with only 3 focusing on MSK therapists and 4 addressing WMSDs. Similar to all secondary data source research, the challenges include data quality, missing data and unstructured data. There is not yet a standardised or minimum set of data that has been defined for MSK therapists to collect when managing WMSD. Further work based on existing frameworks is required to reduce the documentation burden and increase usability. The review outlines the limited research on using EHRs to predict outcomes of WMSDs. It highlights the need for EHR design to address data quality issues and develop a standardised data set in occupational healthcare that includes known factors that potentially predict outcomes to help regulators, research efforts, and practitioners make better informed clinical decisions.

Core outcomes in nerve surgery: development of a core outcome set for brachial plexus and upper extremity nerve injuries.

When considering traumatic brachial plexus and upper extremity nerve injuries, iatrogenic nerve injuries, and nontraumatic nerve injuries, brachial plexus and upper extremity nerve injuries are commonly encountered in clinical practice. Despite this, data synthesis and comparison of available studies are difficult. This is at least in part due to the lack of standardization in reporting and a lack of a core outcome set (COS). Thus, there is a need for a COS for adult brachial plexus and upper extremity nerve injuries (COS-BPUE). The objective of this study was to develop a COS-BPUE using a modified Delphi approach. A 5-stage approach was used to develop the COS-BPUE: 1) consortium development, 2) literature review to identify potential outcome measures, 3) Delphi survey to develop consensus on outcomes for inclusion, 4) Delphi survey to develop definitions, and 5) consensus meeting to finalize the COS and definitions. The study followed the Core Outcome Set-STAndards for Development (COS-STAD) recommendations. The Core Outcomes in Nerve Surgery (COINS) Consortium comprised 23 participants, all neurological surgeons, representing 13 countries. The final COS-BPUE consisted of 36 data points/outcomes covering demographic, diagnostic, patient-reported outcome, motor/sensory outcome, and complication domains. Appropriate instruments, methods of testing, and definitions were set. The consensus minimum duration of follow-up was 24 months, with the consensus optimal time points for assessment being preoperatively and 3, 6, 12, and 24 months postoperatively. The COINS Consortium developed a consensus COS and provided definitions, methods of implementation, and time points for assessment. The COS-BPUE should serve as a minimum set of data that should be collected in all future neurosurgical studies on adult brachial plexus and upper extremity nerve injuries. Incorporation of this COS should help improve consistency in reporting, data synthesis, and comparability, and should minimize outcome reporting bias.

Core outcomes in nerve surgery: development of a core outcome set for ulnar neuropathy at the elbow.

Ulnar neuropathy at the elbow (UNE) is common, affecting 1%-6% of the population. Despite this, there remains a lack of consensus regarding optimal treatment. This is primarily due to the difficulty one encounters when trying to assess the literature. Outcomes are inconsistently reported, which makes comparing studies or developing meta-analyses difficult or even impossible. Thus, there is a need for a core outcome set (COS) for UNE (COS-UNE) to help address this problem. The objective of this study was to utilize a modified Delphi method to develop COS-UNE. A 5-stage approach was utilized to develop COS-UNE: stage 1, consortium development; 2, literature review to identify potential outcome measures; 3, Delphi survey to develop consensus on outcomes for inclusion; 4, Delphi survey to develop definitions; and 5, consensus meeting to finalize the COS and definitions. The study followed the Core Outcome Set-STAndards for Development (COS-STAD) recommendations. The Core Outcomes in Nerve Surgery (COINS) Consortium comprised 21 participants, all neurological surgeons representing 11 countries. The final COS-UNE consisted of 22 data points/outcomes covering the domains of demographic characteristics, diagnostics, patient-reported outcomes, motor/sensory outcomes, and complications. Appropriate instruments, methods of testing, and definitions were set. The consensus minimum duration of follow-up was 6 months, with the consensus optimal timepoints for assessment identified as preoperatively and 3, 6, and 12 months postoperatively. The authors identified consensus data points/outcomes and also provided definitions and specific scales to be utilized to help ensure that clinicians are consistent in their reporting across studies on UNE. This COS should serve as a minimum set of data to be collected in all future neurosurgical studies on UNE. The authors hope that clinicians evaluating ulnar neuropathy will incorporate this COS into routine practice and that future studies will consider this COS in the design phase.

