19 research outputs found
Effects of Psychopathy on Neurocognitive Domains of Impulsivity in Abstinent Opiate and Stimulant Users
Background: Psychopathy and substance use disorders (SUDs) are both characterized by neurocognitive impairments reflecting higher levels of impulsivity such as reward-driven decision-making and deficient inhibitory control. Previous studies suggest that psychopathy may exacerbate decision-making deficits, but it may be unrelated to other neurocognitive impairments among substance dependent individuals (SDIs). The aim of the present study was to examine the role of psychopathy and its interpersonal-affective and impulsive-antisocial dimensions in moderating the relationships between dependence on different classes of drugs and neurocognitive domains of impulsivity.Method: We tested 693 participants (112 heroin mono-dependent individuals, 71 heroin polysubstance dependent individuals, 115 amphetamine mono-dependent individuals, 76 amphetamine polysubstance dependent individuals, and 319 non-substance dependent control individuals). Participants were administered the Psychopathy Checklist: Screening Version (PCL:SV) and seven neurocognitive tasks measuring impulsive choice/decision-making (Iowa Gambling Task; Cambridge Gambling Task; Kirby Delay Discounting Task; Balloon Analog Risk Task), and impulsive action/response inhibition (Go/No-Go Task, Immediate Memory Task, and Stop Signal Task).Results: A series of hierarchical multiple regressions revealed that the interpersonal-affective dimension of psychopathy moderated the association between decision-making, response inhibition and both amphetamine and heroin dependence, albeit differently. For amphetamine users, low levels of interpersonal-affective traits predicted poor decision-making on the Iowa Gambling Task and better response inhibition on the Stop Signal task. In contrast, in heroin users high interpersonal-affective psychopathy traits predicted lower risk taking on the Cambridge Gambling Task and better response inhibition on the Go/No-Go task. The impulsive-antisocial dimension of psychopathy predicted poor response inhibition in both amphetamine and heroin users.Conclusions: Our findings reveal that psychopathy and its dimensions had both common and unique effects on neurocognitive function in heroin and amphetamine dependent individuals. Our results suggest that the specific interactions between psychopathy dimensions and dependence on different classes of drugs may lead to either deficient or superior decision-making and response inhibition performance in SDIs, suggesting that psychopathy may paradoxically play a protective role for some neurocognitive functions in specific subtypes of substance users
Validation of the Substance Use Risk Profile Scale (SURPS) With Bulgarian Substance Dependent Individuals
