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INTRODUCTION: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have a favorable impact on the kidney function in patients with heart failure (HF), while there is no clear evidence of what factors predict this effect. The aim of the study was to identify plausible predictors for kidney function outcome among patients with HF and investigate their association with SGLT2i. METHODS: We prospectively enrolled 480 patients with type 2 diabetes mellitus (T2DM) treated with diet and metformin and concomitant chronic HF and followed them for 52 weeks. In the study, we determined kidney outcome as a composite of ≥ 40% reduced estimated glomerular filtration rate from baseline, newly diagnosed end-stage kidney disease or kidney replacement therapy. The relevant medical information and measurement of the biomarkers (N-terminal natriuretic pro-peptide, irisin, apelin, adropin, C-reactive protein, tumor necrosis factor-alpha) were collected at baseline and at the end of the study. RESULTS: The composite kidney outcome was detected in 88 (18.3%) patients of the entire population. All patients received guideline-recommended optimal therapy, which was adjusted to phenotype/severity of HF, cardiovascular risk and comorbidity profiles, and fasting glycemia. Levels of irisin, adropin and apelin significantly increased in patients without clinical endpoint, whereas in those with composite endpoint the biomarker levels exhibited a decrease with borderline statistical significance (p = 0.05). We noticed that irisin ≤ 4.50 ng/ml at baseline and a ≤ 15% increase in irisin serum levels added more valuable predictive information than the reference variable. However, the combination of irisin ≤ 4.50 ng/ml at baseline and ≤ 15% increase in irisin serum levels (area under curve = 0.91; 95% confidence interval = 0.87-0.95) improved the discriminative value of each biomarker alone. CONCLUSION: We suggest that low levels of irisin and its inadequate increase during administration of SGLT2i are promising predictors for unfavorable kidney outcome among patients with T2DM and concomitant HF.
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Compuestos de Bencidrilo , Diabetes Mellitus Tipo 2 , Glucósidos , Insuficiencia Cardíaca , Inhibidores del Cotransportador de Sodio-Glucosa 2 , Humanos , Diabetes Mellitus Tipo 2/complicaciones , Diabetes Mellitus Tipo 2/tratamiento farmacológico , Inhibidores del Cotransportador de Sodio-Glucosa 2/uso terapéutico , Fibronectinas/uso terapéutico , Apelina/uso terapéutico , Insuficiencia Cardíaca/complicaciones , Insuficiencia Cardíaca/tratamiento farmacológico , Enfermedad Crónica , Riñón , BiomarcadoresRESUMEN
BACKGROUND: Today, cardiovascular diseases cause 47% of all deaths among the European population, which is 4 million cases every year. In Ukraine, CAD accounts for 65% of the mortality rate from circulatory system diseases of the able-bodied population and is the main cause of disability. The aim of this study is to develop a medical expert system based on fuzzy sets for assessing the degree of coronary artery lesions in patients with coronary artery disease. METHODS: The method of using fuzzy sets for the implementation of an information expert system for solving the problems of medical diagnostics, in particular, when assessing the degree of anatomical lesion of the coronary arteries in patients with various forms of coronary artery disease, has been developed. RESULTS: The paper analyses the main areas of application of mathematical methods in medical diagnostics, and formulates the principles of diagnostics, based on fuzzy logic. The developed models and algorithms of medical diagnostics are based on the ideas and principles of artificial intelligence and knowledge engineering, the theory of experiment planning, the theory of fuzzy sets and linguistic variables. The expert system is tested on real data. Through research and comparison of the results of experts and the created medical expert system, the reliability of supporting the correct decision making of the medical expert system based on fuzzy sets for assessing the degree of anatomical lesion of the coronary arteries in patients with various forms of coronary artery disease with the assessment of experts was 95%, which shows the high efficiency of decision making. CONCLUSIONS: The practical value of the work lies in the possibility of using the automated expert system for the solution of the problems of medical diagnosis based on fuzzy logic for assessing the degree of anatomical lesion of the coronary arteries in patients with various forms of coronary artery disease. The proposed concept must be further validated for inter-rater consistency and reliability. Thus, it is promising to create expert medical systems based on fuzzy sets for assessing the degree of disease pathology.
