18 research outputs found
Strategic analysis of sustainable socioeconomic situation of rural areas in the Samara Region of the Russian Federation
On the one hand, the relevance of this problem is primarily determined by growing gap of rural territorial entities in socioeconomic development, and on the other hand, due to their significance in such prominent aspects for the country as food security, maintaining the existing land, industrial, ecological, demographic and human potential. The purpose of the article is comprehensive assessment of socioeconomic, institutional and ecological situation of rural areas in order to justify managerial decisions and effective policy making at the regional and local levels. The leading method for studying this problem is stratigic analysis of processes of developing rural areas, as well as factors, affecting development. The results of the study: In this article the authors assessed the situation in socioeconomic sphere of munitipalities in the Samara Region of the Russian Federation, accordingly, based on this, the authors concluded about a predominance of degradation processes, which form instability in the development of rural areas. The results of this study can be used by the regional authorities in their practice for making and implementation both regional policy, as well as strategy of socioeconomic development of rural area. Β© 2016 Belyaeva et al
Environmental risk to health of the population
Researches of the last years in the field of ecological epidemiology and the analysis of risk for health allow to claim with confidence that the polluted environment is one of the important factors defining changes of a state of health of the population. Expert opinions on the scale of this influence differ considerably now. These estimations vary from small shares of percent to several percent, reaching in some cases 30-50%. An attempt to elaborate economic approaches to a risk assessment to health of the population has been made in this work. The main reason which demands development of special approaches for an assessment of an environmental risk is that quantitative estimation of risk for health from environmental pollution is difficult to be realized. As a rule, population is affected by the whole set of the polluting substances from the atmosphere, drinking