Background: The Substance Use Risk Profile Scale (SURPS) is a 23-item self-report questionnaire that assesses four well-validated personality risk factors for substance misuse (Impulsivity, Sensation Seeking, Anxiety Sensitivity, and Hopelessness). While the SURPS has been used extensively with adolescents at risk for substance dependence, its properties with adult substance-dependent populations have been understudied. Further, the validity of the Bulgarian version of the SURPS has not been evaluated. The aims of the present study were to examine the factor structure of the Bulgarian version of the SURPS, its psychometric properties, and its ability to distinguish individuals with substance dependence from healthy controls.Methods: Participants included 238 individuals ages 18 to 50 (45% female): 36 βpureβ (i.e., mono-substance dependent) heroin users, 34 βpureβ amphetamine users, 32 polysubstance users, 64 controls with no history of substance dependence, 43 unaffected siblings of heroin users, and 29 unaffected siblings of amphetamine users. We explored the factor structure of the Bulgarian version of the SURPS with confirmatory factor analyses, examined its reliability and validity, and tested for group differences between substance dependent and non-dependent groups.Results: Confirmatory factor analyses (CFA) replicated the original four-factor model of the SURPS. The four subscales of the SURPS demonstrated good internal consistency (Cronbach's alphas ranged from 0.71 to 0.85) and adequate concurrent validity. Significant group differences were found on the Impulsivity and Sensation Seeking subscales, with the three substance dependent groups scoring higher than controls.Conclusions: The SURPS is a valid instrument for measuring personality risk for substance use disorders in the Bulgarian population. The Bulgarian version of the SURPS demonstrates adequate to good reliability, concurrent validity, and predictive validity. Its ability to distinguish between groups with and without a history of substance dependence was specific to externalizing traits such as Impulsivity and Sensation Seeking, on which opiate, stimulant, and polysubstance dependent individuals scored higher than non-dependent controls
Testing macroecological abundance patterns: The relationship between local abundance and range size, range position and climatic suitability among European vascular plants
Aim: A fundamental question in macroecology centres around understanding the relationship between species' local abundance and their distribution in geographical and climatic space (i.e. the multiβdimensional climatic space or climatic niche). Here, we tested three macroecological hypotheses that link local abundance to the following range properties: (a) the abundance-range size relationship, (b) the abundance-range centre relationship and (c) the abundance-suitability relationship. Location: Europe. Taxon: Vascular plants. Methods: Distribution range maps were extracted from the Chorological Database Halle to derive information on the range and niche sizes of 517 European vascular plant species. To estimate local abundance, we assessed samples from 744,513 vegetation plots in the European Vegetation Archive, where local species' abundance is available as plant cover per plot. We then calculated the 'centrality', that is, the distance between the location of the abundance observation and each species' range centre in geographical and climatic space. The climatic suitability of plot locations was estimated using coarseβgrain species distribution models (SDMs). The relationships between centrality or climatic suitability with abundance was tested using linear models and quantile regression. We summarized the overall trend across species' regression slopes from linear models and quantile regression using a metaβanalytical approach. Results: We did not detect any positive relationships between a species' mean local abundance and the size of its geographical range or climatic niche. Contrasting yet significant correlations were detected between abundance and centrality or climatic suitability among species. Main conclusions: Our results do not provide unequivocal support for any of the relationships tested, demonstrating that determining properties of species' distributions at large grains and extents might be of limited use for predicting local abundance, including current SDM approaches. We conclude that environmental factors influencing individual performance and local abundance are likely to differ from those factors driving plant species' distribution at coarse resolution and broad geographical extents
Filtering Knowledge: A Comparative Analysis of Information-Theoretical-Based Feature Selection Methods
The data used in machine learning algorithms strongly influences the algorithms' capabilities. Feature selection techniques can choose a set of columns that meet a certain learning goal. There is a wide variety of feature selection methods, however, the ones we cover in this comparative analysis are part of the information-theoretical-based family. We evaluate MIFS, MRMR, CIFE, and JMI using the machine learning algorithms Logistic Regression, XGBoost, and Support Vector Machines.Multiple datasets with a variety of feature types are used during evaluation. We find that MIFS and MRMR are 2-4 times faster than CIFE and JMI. MRMR and JMI choose columns that lead to significantly higher accuracy and lower root mean squared error earlier. The results we present here can help data scientists pick the right feature selection method depending on the datasets used.CSE3000 Research ProjectComputer Science and Engineerin
Concentration of Polyphenolic Antioxidants in Apple Juice and Extract Using Ultrafiltration