Methodological differences between studies confound one-size-fits-all approaches to managing surface waterways for food and water safety.

Even though differences in methodology (e.g., sample volume and detection method) have been shown to affect observed microbial water quality, multiple sampling and laboratory protocols continue to be used for water quality monitoring. Research is needed to determine how these differences impact the comparability of findings to generate best management practices and the ability to perform meta-analyses. This study addresses this knowledge gap by compiling and analyzing a data set representing 2,429,990 unique data points on at least one microbial water quality target (e.g., Salmonella presence and Escherichia coli concentration). Variance partitioning analysis was used to quantify the variance in likelihood of detecting each pathogenic target that was uniquely and jointly attributable to non-methodological versus methodological factors. The strength of the association between microbial water quality and select methodological and non-methodological factors was quantified using conditional forest and regression analysis. Fecal indicator bacteria concentrations were more strongly associated with non-methodological factors than methodological factors based on conditional forest analysis. Variance partitioning analysis could not disentangle non-methodological and methodological signals for pathogenic Escherichia coli, Salmonella, and Listeria. This suggests our current perceptions of foodborne pathogen ecology in water systems are confounded by methodological differences between studies. For example, 31% of total variance in likelihood of Salmonella detection was explained by methodological and/or non-methodological factors, 18% was jointly attributable to both methodological and non-methodological factors. Only 13% of total variance was uniquely attributable to non-methodological factors for Salmonella, highlighting the need for standardization of methods for microbiological water quality testing for comparison across studies.IMPORTANCEThe microbial ecology of water is already complex, without the added complications of methodological differences between studies. This study highlights the difficulty in comparing water quality data from projects that used different sampling or laboratory methods. These findings have direct implications for end users as there is no clear way to generalize findings in order to characterize broad-scale ecological phenomenon and develop science-based guidance. To best support development of risk assessments and guidance for monitoring and managing waters, data collection and methods need to be standardized across studies. A minimum set of data attributes that all studies should collect and report in a standardized way is needed. Given the diversity of methods used within applied and environmental microbiology, similar studies are needed for other microbiology subfields to ensure that guidance and policy are based on a robust interpretation of the literature.

Conceptual Model and Requirements of An Electronic Case Report Form to Collect a Minimum Data Set of Complications of the COVID -19

Introduction: In recent years, the collection of data from the monitoring of clinical trials in the form of electronic case report forms (eCRF) has been increasingly used, because avoiding mistakes, reducing the duration of clinical studies, and preventing increasing data collection costs can affect the success of the study. Accordingly, this research aimed to present the conceptual model and requirements of the proposed eCRF, which is based on NoSQL database to achieve complications caused by the COVID -19 vaccine. Method: In this study, using the descriptive -applicative method, the conceptual model of the eCRF system was first designed to collect the minimum set of data on the complications of the COVID -19 vaccine. Then, the functional and non -functional requirements of the proposed system were identified using the methods of observation, thinking and reflection, and questionnaire. Results: This research has two main parts: the proposed conceptual model and the functional and non -functional requirements of the eCRF system. A conceptual model was proposed based on the components, modules, and objectives of the eCRF core, which can be used by researchers and clinical trial specialists. Requirements including the ability to register, insert, delete, and edit the case report form, were also calculated for four groups of patients, health care workers, disease experts, and the executive manager. Conclusion: The proposed system provides researchers and experts of clinical trials with classified and valid data regarding the registration of complications caused by the COVID -19 vaccine in an integrated manner. Therefore, some eCRF stakeholders such as patients, healthcare workers, disease experts, and executive managers and researchers can achieve a vaccine with acceptable safety and effectiveness by analyzing, interpreting, and sharing the recorded information.