water, food, etc. For effective risk management it is necessary to assess and compare diverse risks caused by action of various pollutants coming to an organism in different ways. The stated methodical materials give an idea of possibility of the stage-by-stage multilevel risk analysis at the solution of environmental problems. Further comparative analysis connected with definition and comparison of various dangers can be done by means of the results received at a risk evaluation stage. Β© 2016 Anopchenko et al
INFORMATIVNOST' OTsENKI GORMONAL'NOGO FONA I DENSITOMETRII DLYa DIAGNOSTIKI OSTEOPOROZA
Π¦Π΅Π»Ρ. ΠΡΠ΅Π½ΠΈΡΡ ΡΡΠΎΠ²Π΅Π½Ρ Π³ΠΎΡΠΌΠΎΠ½ΠΎΠ² ΡΡΠ°ΡΡΠ²ΡΡΡΠΈΡ
Π² ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ ΠΊΠΎΡΡΠ½ΠΎΠΉ ΡΠΊΠ°Π½ΠΈ ΠΈ Π½Π΅ΠΊΠΎΡΠΎΡΡΡ
Π±ΠΈΠΎΡ
ΠΈΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ°ΡΠΊΠ΅ΡΠΎΠ² Π΅Π΅ ΠΏΠΎΠ²ΡΠ΅ΠΆΠ΄Π΅Π½ΠΈΡ, Π° ΡΠ°ΠΊ ΠΆΠ΅ Π·Π½Π°ΡΠ΅Π½ΠΈΡ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ Π΄Π΅Π½ΡΠΈΡΠΎΠΌΠ΅ΡΡΠΈΠΈ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΡΠ°Π·Π»ΠΈΡΠ½ΠΎΠΉ ΡΡΠ°Π΄ΠΈΠ΅ΠΉ ΠΎΡΡΠ΅ΠΎΠΏΠΎΡΠΎΠ·Π°. ΠΠ°ΡΠ΅ΡΠΈΠ°Π» ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. Π ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΡΠΈΠ½ΠΈΠΌΠ°Π»ΠΈ ΡΡΠ°ΡΡΠΈΠ΅ 45 ΡΡΡΡΠΊΠΈΡ
ΠΆΠ΅Π½ΡΠΈΠ½, ΠΊΠΎΡΠΎΡΡΠ΅ Π±ΡΠ»ΠΈ ΡΠ°Π·Π΄Π΅Π»Π΅Π½Ρ Π½Π° 3 Π³ΡΡΠΏΠΏΡ: 1 Π³ΡΡΠΏΠΏΠ° - 15 ΡΡΠ»ΠΎΠ²Π½ΠΎ Π·Π΄ΠΎΡΠΎΠ²ΡΡ
, 2 Π³ΡΡΠΏΠΏΠ° - 15 ΠΆΠ΅Π½ΡΠΈΠ½ Ρ ΠΎΡΡΠ΅ΠΎΠΏΠ΅Π½ΠΈΠ΅ΠΉ ΠΈ 3 Π³ΡΡΠΏΠΏΠ° - 15 ΡΠ΅Π»ΠΎΠ²Π΅ΠΊ Ρ ΠΎΡΡΠ΅ΠΎΠΏΠΎΡΠΎΠ·ΠΎΠΌ, Π² Π²ΠΎΠ·ΡΠ°ΡΡΠ΅ ΠΎΡ 48 Π΄ΠΎ 60 Π»Π΅Ρ. ΠΠΈΠ½Π΅ΡΠ°Π»ΡΠ½Π°Ρ ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΡ ΠΊΠΎΡΡΠ½ΠΎΠΉ ΡΠΊΠ°Π½ΠΈ Π² ΡΠ΅ΠΉΠΊΠ΅ Π±Π΅Π΄ΡΠ° ΠΈ ΠΏΠΎΡΡΠ½ΠΈΡΠ½ΠΎΠΌ ΠΎΡΠ΄Π΅Π»Π΅ ΠΏΠΎΠ·Π²ΠΎΠ½ΠΎΡΠ½ΠΈΠΊΠ° ΡΡΡΠ°Π½Π°Π²Π»ΠΈΠ²Π°Π»Π°ΡΡ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΡΠ΅Π½ΡΠ³Π΅Π½ΠΎΠ²ΡΠΊΠΎΠΉ Π΄Π΅Π½ΡΠΈΡΠΎΠΌΠ΅ΡΡΠΈΠΈ ΠΏΠΎΡΡΠ΅Π΄ΡΡΠ²ΠΎΠΌ Π’-ΠΊΡΠΈΡΠ΅ΡΠΈΡ. Π ΡΡΠ²ΠΎΡΠΎΡΠΊΠ΅ ΠΊΡΠΎΠ²ΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ»ΠΈ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΡ ΠΊΠΎΡΡΠΈΠ·ΠΎΠ»Π°, ΠΎΠ±ΡΠ΅Π³ΠΎ ΡΡΠΈΠΉΠΎΠ΄ΡΠΈΡΠΎΠ½ΠΈΠ½Π°, ΠΏΠ°ΡΠ°-ΡΠΈΡΠ΅ΠΎΠΈΠ΄Π½ΠΎΠ³ΠΎ Π³ΠΎΡΠΌΠΎΠ½Π°, ΠΊΠ°Π»ΡΡΠΈΡΡΠΈΠΎΠ»Π° ΠΈ ΡΡΡΡΠ°Π΄ΠΈΠΎΠ»Π° ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΠΠ€Π. Π’Π°ΠΊΠΆΠ΅ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ»ΠΈ ΡΡΠΎΠ²Π½ΠΈ ΠΏΡΠΎΠ΄ΡΠΊΡΠΎΠ² ΡΠ°ΡΠΏΠ°Π΄Π° ΠΊΠΎΠ»Π»Π°Π³Π΅Π½Π°: Π‘-ΠΊΠΎΠ½ΡΠ΅Π²ΡΡ