The aim of the present work was to study the potential of ultrafiltration with three polyacrylonitrile membranes (1, 10, and 25 kDa) to concentrate polyphenolic antioxidants in apple juice and extract. The permeate flux, total polyphenols, polyphenolic profile, phenolic acid content, and total antioxidant capacity were determined using the FRAP and DPPH tests, the content of water-soluble proteins during ultrafiltration was established, and the concentration factors and rejections were determined. The permeate flux decreased by increasing the volume reduction ratio and decreasing the molecular weight cut-off of the membranes. The concentration factor and rejection of polyphenolics increased with the increase in the volume reduction ratio (VRR) for all membranes and both liquids. The concentration and rejection effectiveness of the 1 kDa membrane was higher than those observed for 10 and 25 kDa during the ultrafiltration of the apple extract, while these values were comparable for 1 and 10 kDa during the ultrafiltration of the apple juice. The concentration factors and rejections of total polyphenols were higher in the extract than in the juice. Chlorogenic acid was the main compound in the polyphenol profile of apple juice. The total content of phenolic acids, determined by using HPLC, increased by 15–20% as a result of the membrane concentration, but the separation process did not significantly change the ratio between the individual compounds
Πortic regurgitation β hemodynamic changes and evaluation
ΠΠ»Π°ΠΏΠ½ΠΈΡΠ΅ ΡΡΡΠ΄Π΅ΡΠ½ΠΈ Π·Π°Π±ΠΎΠ»ΡΠ²Π°Π½ΠΈΡ ΡΠ° Π²ΠΎΠ΄Π΅ΡΠ° ΠΏΡΠΈΡΠΈΠ½Π° Π·Π° Π½Π°ΡΡΡΠ΅Π½ΠΈΡ Π² ΠΊΠ°ΡΠ΅ΡΡΠ²ΠΎΡΠΎ ΠΈ ΠΏΡΠΎΠ΄ΡΠ»ΠΆΠΈΡΠ΅Π»Π½ΠΎΡΡΡΠ° Π½Π° ΠΆΠΈΠ²ΠΎΡ. ΠΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΡΠ° ΠΈΠΌ Π²Π°ΡΠΈΡΠ° Π·Π½Π°ΡΠΈΡΠ΅Π»Π½ΠΎ Π² ΡΠ΅Π»ΠΈΡ ΡΠ²ΡΡ. ΠΡ ΠΈΠ·ΠΊΠ»ΡΡΠΈΡΠ΅Π»Π½ΠΎ Π²Π°ΠΆΠ½ΠΎ Π·Π½Π°ΡΠ΅Π½ΠΈΠ΅ Π΅ ΠΏΠΎΠ·Π½Π°Π²Π°Π½Π΅ΡΠΎ Π½Π° Ρ
Π΅ΠΌΠΎ- Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ½ΠΈΡΠ΅ ΠΏΡΠΎΠΌΠ΅Π½ΠΈ, Π΄ΠΎ ΠΊΠΎΠΈΡΠΎ Π²ΠΎΠ΄ΡΡ. Π’ΠΎΠ²Π° ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ²Π° ΠΏΡΠ°Π²ΠΈΠ»Π½ΠΎ ΠΈΠ·ΡΠ°Π±ΠΎΡΠ²Π°Π½Π΅ Π½Π° ΡΡΠ°ΡΠ΅Π³ΠΈΡ ΠΎΡΠ½ΠΎΡΠ½ΠΎ Π±ΡΠ΄Π΅ΡΠΈ ΠΈΠ½ΡΠ΅Ρ- Π²Π΅Π½ΡΠΈΠΈ Π²ΡΡΡ
Ρ ΠΊΠ»Π°ΠΏΠ½ΠΈΡ Π°ΠΏΠ°ΡΠ°Ρ. ΠΡΠ΅Π· ΠΏΠΎΡΠ»Π΅Π΄Π½ΠΈΡΠ΅ Π³ΠΎΠ΄ΠΈΠ½ΠΈ ΡΠ΅ ΠΎΡΠ±Π΅Π»ΡΠ·Π²Π° ΠΈΠ·ΠΊΠ»ΡΡΠΈΡΠ΅Π»Π΅Π½ Π½Π°ΠΏΡΠ΅Π΄ΡΠΊ Π² ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ²Π°Π½Π΅ΡΠΎΒ Π½Π° ΡΠ°Π·Π»ΠΈΡΠ½ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ Π² ΡΡΠ΅ΡΠ°ΡΠ° Π½Π° ΠΎΠΏΠ΅ΡΠ°ΡΠΈΠ²Π½ΠΎ ΠΈ ΠΈΠ½ΡΠ΅ΡΠ²Π΅Π½ΡΠΈΠΎΠ½Π°Π»Π½ΠΎΡΠΎ Π»Π΅ΡΠ΅Π½ΠΈΠ΅ Π½Π° ΠΊΠ»Π°ΠΏΠ½ΠΈΡΠ΅ Π·Π°Π±ΠΎΠ»ΡΠ²Π°Π½ΠΈΡ. Π ΡΠΎΠ·ΠΈ ΡΠ°Π·Π΄Π΅Π» Π½ΠΈΠ΅ ΡΠ΅ ΡΠΏΠΈΡΠ°ΠΌΠ΅ ΠΎΡΠ½ΠΎΠ²Π½ΠΎ Π½Π° Π°ΠΎΡΡΠ½Π°ΡΠ° ΡΠ΅Π³ΡΡΠ³ΠΈΡΠ°ΡΠΈΡ ΠΈ Π½Π΅ΠΉΠ½Π°ΡΠ° Π·Π½Π°ΡΠΈΠΌΠΎΡΡ. Valvular diseases are a leading cause of morbidity, mortality and impaired quality of life in all over the world with different epidemiology. It is extremely important to know the hemodynamic changes for the proper development of a strategy for future interventions. The recent years shows progress in various methodologies of the field of surgery and interventional treatments of valvular diseases. In this section, we focus mainly on aortic regurgitation and its clinical significance