Pharmacotherapy follow-up of patients under treatment with biologic agents for chronic inflammatory systemic conditions: an agreement among hospital pharmacists for the standardized collection of a minimum set of data

Background and objectiveThe objective of this study was to reach a consensus on the minimum set of data that would allow to optimize the pharmacotherapy follow-up of patients on biologic agents for chronic systemic inflammatory conditions, through structured and standardized collection with an electronic tool in the hospital pharmacy. Materials and methodA scientific committee was formed (n = 5 hospital pharmacists). The Delphi Technique was used, 2 rounds of consultation by e-mail for hospital pharmacists. A structured questionnaire was used, based on a bibliographic review and recommendations by the scientific committee; 37 statements were assessed with the Likert 5-point scale (1= „Strongly Disagree“; 5= „Strongly Agree“). Consensus was reached when 75% or more of panel members assigned a score of 1-2 (rejection consensus) or 4-5 (agreement consensus) to the matter reviewed. Descriptive statistical analyses were conducted. ResultsThe study included 21 hospital pharmacists (70 were invited, there was 70% response). Consensus was reached for 100% of statements. The minimum set of data was agreed upon, as well as the recommendations that the pharmacist had to collect and make during visits: to document the health status, health-related quality of life, changes In treatment compliance and In patient autonomy, as well as the conditions to make feasible the systematic collection of the minimum data set. ConclusionsThere Is consensus among hospital pharmacists about a minimum data set to be collected, through an electronic tool, which will order, standardize and structure the pharmacotherapy follow-up of patients with chronic Inflammatory conditions on treatment with biologic agents In the Spanish public health system.

A decade of urban fires: Portuguese events between 2013 and 2022

This study describes a dataset containing urban fire events that took place in mainland Portugal between 2013 and 2022. The Regulation n.º3317-A/2018, established by the Portuguese National Emergency and Civil Protection Authority (Autoridade Nacional de Emergência e Proteção Civil, ANEPC), defines the Operations Management System (Sistema de Gestão de Operações, SGO). Among other attributions, this system allows to manage the lyfe-cycle of the urban fire events, from ignition to extinction, through the Operations Decision Support System (Sistema de Apoio à Decisão Operacional, SADO). This system supports the systematic collection of a minimum set of data on each event. All instances included in the dataset were retrieved from SADO. To make the data suitable for analytic purposes, several pre-processing actions were taken, including the steps of data transformation and cleaning. The dataset was further validated by a set of technical procedures aiming to verify both data correctness and utility. The final dataset provides the most recent multi-year record of Portuguese urban fires including 27 variables on 72641 events.

Soil Quality Assessment in Response to Water Erosion and Mining Activity

Erosion significantly decreases the depth of a soil, the nutrients available for plants, the organic matter and, consequently, the productivity of the edaphic environment. Due to the above considerations, the objective of this study was to evaluate, through various properties, the quality of two eroded soils, one eroded by water and the other by mining activity, amended with biosolids. The quality for both soils was estimated through the selection of a minimum set of data by means of principal component analysis (PCA) and the subsequent realization of correlations, multiple regressions and finally calculations of normalized values (Vn) of those properties considered as indicators of soil quality. According to the results, inorganic nitrogen (NI) and respiratory activity (RA) were the properties selected as indicators to assess quality. For soil eroded by water and by mining activity, NI presented a low and very low quality, respectively (class 4 and 5 of quality according to the calculation of Vn). The quality of RA in soil eroded by mining extraction was very high (quality class 1 according to Vn), and thus it can be considered an ideal indicator for the evaluation of soil quality due to its sensitivity to anthropogenic changes (mining) in soil.

Development of a Minimum Data Set for Dental Implants Registry.