ΡΠ΅Π»ΠΎΠΏΠ΅ΠΏΡΠΈΠ΄ΠΎΠ² ΠΊΠΎΠ»Π»Π°Π³Π΅Π½Π° I ΡΠΈΠΏΠ° ΠΈ ΠΏΠΈΡΠΈΠ΄ΠΎΠ½ΠΎΠ»ΠΈΠ½Π°. Π‘ΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΡΡ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΡ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΠΏΠ°ΠΊΠ΅ΡΠ° ΠΏΡΠΈΠΊΠ»Π°Π΄Π½ΡΡ
ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌ Statistica 6.0 for Windows. ΠΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠ΅ Π΄Π°Π½Π½ΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΠ»ΠΈ Π² Π²ΠΈΠ΄Π΅ ΠΌΠ΅Π΄ΠΈΠ°Π½Ρ Ρ Π²Π΅ΡΡ
Π½ΠΈΠΌ ΠΈ Π½ΠΈΠΆΠ½ΠΈΠΌ ΠΊΠ²Π°ΡΡΠΈΠ»ΡΠΌΠΈ (25-ΠΉ ΠΈ 75-ΠΉ ΠΏΡΠΎΡΠ΅Π½ΡΠΈΠ»ΠΈ) - Me (25;75). ΠΡΠΈ ΡΡΠ°Π²Π½Π΅Π½ΠΈΠΈ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π»ΠΈ ΠΊΡΠΈΡΠ΅ΡΠΈΠΈ ΠΠ°Π½Π½Π°-Π£ΠΈΡΠ½ΠΈ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΠ°Π½Π½ΡΠ΅ Π΄Π΅Π½ΡΠΈΡΠΎΠΌΠ΅ΡΡΠΈΠΈ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎ ΡΠ°Π·Π»ΠΈΡΠ°Π»ΠΈΡΡ Π²ΠΎ 2 ΠΈ 3 Π³ΡΡΠΏΠΏΠ°Ρ
ΠΆΠ΅Π½ΡΠΈΠ½ ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ Ρ ΠΊΠΎΠ½ΡΡΠΎΠ»Π΅ΠΌ (p<0,001) ΠΈ Π±ΡΠ»ΠΈ ΡΠ°Π²Π½Ρ ΠΏΠΎ Π’-ΠΊΡΠΈΡΠ΅ΡΠΈΡ ΡΠ΅ΠΉΠΊΠΈ Π±Π΅Π΄ΡΠ°: 0,90 [0,63; 1,23], -1,65 [-2,28; -0,78], -1,80 [-2,10; -1,20] SD; ΠΏΠΎ T-ΠΊΡΠΈΡΠ΅ΡΠΈΡ ΠΏΠΎΠ·Π²ΠΎΠ½ΠΎΡΠ½ΠΈΠΊΠ°: 0,35 [-0,18; 1,13], -1,95 [-3,50; -1,38], -1,15 [-2,30; 0] SD Π² 1, 2 ΠΈ 3 Π³ΡΡΠΏΠΏΠ°Ρ
ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΠΎ. ΠΠ°Π±ΠΎΡΠ°ΡΠΎΡΠ½ΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΈ, ΡΡΠΎ Ρ Π²ΡΠ΅Ρ
ΠΎΠ±ΡΠ»Π΅Π΄ΡΠ΅ΠΌΡΡ
Π»ΠΈΡ ΡΡΠΎΠ²Π½ΠΈ Π³ΠΎΡΠΌΠΎΠ½ΠΎΠ² Π±ΡΠ»ΠΈ Π² ΠΏΡΠ΅Π΄Π΅Π»Π°Ρ
ΡΠ΅ΡΠ΅ΡΠ΅Π½ΡΠ½ΡΡ
Π·Π½Π°ΡΠ΅Π½ΠΈΠΉ. Π‘ΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΠ΅ ΡΡΡΡΠ°Π΄ΠΈΠΎΠ»Π°, ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ Ρ ΠΊΠΎΠ½ΡΡΠΎΠ»Π΅ΠΌ, Π² Π³ΡΡΠΏΠΏΠ΅ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΎΡΡΠ΅ΠΎΠΏΠ΅Π½ΠΈΠ΅ΠΉ Π±ΡΠ»ΠΎ ΠΌΠ΅Π½ΡΡΠ΅ Π½Π° 15% (p=0,002), Π° Π² Π³ΡΡΠΏΠΏΠ΅ Ρ ΠΎΡΡΠ΅ΠΎΠΏΠΎΡΠΎΠ·ΠΎΠΌ - Π½Π° 8,4% (p=0,036). ΠΠ½Π°ΡΠ΅Π½ΠΈΡ ΠΊΠ°Π»ΡΡΠΈΡΡΠΈΠΎΠ»Π° Π±ΡΠ»ΠΈ Π²ΡΡΠ΅ Π½Π° 107% (p=0,001) Π²ΠΎ 2 Π³ΡΡΠΏΠΏΠ΅ ΠΈ Π½Π° 43% (p=0,036) - Π² ΡΡΠ΅ΡΡΠ΅ΠΉ ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ Ρ ΠΊΠΎΠ½ΡΡΠΎΠ»Π΅ΠΌ, ΠΈ ΠΊΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, Π²ΠΎ Π²ΡΠΎΡΠΎΠΉ Π²ΡΡΠ΅, ΡΠ΅ΠΌ Π² ΡΡΠ΅ΡΡΠ΅ΠΉ Π½Π° 31% (p=0,045). ΠΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΈ ΠΠ’Π ΡΠ°ΠΊΠΆΠ΅ Π±ΡΠ»Π° Π½Π°ΠΈΠ±ΠΎΠ»ΡΡΠ΅ΠΉ Π² Π³ΡΡΠΏΠΏΠ΅ Ρ ΠΎΡΡΠ΅ΠΎΠΏΠ΅Π½ΠΈΠ΅ΠΉ: Π½Π° 51% (p=0,002) Π±ΠΎΠ»ΡΡΠ΅ ΡΠ΅ΠΌ Π² ΠΊΠΎΠ½ΡΡΠΎΠ»Π΅. Π’Π°ΠΊΠΆΠ΅ Π±ΡΠ»ΠΈ ΡΠ°ΡΡΡΠΈΡΠ°Π½Ρ ΡΠΎΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΡ Π²Π΅Π»ΠΈΡΠΈΠ½ Π³ΠΎΡΠΌΠΎΠ½ΠΎΠ², ΡΡΠ°ΡΡΠ²ΡΡΡΠΈΡ