Invasive hemodynamic assessment of patients with cardiomyopathies
ΠΠ½Π²Π°Π·ΠΈΠ²Π½Π°ΡΠ° Ρ
Π΅ΠΌΠΎΠ΄ΠΈΠ½Π°ΠΌΠΈΡΠ½Π° ΠΎΡΠ΅Π½ΠΊΠ° Π½Π° ΡΡΡΠ΄Π΅ΡΠ½ΠΈΡΠ΅ Π·Π°Π±ΠΎΠ»ΡΠ²Π°Π½ΠΈΡ ΠΏΡΠΈΠ΄ΠΎΠ±ΠΈΠ²Π° Π²ΡΠ΅ ΠΏΠΎ-Π³ΠΎΠ»ΡΠΌΠ° ΡΠΎΠ»Ρ ΠΏΡΠ΅Π· ΠΏΠΎΡΠ»Π΅Π΄Π½ΠΈ- ΡΠ΅ Π΄Π΅ΡΠ΅ΡΠΈΠ»Π΅ΡΠΈΡ. ΠΠΎΡΠ°Π΄ΠΈ ΠΏΠΎ-ΡΠΈΡΠΎΠΊΠ°ΡΠ° ΡΠΈ Π΄ΠΎΡΡΡΠΏΠ½ΠΎΡΡ ΠΈ Π±Π΅Π·ΠΎΠΏΠ°ΡΠ½ΠΎΡΡ Π½Π΅ΠΈΠ½Π²Π°Π·ΠΈΠ²Π½ΠΈΡΠ΅ ΡΠ΅Ρ
Π½ΠΈΠΊΠΈ ΡΠ° ΠΎΡΠ½ΠΎΠ²Π½ΠΈΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄ΠΈ, ΠΈΠ·ΠΏΠΎΠ»Π·Π²Π°ΡΠΈ ΡΠ΅ Π·Π° ΠΎΡΠ΅Π½ΠΊΠ° Π½Π° ΡΡΡΠ΄Π΅ΡΠ½Π°ΡΠ° ΡΡΠ½ΠΊΡΠΈΡ. Π₯Π΅ΠΌΠΎΠ΄ΠΈΠ½Π°ΠΌΠΈΡΠ½Π°ΡΠ° ΠΎΡΠ΅Π½ΠΊΠ° ΡΡΠ΅Π· ΡΡΡΠ΄Π΅ΡΠ½Π° ΠΊΠ°ΡΠ΅ΡΠ΅ΡΠΈΠ·Π°ΡΠΈΡ ΡΠ΅ ΠΏΡΠΈ- Π»Π°Π³Π° Π·Π° ΡΠ΅ΡΠ°Π²Π°Π½Π΅ Π½Π° Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠ½ΠΈ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠΈ, ΠΊΠΎΠΈΡΠΎ Π½Π΅ ΠΌΠΎΠ³Π°Ρ Π΄Π° Π±ΡΠ΄Π°Ρ ΡΠ΅ΡΠ΅Π½ΠΈ ΡΡΠ΅Π· ΡΡΡΠΈΠ½Π½ΠΈΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ. Π’ΠΎΠ·ΠΈ ΡΠΈΠΏ ΠΈΠ·ΡΠ»Π΅Π΄Π²Π°Π½Π΅ ΡΡΡΠ±Π²Π° Π΄Π° Π±ΡΠ΄Π΅ ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡΠ°Π»ΠΈΠ·ΠΈΡΠ°Π½ΠΎ ΡΠΏΡΡΠΌΠΎ ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΠΈΡΠ΅ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠΈ Π½Π° Π²ΡΠ΅ΠΊΠΈ ΠΏΠ°ΡΠΈΠ΅Π½Ρ ΠΈ Π±Π°Π·ΠΈΡΠ°Π½ΠΎ Π½Π° ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΈΡΠ΅ ΠΎΡ Π½Π΅ΠΈΠ½Π²Π°Π·ΠΈΠ²Π½ΠΈΡΠ΅ ΠΈΠ·ΡΠ»Π΅Π΄Π²Π°Π½ΠΈΡ ΡΠ΅Π·ΡΠ»ΡΠ°ΡΠΈ. ΠΠ½Π²Π°Π·ΠΈΠ²Π½Π°ΡΠ° Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠ° ΡΠ΅ ΠΈΠ·ΠΏΠΎΠ»Π·Π²Π° ΡΠΈΡΠΎΠΊΠΎ ΠΏΡΠΈ ΠΎΡΠ΅Π½ΠΊΠ°- ΡΠ° Π½Π° ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΈΡΠ΅ Ρ ΡΠ°Π·Π»ΠΈΡΠ½ΠΈ ΡΡΡΠ΄Π΅ΡΠ½ΠΎ-ΡΡΠ΄ΠΎΠ²ΠΈ Π·Π°Π±ΠΎΠ»ΡΠ²Π°Π½ΠΈΡ, Π²ΠΊΠ»ΡΡΠΈΡΠ΅Π»Π½ΠΎ ΠΈ ΠΊΠ°ΡΠ΄ΠΈΠΎΠΌΠΈΠΎΠΏΠ°ΡΠΈΠΈ. Π Π½Π°ΡΡΠΎΡΡΠΈΡ ΠΎΠ±Π·ΠΎΡ ΡΠ°Π·Π³Π»Π΅ΠΆΠ΄Π°ΠΌΠ΅ ΡΠΎΠ»ΡΡΠ° Π½Π° ΡΡΡΠ΄Π΅ΡΠ½Π°ΡΠ° ΠΊΠ°ΡΠ΅ΡΠ΅ΡΠΈΠ·Π°ΡΠΈΡ, Π½Π΅ΠΉΠ½ΠΈΡΠ΅ ΠΏΡΠ΅Π΄ΠΈΠΌΡΡΠ²Π° ΠΈ Π½Π΅Π΄ΠΎΡΡΠ°ΡΡΡΠΈ ΠΊΠ°ΡΠΎ ΡΠ°ΡΡ ΠΎΡ ΡΡΠ»ΠΎΡΡΠ½Π°ΡΠ° ΠΎΡΠ΅Π½ΠΊΠ° Π½Π° ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΈΡΠ΅ Ρ ΠΊΠ°ΡΠ΄ΠΈΠΎΠΌΠΈΠΎΠΏΠ°ΡΠΈΠΈ.Β Invasive hemodynamic assessment of cardiac diseases has become an important diagnostic tool in recent decades. Non-invasive methods are the main techniques used to assess cardiac function, due to their wider availability. Cardiac catheterization is useful when there are diagnostic problems that cannot be solved with routine methods. Cardiac catheterization should be individualized according to the specific problems of the patient and based on the results from non-invasive methods. Invasive diagnostics is used in the assessment of patients with various cardiovascular diseases, including cardiomyopathies. In this review, we consider the role of cardiac catheterization, its advantages and disadvantages as part of the overall assessment of patients with cardiomyopathies.