Objectives: Registries are powerful tools for the collection and distribution of valid and reliable data. The initial step in health information management is to design a minimum data set that can improve the collection of high-quality data from the registry. The present pilot study aimed to determine the optimal minimum data set for dental implants to effectively utilize at Tehran University of Medical Sciences, Tehran, Iran. Materials and Methods: This descriptive cross-sectional study was conducted in 2019 at Tehran University of Medical Sciences. A minimum data set checklist was developed based on our previous systematic review. The content validity of the minimum data set was approved by the recruited experts and the final minimum data set was established using the Delphi technique. Results: The minimum data set for dental implants consists of two separate sections - administrative and clinical data. The administrative portion includes two main segments: patient demographic data and clinic data, consisting of 12 data elements. The clinical part includes five main segments (patient clinical data, implant data, implant complications, implant loss, and implant follow-up), and contains 96 data elements. Conclusion: This study suggests a minimum set of data for dental implants that can aid in efficient management of information, facilitate evidence-based decision-making, and enable high-quality clinical research, evaluation of treatment results, monitoring, and benchmarking of care.

COMPARISON OF OPTIMIZATION STRATEGIES AND ESTIMATION TECHNIQUES FOR RADIO NETWORK PLANNING AND OPTIMIZATION PROBLEMS

Background. Radio network planning is one of the main phases of the cellular network lifecycle, as it determines capital and operating costs and allows system performance evaluation at any given time. An accurate and comprehensive analysis of existing network statistics is necessary for proper cell planning during network expansion. These statistics are collected throughout the life cycle of the cellular network and usually have certain imperfections (heterogeneity of statistics, which have different densities in different parts of the search space, up to the presence of significant voids, etc.) The system describing the functioning of the radio network can be represented as a black box because its internal processes are too complex to be defined by mathematical functions. This determines the need to use appropriate tools.
 Objective. The purpose of the paper is to create a toolkit that allows finding the proper relationships between network parameters to define target values that will help to build an effective network plan in terms of performance and costs for its creation and operation. The tools should be able to work efficiently using the minimum set of available statistical data, as well as taking into account their imperfections.
 Methods. Mathematical estimation and optimization methods are used, namely Ordinary Least Squares, Ridge Regression, Lasso, Elastic-net, LARS lasso, Bayesian Ridge Regression, Automatic Relevance Determination, Stochastic gradient descent, Theil-Sen estimator, Huber Regression, Quantile regression, Polynomial regression. We consider 12 estimation methods in combination with two optimization strategies. Additionally, the method of partial analysis of the search space with different number of configurations is considered.
 Results. A software package using the Python programming language has been created, which contains a practical implementation of all the considered estimation and optimization methods, as well as tools for evaluating arbitrary configurations of the software package (benchmark) and visualizing the results. The best estimation method is Ordinary Least Squares for finding the optimal configuration of the statistical parameters of the 4G radio network to maximize the download speed. To obtain satisfactory results, it is enough to consider 25 initial and 250 estimated points - a larger number of points will not significantly increase prediction accuracy.
 Conclusions. The results indicate the possibility of using the created software package for radio network planning tasks. Further research is aimed at expanding the created software package's functionality and considering additional estimation methods and optimization strategies.
 Keywords: radio network planning; radio network optimization; cellular networks; estimation techniques; optimization strategies; big data; 2G; 3G; 4G; CQI; capacity.

Identifying and validating the educational needs to develop a Celiac Self-Care System

BackgroundCeliac disease is a major public health problem in many countries, including Iran. Considering the disease’s exponential spread throughout the world and its risk factors, identifying the educational priorities and minimum data required to control and treat the disease is of great significance.MethodsThe present study was conducted in two phases in 2022. In the first phase, a questionnaire was developed based on the information obtained from a review of the literature. Later, the questionnaire was administered to 12 pundits in the fields of nutrition (n = 5), internal medicine (n = 4), and gastroenterology (n = 3). As a result, the necessary and important educational content was determined for developing the Celiac Self-Care System.ResultsAccording to the experts’ viewpoints, the educational needs of patients were classified into nine categories of demographic information, clinical information, long-term complications, comorbidity, tests, medications, dietary recommendations, general recommendations, technical capabilities as well as 105 subcategories.ConclusionsDue to the increased prevalence of Celiac disease and the lack of an established minimum set of data, determining the required educational information is of great importance at the national level. Such information could be useful in implementing educational health programs to raise the public level of awareness. In the field of education, such contents can be employed in planning new technology based on mobile phones (mobile health), preparing registries, and producing widely used content.