Π² ΠΊΠ°Π»ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΠΈ Π΄Π΅ΠΌΠΈΠ½ΠΈΡΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΠΊΠΎΡΡΠ½ΠΎΠΉ ΡΠΊΠ°Π½ΠΈ, Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠΈΠ΅ ΡΠ²ΡΠ·Ρ ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΊΠΎΡΡΠ½ΠΎ-ΡΡΡΡΠ°Π²Π½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ Ρ Π³ΠΎΡΠΌΠΎΠ½Π°Π»ΡΠ½ΡΠΌΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡΠΌΠΈ. ΠΠ°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π·Π½Π°ΡΠΈΠΌΡΠ΅ ΡΠ°Π·Π»ΠΈΡΠΈΡ Π²ΡΡΠ²Π»Π΅Π½Ρ Π² ΡΠΎΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ ΡΡΠΎΠ²Π½Π΅ΠΉ ΡΡΡΡΠ°Π΄ΠΈΠΎΠ»Π° ΠΈ ΠΏΠ°ΡΠ°ΡΠΈΡΠ΅ΠΎΠΈΠ΄Π½ΠΎΠ³ΠΎ Π³ΠΎΡΠΌΠΎΠ½Π°, ΠΊΠΎΡΠΎΡΡΠ΅ Π±ΡΠ»ΠΈ Π² Π³ΡΡΠΏΠΏΠ΅ Ρ ΠΎΡΡΠ΅ΠΎΠΏΠ΅Π½ΠΈΠ΅ΠΉ Π½Π° 46% (p=0,006), Π° Π² Π³ΡΡΠΏΠΏΠ΅ Ρ ΠΎΡΡΠ΅ΠΎΠΏΠΎΡΠΎΠ·ΠΎΠΌ Π½Π° 41% (p=0,041) Π½ΠΈΠΆΠ΅, ΡΠ΅ΠΌ Π² ΠΊΠΎΠ½ΡΡΠΎΠ»Π΅. ΠΠ°ΠΈΠ±ΠΎΠ»ΡΡΠΈΠ΅ Π³ΠΎΡΠΌΠΎΠ½Π°Π»ΡΠ½ΡΠ΅ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΠ΅Π³ΠΈΡΡΡΠΈΡΡΡΡΡΡ Π² Π³ΡΡΠΏΠΏΠ΅ Ρ ΠΎΡΡΠ΅ΠΎΠΏΠ΅Π½ΠΈΠ΅ΠΉ. ΠΠΎΡΡΡΠΈΡΠΈΠ΅Π½Ρ ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΡ ΡΡΡΡΠ°Π΄ΠΈΠΎΠ»Π° ΠΊ ΠΠ’Π Π³ΠΎΡΠΌΠΎΠ½Ρ Π² Π³ΡΡΠΏΠΏΠ΅ ΠΊΠΎΠ½ΡΡΠΎΠ»Ρ ΡΠΎΡΡΠ°Π²ΠΈΠ» 1,82 [1,10; 2,33], Π² Π³ΡΡΠΏΠΏΠ΅ Ρ ΠΎΡΡΠ΅ΠΎΠΏΠ΅Π½ΠΈΠ΅ΠΉ 0,99 [0,93; 1,06], Π° Ρ ΠΎΡΡΠ΅ΠΎΠΏΠΎΡΠΎΠ·ΠΎΠΌ 1,43 [1,01; 1,58]. ΠΡΠΈ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠΈ ΠΌΠ½ΠΎΠ³ΠΎΡΠ°ΠΊΡΠΎΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ² Π³ΠΎΡΠΌΠΎΠ½Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΡΠ°ΡΡΡΠ° ΠΈ Π±ΠΈΠΎΡ
ΠΈΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ°ΡΠΊΠ΅ΡΠΎΠ² ΠΏΠΎΠ²ΡΠ΅ΠΆΠ΄Π΅Π½ΠΈΡ ΠΊΠΎΡΡΠ½ΠΎΠΉ ΡΠΊΠ°Π½ΠΈ ΠΊ Π’-ΠΊΡΠΈΡΠ΅ΡΠΈΡ ΠΏΠΎΠ·Π²ΠΎΠ½ΠΎΡΠ½ΠΈΠΊΠ° ΠΈ ΡΠ΅ΠΉΠΊΠΈ Π±Π΅Π΄ΡΠ° ΡΡΡΠ°Π²ΠΈΠ»ΠΈ, ΡΡΠΎ ΡΠΎΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠ΅ ΡΡΡΡΠ°Π΄ΠΈΠΎΠ»Π° ΠΊ ΠΏΠ°ΡΠ°ΡΠΈΡΠ΅ΠΎΠ΄Π½ΠΎΠΌΡ Π³ΠΎΡΠΌΠΎΠ½Ρ ΠΈΠΌΠ΅Π΅Ρ ΡΠΈΠ»ΡΠ½ΡΡ ΡΠ²ΡΠ·Ρ Ρ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ΠΌ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΠΌΠΈΠ½Π΅ΡΠ°Π»ΡΠ½ΠΎΠΉ ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΠΈ ΠΏΠΎΠ·Π²ΠΎΠ½ΠΎΡΠ½ΠΈΠΊΠ° Π² ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
Π³ΡΡΠΏΠΏΠ°Ρ
ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ². ΠΡΠΎ ΠΏΠΎΠ΄ΡΠ²Π΅ΡΠΆΠ΄Π°Π΅Ρ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΡΠΎΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΡ Π² ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΡΠ°Π½Π½Π΅Π³ΠΎ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠ°ΡΠΊΠ΅ΡΠ° ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΎΡΡΠ΅ΠΎΠΏΠΎΡΠΎΠ·Π°. ΠΡΠ²ΠΎΠ΄Ρ. ΠΠ°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΡΠ΅Π»Π΅ΡΠΎΠΎΠ±ΡΠ°Π·Π½ΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡ Π² ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΡΠ°Π½Π½ΠΈΡ
Π±ΠΈΠΎΡ
ΠΈΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ°ΡΠΊΠ΅ΡΠΎΠ² ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΎΡΡΠ΅ΠΎΠΏΠΎΡΠΎΠ·Π° Ρ ΠΆΠ΅Π½ΡΠΈΠ½ ΡΡΠΎΠ²Π΅Π½Ρ ΠΏΠ°ΡΠ°ΡΠ³ΠΎΡΠΌΠΎΠ½Π°, ΡΡΡΡΠ°Π΄ΠΈΠΎΠ»Π° ΠΈ ΠΈΡ
ΡΠΎΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠ΅. ΠΠ½Π°ΡΠ΅Π½ΠΈΡ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ Π΄Π΅Π½ΡΠΈΡΠΎΠΌΠ΅ΡΡΠΈΠΈ ΠΏΠΎ Π’-ΠΊΡΠΈΡΠ΅ΡΠΈΡ ΡΠ΅ΠΉΠΊΠΈ Π±Π΅Π΄ΡΠ° Π² Π±ΠΎΠ»ΡΡΠ΅ΠΉ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΡΡΡ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ ΡΡΠΆΠ΅ΡΡΠΈ ΠΎΡΡΠ΅ΠΎΠΏΠΎΡΠΎΠ·Π°, Π½Π΅ΠΆΠ΅Π»ΠΈ Π²Π΅Π»ΠΈΡΠΈΠ½Ρ T-ΠΊΡΠΈΡΠ΅ΡΠΈΡ ΠΏΠΎΠ·Π²ΠΎΠ½ΠΎΡΠ½ΠΈΠΊΠ°
AGE-DEPENDING EFFICIENCY AND SAFETY OF TOPIRAMATE IN PATIENTS WITH DIFFERENT FORMS OF EPILEPSY
Abstract: the aim of the study was to analyst the efficiency and safety of topiramate in children and adult epileptic populations depending on the patientβs age and forms of epilepsy. 597 epileptic patients receiving topiramate (302 males, 295 females) aged from 2 up 57 years were followed with video-EEG control during the period of 2002-2012. Topiramate was effective at 66,2% of patients (n=395). Low efficiency was seen at 26,8% (n=160) patients. The aggravation effect has been noted at 7% (n=42) of patients. Drug compliance (for >1 year) was 61,8% (n=369). High efficiency in group 2-3 year (n=134) was 53,8% (n=72), low efficiency in 34,3% (n=46), aggravation β in 11,9% cases (n=16); in group >3-7 years (n=253) high efficiency 59,7% (n=151), low 32% (n=81), aggravation in 8,3% (n=21); in pediatric population >7 years (n=132) high efficiency 81,8% (n=108), low effect in 15,2% (n=20), and 3% aggravation (n=4); in adult population >18 years (n=78) the efficiency was 82,1% (n=64), low effect 16,6% (n=13) and aggravation in 1,3% (n=1). So, topiramate is highly effective medication in