Survival of patients with cardiomyopathies
ΠΠ°ΡΠ΄ΠΈΠΎΠΌΠΈΠΎΠΏΠ°ΡΠΈΠΈΡΠ΅ ΡΠ° Ρ
Π΅ΡΠ΅ΡΠΎΠ³Π΅Π½Π½Π° Π³ΡΡΠΏΠ° Π·Π°Π±ΠΎΠ»ΡΠ²Π°Π½ΠΈΡ. ΠΡΠ½ΠΎΠ²Π½ΠΈΡΡ ΠΏΠ°ΡΠΎΠ³Π΅Π½Π΅ΡΠΈΡΠ΅Π½ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΡΠΌ Π΅ ΠΌΠΈΠΎΠΊΠ°ΡΠ΄Π½Π° ΡΠ²ΡΠ΅Π΄Π°, ΡΠ΅Π·ΡΠ»ΡΠ°Ρ Π½Π°ΠΉ-ΡΠ΅ΡΡΠΎ Π½Π° Π³Π΅Π½Π΅ΡΠΈΡΠ½ΠΈ ΠΌΡΡΠ°ΡΠΈΠΈ. Π’Π΅ ΡΠ° Π΅Π΄Π½Π° ΠΎΡ Π²ΠΎΠ΄Π΅ΡΠΈΡΠ΅ ΠΏΡΠΈΡΠΈΠ½ΠΈ Π·Π° ΡΠ°Π·Π²ΠΈΡΠΈΠ΅ Π½Π° ΡΡΡΠ΄Π΅ΡΠ½Π° Π½Π΅Π΄ΠΎΡΡΠ°ΡΡΡ- Π½ΠΎΡΡ, Π²Π½Π΅Π·Π°ΠΏΠ½Π° ΡΡΡΠ΄Π΅ΡΠ½Π° ΡΠΌΡΡΡ ΠΈ ΠΆΠΈΠ²ΠΎΡΠΎΠ·Π°ΡΡΡΠ°ΡΠ°Π²Π°ΡΠΈ Π°ΡΠΈΡΠΌΠΈΠΈ. ΠΡΠΎΠ³Π½ΠΎΠ·Π°ΡΠ° ΠΏΡΠΈ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΈΡΠ΅ Ρ ΠΊΠ°ΡΠ΄ΠΈΠΎΠΌΠΈΠΎΠΏΠ°ΡΠΈΠΈ ΡΠ΅ ΠΎΠΏΡΠ΅Π΄Π΅Π»Ρ ΠΎΡΠ½ΠΎΠ²Π½ΠΎ ΠΎΡ Π½Π°Π»ΠΈΡΠΈΠ΅ΡΠΎ ΠΈΠ»ΠΈ Π»ΠΈΠΏΡΠ°ΡΠ° Π½Π° ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈ ΡΠ°ΠΊΡΠΎΡΠΈ, Π°ΡΠΎΡΠΈΠΈΡΠ°Π½ΠΈ Ρ Π½Π΅Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΠΎ ΠΏΡΠΎΡΠΈΡΠ°Π½Π΅, ΠΊΠ°ΠΊΡΠΎ ΠΈ ΠΎΡ Π΅ΡΠ°ΠΏΠ° Π½Π° Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠΈΡΠ°Π½Π΅ΡΠΎ ΠΈΠΌ. ΠΡΠ΅ΠΆΠΈΠ²ΡΠ΅ΠΌΠΎΡΡΡΠ° ΠΏΡΠΈ ΠΎΡΠ΄Π΅Π»Π½ΠΈΡΠ΅ Π²ΠΈΠ΄ΠΎΠ²Π΅ ΠΊΠ°ΡΠ΄ΠΈΠΎΠΌΠΈΠΎΠΏΠ°ΡΠΈΠΈ Π΅ ΡΠ°Π·Π»ΠΈΡΠ½Π°, ΠΊΠ°ΡΠΎ Π²ΠΎΠ΄Π΅ΡΠ° ΠΏΡΠΈΡΠΈΠ½Π° Π·Π° ΠΏΠΎΠ²ΠΈΡΠ΅Π½Π° ΡΠΌΡΡΡΠ½ΠΎΡΡ Π΅ ΠΊΡΡΠ½ΠΎΡΠΎ ΠΎΡΠΊΡΠΈΠ²Π°Π½Π΅ Π½Π° Π·Π°Π±ΠΎΠ»ΡΠ²Π°Π½Π΅ΡΠΎ ΠΈ ΡΡΠΎΡΠ²Π΅ΡΠ½ΠΎ Π·Π°Π±Π°Π²Π΅Π½ΠΎΡΠΎ Π·Π°- ΠΏΠΎΡΠ²Π°Π½Π΅ Π½Π° Π»Π΅ΡΠ΅Π½ΠΈΠ΅. ΠΡΠ½ΠΎΠ²Π½ΠΈΡΠ΅ ΠΊΠ°ΡΠ΄ΠΈΠΎΠΌΠΈΠΎΠΏΠ°ΡΠΈΠΈ, ΡΠ°Π·Π³Π»Π΅Π΄Π°Π½ΠΈ Π² Π½Π°ΡΡΠΎΡΡΠΈΡ ΠΎΠ±Π·ΠΎΡ, ΡΠ° Ρ