Designing a minimum data set of laboratory data for the electronic summary sheet of pediatric ward in Iran: A cross-sectional study.

Iranian hospitals are provided with hospital information systems (HISs) from different vendors, which make it hardly possible to summarize laboratory data in an consistent manner. Therefore, there is a need to design a minimum data set of laboratory data that will define standard criteria and reduce potential medical errors. The purpose of this study was to design a minimum data set (MDS) of laboratory data for an electronic summary sheet to be used in the pediatric ward of Iranian hospitals. This study consists of three phases. In the first phase, out of 3997 medical records from the pediatric ward, 604 summary sheets were chosen as sample. The laboratory data of these sheets were examined and the recorded tests were categorized. In the second phase, based on the types of diagnosis we developed a list of tests. Then we asked the physicians of the ward to select which ones should be documented for each patient's diagnosis. In the third phase, the tests that were reported in 21%-80% of the records, and were verified by the same percentage of physicians, were evaluated by the experts' panel. In the first phase, 10,224 laboratory data were extracted. Of these, 144 data elements reported in more than 80% of the records, and more than 80% of experts approved them to be included in the MDS for patients' summary sheet. After data elements were investigated in the experts' panel, 292 items were chosen for the final list of the data set. This MDS was designed such that, if implemented in hospital information systems, it could automatically enable registering data in the summary sheet when patient's diagnosis is registered.

DEVELOPMENT OF A SPECIALIZED SOFTWARE PACKAGE FOR NETWORK FORECAST OF FLOOD WATERS

Link for citation: Syryamkin V.I., Ivanenko B.P., Klestov S.A., Khilchuk M.D. Development of a specialized software package for neural network forecast of flood waters. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 5, рр.205-216. In Rus. The relevance of the study is caused by the need to develop modern methods of operational monitoring of the condition of territories due to the presence of various kinds of natural phenomena, in particular, floods and flood inundations. A lot of attention is paid to solving this problem by States, regions, municipalities and settlements. Purpose: development of a specialized software package designed to solve problems of short-term and medium-term flood water level forecasting based on operational data from hydrological observations with a minimum set of input data and with the ability to work with aerospace observation data. Objects: the area where the Tom and Ob rivers merge and downstream of the Ob river at the locations of hydrological posts: villages Pobeda, Nikolskoye, Molchanovo. Methods: neural network information modeling. Results. The paper considers the method of creating a neural network simulator designed for processing the results of hydrological measurements and solving a wide range of practical problems, including prognostic ones. An original method of constructing training samples was developed, which allows obtaining results with a minimum set of initial data. The authors investigated the efficiency and accuracy characteristics of neural network algorithms in solving the problem of forecasting the flood water level in the period from April 1 to June 30, 2011–2017.

Deep Neural Network for Detecting Fake Profiles in Social Networks

This paper proposes a deep neural network (DNN) approach for detecting fake profiles in social networks. The DNN model is trained on a large dataset of real and fake profiles and is designed to learn complex features and patterns that distinguish between the two types of profiles. In addition, the present research aims to determine the minimum set of profile data required for recognizing fake profiles on Facebook and propose the deep convolutional neural network method for fake accounts detection on social networks, which has been developed using 16 features based on content-based and profile-based features. The results demonstrated that the proposed method could detect fake profiles with an accuracy of 99.4%, equivalent to the achieved findings based on bigger data sets and more extensive profile information. The results were obtained with the minimum available profile data. In addition, in comparison with the other methods that use the same amount and kind of data, the proposed deep neural network gives an increase in accuracy of roughly 14%. The proposed model outperforms existing methods, achieving high accuracy and F1 score in identifying fake profiles. The associated findings indicate that the proposed model attained an average accuracy of 99% while considering two distinct scenarios: one with a single theme and another with a miscellaneous one. The results demonstrate the potential of DNNs in addressing the challenging problem of detecting fake profiles, which has significant implications for maintaining the authenticity and trustworthiness of online social networks.