the therapy of idiopathic generalized epilepsies without absences and in symptomatic/cryptogenic focal forms of epilepsy. Topiramate could also be useful additional drug in the therapy of epileptic encephalopathies. With the increasing of patientsβ age the efficiency of topiramate raised, while the aggravation risks decreased. Peak of aggravation potential was seen in early childhood population and maximal effectiveness β in children up 7 years and adult population
Collection of samples from women at different stages of pregnancy to search for early biomarkers of preterm birth
Aim. To create a collection of samples from women at different stages of pregnancy to search for early biomarkers of preterm birth.Material and methods. In order to standardize the sample collection, standard operation procedures have been developed with a step-by-step protocol for each research member at the clinical (collection of medical data and biological material) and laboratory (transportation, sample preparation, storage, quality control) stages.Results. As of October 1, 2020, the collection includes peripheral blood samples from 182 women. Whole blood, serum, plasma, buffy coat and urine were collected during pregnancy, and placenta and umbilical cord blood samples β during labor. Clinical and medical history data was obtained about each pregnant woman, which includes data on the womanβs health status, the course and outcome of pregnancy. An electronic catalog has been created with information on samples (data on clinical characteristics and the number of aliquots of each sample type). The quality control (assessment of DNA and microRNA) was carried out, which showed the compliance of the obtained samples with the quality criteria and the preservation of initial characteristics during long-term storage. On the basis of collection, a study has begun to assess the level of microRNA expression in various types of biomaterial, in order to search for early biomarkers of premature birth.Conclusion. The creation of a collection of samples from pregnant women is a significant groundwork for future fundamental and applied research in various fields of biomedicine. This collection may provide an in-depth study of the pathogenesis of various pregnancy complications and the development of new methods for their diagnosis and treatment.