ΠΈΠΏΠ΅ΡΡΡΠΎΡΠΈΡΠ½Π°, Π΄ΠΈΠ»Π°ΡΠΈΠ²Π½Π°, ΡΠ΅ΡΡΡΠΈΠΊΡΠΈΠ²Π½Π°, ΠΠ Π½Π΅ΠΊΠΎΠΌΠΏΠ°ΠΊΡΠ½ΠΎΡΡ ΠΈ Π°ΡΠΈΡΠΌΠΎΠ³Π΅Π½Π½Π° Π΄Π΅ΡΠ½ΠΎΠΊΠ°ΠΌΠ΅ΡΠ½Π° ΠΊΠ°ΡΠ΄ΠΈΠΎΠΌΠΈΠΎΠΏΠ°ΡΠΈΡ. Cardiomyopathies are a heterogeneous group of diseases. The main pathogenetic mechanism is myocardial damage due to genetic mutations. Cardiomyopathies are one of the leading causes of heart failure, sudden cardiac death, and life-threatening arrhythmias. Certain factors associated with poor prognosis determined the prognosis in this group of patients. Survival in different types of cardiomyopathies depends on the time of diagnosis and initial treatment. The types of cardiomyopathies discussed in this review are hypertrophic cardiomyopathy, dilative cardiomyopathy, restrictive cardiomyopathy, left ventricle non-compaction, and arrhythmogenic right ventricular cardiomyopathy
Serum biomarkers for pulmonary hypertension
ΠΠ°Π»ΠΈΡΠ΅ ΡΠ° Π·Π½Π°ΡΠΈΠΌΠΈ ΠΈΠ·ΡΠ»Π΅Π΄Π²Π°Π½ΠΈΡ ΠΈ Π½Π°ΡΡΠ½ΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ, ΡΠ²ΡΡΠ·Π°Π½ΠΈ Ρ ΠΏΠ°ΡΠΎΡΠΈΠ·ΠΈΠΎΠ»ΠΎΠ³ΠΈΡΡΠ° Π½Π° ΠΏΡΠ»ΠΌΠΎΠ½Π°Π»Π½Π°ΡΠ° Ρ
ΠΈΠΏΠ΅ΡΡΠΎΠ½ΠΈΡ (ΠΠ₯), Π²ΡΠ»Π΅Π΄ΡΡΠ²ΠΈΠ΅ Π½Π° ΠΊΠΎΠ΅ΡΠΎ ΡΠ΅ ΡΠ²Π΅Π»ΠΈΡΠ°Π²Π°Ρ Π²ΡΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈΡΠ΅ Π·Π° ΡΠ΅ΡΠ°ΠΏΠ΅Π²ΡΠΈΡΠ½ΠΎΡΠΎ ΠΈ ΠΏΠΎΠ²Π»ΠΈΡΠ²Π°Π½Π΅. Π’ΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π½ΠΈΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄ΠΈ Π·Π° Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠ° ΠΈ ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΡΠ°Π½Π΅ Π½Π° ΠΠ₯ Π²ΠΊΠ»ΡΡΠ²Π°Ρ Π΅Ρ