Evaluation of the Performance Characteristics for SARS-CoV-2 S-RBD IgG Antibody Rapid Test Cassette (Fingerstick Whole Blood) by Comparing CLIA Test

Background: SARS-CoV-2, a branch of coronavirus, is a positive-strand RNA virus with four major proteins and several auxiliary proteins wrapped with genetic material. It mediates the invasion of the virus mainly through the binding of the S protein to host cell receptors and determines the organization of virus and host tropism. Human coronaviruses are one of the fastest-developing viruses due to their high genomic nucleotide substitution rate and recombination ability. Human coronaviruses are associated with a variety of respiratory diseases of varying severity, such as colds, pneumonia, and bronchitis. On January 30 2020, the World Health Organization (WHO) declared that the COVID-19 outbreak caused by SARS-CoV2 constituted a public health emergency of international concern (PHEIC) and characterized as a pandemic on March 11 2020. In an effort to expedite the availability of in vitro diagnostics (IVDs) needed in public health emergencies, the WHO has opened the development of an emergency use checklist process, which aims to assist procurement agencies and Member States in deciding whether a specific IVD is suitable for use based on a minimum set of available quality, safety and performance data. IVDs with guaranteed quality, safety and performance are a key component of the overall strategy to control the pandemic.Objective: The main purpose of this evaluation report is to investigate the sensitivity of the SARS-CoV-2 S-RBD IgG Antibody Rapid Test (Fingerstick Whole Blood) for diagnosis during COVID-19. Method: The SARS-CoV-2 S-RBD IgG Antibody Rapid Test (Fingerstick Whole Blood) is a rapid chromatographic immunoassay intended for the qualitative detection of IgG antibodies to SARS-CoV-2 spike (S) protein receptor binding domain (RBD) in human fingerstick whole blood approximately 10 days after vaccination. Result: Through the clinical evaluation of vaccinated, unvaccinated, and virus-uninfected populations, the results show that the overall relative sensitivity of SARS-CoV-2 S-RBD IgG Antibody Rapid Test (Fingerstick Whole Blood) is 97.7%, the relative specificity is 99.0%, and the relative accuracy is 98.5%. Conclusion: CITEST SARS-CoV-2 S-RBD IgG Antibody Rapid Test (Fingerstick Whole Blood) is a rapid test that is a qualitative membrane-based immunoassay intended to detect IgG antibodies to SARS-CoV-2 spike (S) protein receptor binding domain (RBD) in fingerstick whole blood. The product is simple to operate and has been validated against an industry leading commercial CLIA test to give results within 10 minutes of the sample being tested. A comparison of 1257 samples showed an accuracy of 98.5% and an excellent sensitivity of 97.7%. People can use the test kits to get accurate results and determine if they have antibodies in their bodies after they have been vaccinated.

Postoperative ventral hernia: characteristics of researching the results of prevention and surgical treatment

Aim. To assess the methodological quality of non-randomized interventional studies of the outcomes of prevention and surgical treatment of postoperative ventral hernias using a systematic approach.Material and methods. We searched the indexed literature for non-randomized studies of VН surgery from January 1995 to December 2019. Each prospective study was combined with a corresponding retrospective study using predefined criteria to obtain comparable groups. The assessment of the following components was conducted: the choices of research methods, their rationale, design, inclusion criteria, reported results, and statistical methodsResults and discussion. 50 studies (17,608 patients) were selected: 25 prospective and 25 retrospective. In general, prospective studies showed slightly higher methodological quality scores than retrospective studies, with a mean score of 17 (IQR: 14-18) versus 15 (IQR 12-18). The studied subcategories of prospective studies obtained higher median scores for their “administration”, “design” and “participants”. 18 (36%) studies had a primary outcome, and only 2 studies (4%) described research power. None of the studies mentioned a standardized definition of VH recurrence, while methods for detecting recurrence varied widely. The methodological quality of the study did not depend on the year of publication or the increase in the impact factor of the magazine.Conclusion. Currently, non-randomized interventional studies of the results of surgical treatment of VH are methodologically ineffective. A clearer analysis of the research results and the establishment of a minimum standardized set of data is necessary.