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Enfermedades Cardiovasculares , Enfermedad de la Arteria Coronaria , Humanos , Sistemas Especialistas , Inteligencia Artificial , Enfermedad de la Arteria Coronaria/diagnóstico , Reproducibilidad de los Resultados , Lógica Difusa , AlgoritmosRESUMEN
We hypothesize that serum irisin can have additional discriminative potency for heart failure (HF) in individuals with type 2 diabetes mellitus (T2DM). The study group comprised 226 consecutive T2DM patients (153 patients with any HF phenotypes and 30 patients without HF) aged 41 to 65 years. The plasma levels N-terminal brain natriuretic pro-peptide (NT-proBNP) and irisin were detected by ELISA at the baseline of the study. We found that the most appropriate cut-off value of irisin (HF versus non-HF) were 10.4 ng/mL (area under curve [AUC] = 0.96, sensitivity = 81.0%, specificity = 88.0%; P = 0.0001). Cutoff point of NT-proBNP that distinguished patients with HF and without it was 750 pmol/L (AUC = 0.78; sensitivity = 72.7%, specificity 76.5%, p = 0.0001). Using multivariate comparative analysis we established that concentrations of irisin < 10.4 ng/mL (odds ration [OR] = 1.30; P = 0.001) and NT-proBNP > 750 pmol/mL (OR = 1.17; P = 0.042), left atrial volume index (LAVI) > 34 mL/m2 (OR = 1.06; P = 0.042) independently predicted HF. Irisin being added to NT-proBNP improved predictive modality for HF, whereas combination of NT-proBNP and LAVI > 34 mL/m2 did not. In conclusion, we established that irisin had independent predicted potency for HF in patients with established T2DM.
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This study analyzes the existing methods for studying nasal breathing. The aspects of verifying the results of rhinomanometric diagnostics according to the data of spiral computed tomography are considered, and the methodological features of dynamic posterior active rhinomanometry and the main indicators of respiration are also analyzed. The possibilities of testing respiratory olfactory disorders are considered, the analysis of errors in rhinomanometric measurements is carried out. In the conclusions, practical recommendations are given that have been developed for the design and operation of tools for functional diagnostics of nasal breathing disorders. It is advisable, according to the data of dynamic rhinomanometry, to assess the functioning of the nasal valve by the shape of the air flow rate signals during forced breathing and the structures of the soft palate by the residual nasopharyngeal pressure drop. It is imperative to take into account not only the maximum coefficient of aerodynamic nose drag, but also the values of the pressure drop and air flow rate in the area of transition to the turbulent quadratic flow regime. From the point of view of the physiology of the nasal response, it is necessary to look at the dynamic change to the current mode, given the hour of the forced response, so that it will ensure the maximum possible acidity in the legend. When planning functional rhinosurgical operations, it is necessary to apply the calculation method using computed tomography, which makes it possible to predict the functional result of surgery.
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Nariz , Respiración , Nariz/diagnóstico por imagen , Frecuencia Respiratoria , Rinomanometría , Tomografía Computarizada por Rayos XRESUMEN
Individual anatomical features of the paranasal sinuses and dentoalveolar system, the complexity of physiological and pathophysiological processes in this area, and the absence of actual standards of the norm and typical pathologies lead to the fact that differential diagnosis and assessment of the severity of the course of odontogenic sinusitis significantly depend on the measurement methods of significant indicators and have significant variability. Therefore, an urgent task is to expand the diagnostic capabilities of existing research methods, study the significance of the measured indicators, and substantiate the expediency of their use in the diagnosis of specific pathologies in an automated mode. Methods of digital filtering, image segmentation and analysis, fluid dynamics, and statistical and discriminant analysis were used. Preliminary differential diagnosis of odontogenic sinusitis can be performed by densitemetric analysis of tomographic images of the maxillary sinuses, performed using frontal multiplanar reconstructions according to a given algorithm. The very manifestation of the characteristic changes in the densitography of the maxillary sinus allows for the initiation of certain pathological processes and permits the development of the effectiveness of the diagnosis of the pathology of the sinus sinuses, which can be realized automatically in real life.
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Sinusitis Maxilar , Sinusitis , Tomografía Computarizada por Rayos X , Humanos , Seno Maxilar , Sinusitis Maxilar/diagnóstico por imagenRESUMEN
The purpose of this work is the authors' attempt to identify the main phases of information transformation in measurement channels on the example of an optical measurement channel with microprocessor control. The authors include such phases: hardware implementation and analytical representation of an optical sensor's converting functions and a current-to-voltage converter; based on the methods of experimental computer science, the converting functions and sensitivity are deduced, analytical dependences for estimation of a range of measurement are obtained. It is shown that the choice of information transmission type in the microprocessor measuring channel significantly affects the speed of the measuring channel. Based on the uncertainty in the form of entropy before and after measurements, the amount of information for measuring channels with optoelectronic sensors is estimated. The application of the results obtained in the work allows even at the design stage of physical and mathematical modeling to assess the basic static metrological characteristics of measuring channels, aimed at reducing the stage of development and debugging of hardware and software and standardization of their metrological characteristics.