ΠΎΠΊΠ°ΡΠ΄ΠΈΠΎΠ³ΡΠ°ΡΠΈΡ ΠΈ Π΄ΡΡΠ½Π° ΡΡΡΠ΄Π΅ΡΠ½Π° ΠΊΠ°ΡΠ΅ΡΠ΅ΡΠΈΠ·Π°ΡΠΈΡ, Π΄ΠΎΠΏΡΠ»Π½Π΅Π½ΠΈ ΠΎΡ ΠΎΡΠ΅Π½ΠΊΠ° Π½Π° ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½ΠΈΡ ΠΊΠ»Π°Ρ ΠΏΠΎ NYHA ΠΈ 6-ΠΌΠΈΠ½ΡΡΠ΅Π½ ΡΠ΅ΡΡ Ρ Ρ
ΠΎΠ΄Π΅Π½Π΅ (6 MWT). ΠΠ°ΡΠ°ΡΡΠ²Π°ΡΠΈΡΡ Π±ΡΠΎΠΉ ΡΠΈΡΠΊΡΠ»Π°ΡΠΎΡΠ½ΠΈ Π±ΠΈΠΎΠΌΠ°ΡΠΊΠ΅ΡΠΈ, ΠΊΠΎΠΈΡΠΎ ΡΠ΅ ΠΏΠΎΠ²ΠΈΡΠ°Π²Π°Ρ ΠΏΡΠΈ ΠΠ₯ ΠΌΠΎΠΆΠ΅ Π΄Π° ΠΏΠΎΠ΄ΠΏΠΎΠΌΠΎΠ³Π½Π΅ ΠΊΠ»ΠΈΠ½ΠΈΡΠΈΡΡΠΈΡΠ΅ ΠΊΠ°ΠΊΡΠΎ Π² Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠ°ΡΠ°, ΡΠ°ΠΊΠ° ΠΈ ΠΏΡΠΈ ΠΎΡΠ΅Π½ΠΊΠ° ΡΠ΅ΠΆΠ΅ΡΡΡΠ° Π½Π° Π·Π°Π±ΠΎΠ»ΡΠ²Π°Π½Π΅ΡΠΎ ΠΈ ΠΎΡΠ³ΠΎΠ²ΠΎΡΠ° ΠΎΡ Π»Π΅ΡΠ΅Π½ΠΈΠ΅ΡΠΎ. In the fi eld of development of pathophysiology of pulmonary hypertension, there are growing number of signifi cant recent advances, which leads to new therapeutic agents. Traditional methods of diagnosing and monitoring this condition have comprised echocardiography and right heart catheterization, in addition to functional measures, such as estimation of functional class and the 6-min walk test. An increasing number of biomarkers have been described that are elevated in pulmonary hypertension and which may assist the clinician in diagnosis and in the assessment of disease severity and response to treatment.