22 research outputs found
Π’ΡΠ±Π΅ΡΠΊΡΠ»Π΅Π· Ρ Π²Π·ΡΠΎΡΠ»ΡΡ ΠΈ Π΄Π΅ΡΠ΅ΠΉ Π² Π‘Π΅Π²Π΅ΡΠΎ-ΠΠ°ΠΏΠ°Π΄Π½ΠΎΠΌ ΡΠ΅Π΄Π΅ΡΠ°Π»ΡΠ½ΠΎΠΌ ΠΎΠΊΡΡΠ³Π΅: Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ° ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΠΈ ΠΊΡΠΈΡΠ΅ΡΠΈΠΈ ΠΈΡ ΠΎΡΠ΅Π½ΠΊΠΈ
The epidemic situation is monitored by numerous rates that may not reflect it objectively which will subsequently lead to higher incidence rates and severe forms of tuberculosis in both adults and children in the regions with the most unfavorable situation.The objective: to evaluate epidemiological rates for tuberculosis in the Northwestern Federal District to identify the most significant, and assess the epidemic situation in the region using these most significant rates.Subjects and Methods. We analyzed the main epidemiological rates of pediatric tuberculosis according to federal statistics (Forms 8 and 33) in 11 districts of the Northwestern District in 2019-2021. Annual figures were obtained from open demographic data of the state statistics (https://www.fedstat.ru). Statistical analysis was pe`rformed using the free software R (v.3.5.1) and the commercial Statistical Package for the Social Sciences (SPSS Statistics for Windows, Version 24.0, IBM Corp., 2016). Hierarchical cluster analysis and k-means clustering were used with the selection of the lowest and highest values of rates. A formula is proposed for calculating the coefficient of full coverage with preventive screening (COP) for tuberculosis of the population which allows adjusting the analyzed epidemic rates taking into account the maximum coverage of the population with preventive screening and determining the accuracy of previous analysis.Results. According to the data obtained, in 2017 and 2018, Vologda Oblast and Nenets Autonomous Okrug were epidemically favorable regions, while in 2020 and 2021 Kaliningrad, Leningrad and Novgorod Oblasts were regarded as favorable regions that were steadily improving their performance. Regions with unfavorable tuberculosis situation include Pskov Oblast, St. Petersburg and the Komi Republic. At the same time, the first two regions occupy this position stably from 2017 to 2021. The use of the coefficient of low coverage with screening for tuberculosis made it possible to determine that Murmansk Oblast, St. Petersburg, Leningrad and Pskov Oblasts in 2020 and 2021 are prognostically unfavorable regions despite a decline in official tuberculosis rates. The data obtained correlate with a high percentage of positive tests with the tuberculosis recombinant tuberculosis allergen (TRA) in children in the regions mentioned above.Conclusions. The analysis of the data clearly demonstrates the possibility of determining the epidemically most favorable or unfavorable regions using four rates: coverage with preventive screening, incidence in the adult population, incidence in children aged 0 to 17 years, and tuberculosis mortality. Cluster analysis using these rates, calculation of rates using the developed coefficient of low coverage with screening for tuberculosis, and analysis of positive results of TRA test in children allows identifying the most epidemically unfavorable regions, despite the decrease in some rates that can be regarded as favorable.ΠΠΎΠ½ΠΈΡΠΎΡΠΈΠ½Π³ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΈΡΡΠ°ΡΠΈΠΈ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΡΡΡ Ρ ΡΡΠ΅ΡΠΎΠΌ Π±ΠΎΠ»ΡΡΠΎΠ³ΠΎ ΡΠΈΡΠ»Π° ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΌΠΎΠ³ΡΡ Π½Π΅ ΡΠΎΠ²ΡΠ΅ΠΌ ΠΎΠ±ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎ ΠΎΡΡΠ°ΠΆΠ°ΡΡ Π΅Π΅, ΡΡΠΎ Π² ΠΏΠΎΡΠ»Π΅Π΄ΡΡΡΠ΅ΠΌ ΠΏΡΠΈΠ²Π΅Π΄Π΅Ρ ΠΊ ΠΏΠΎΠ²ΡΡΠ΅Π½ΠΈΡ ΡΡΠΎΠ²Π½Ρ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ ΠΈ ΠΏΠΎΡΠ²Π»Π΅Π½ΠΈΡ ΡΡΠΆΠ΅Π»ΡΡ
ΡΠΎΡΠΌ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π° ΠΊΠ°ΠΊ Ρ Π²Π·ΡΠΎΡΠ»ΠΎΠ³ΠΎ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ, ΡΠ°ΠΊ ΠΈ Ρ Π΄Π΅ΡΠ΅ΠΉ Π² Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π½Π΅Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΡΡ
ΡΠ΅Π³ΠΈΠΎΠ½Π°Ρ
.Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ: ΠΎΡΠ΅Π½ΠΊΠ° ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΠΏΠΎ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Ρ Π² Π‘Π΅Π²Π΅ΡΠΎ-ΠΠ°ΠΏΠ°Π΄Π½ΠΎΠΌ ΡΠ΅Π΄Π΅ΡΠ°Π»ΡΠ½ΠΎΠΌ ΠΎΠΊΡΡΠ³Π΅ Π΄Π»Ρ Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π·Π½Π°ΡΠΈΠΌΡΡ
, Π° ΡΠ°ΠΊΠΆΠ΅ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠΈΡΡΠ°ΡΠΈΠΈ Π² ΡΠ΅Π³ΠΈΠΎΠ½Π΅ Ρ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ΠΌ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π·Π½Π°ΡΠΈΠΌΡΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ.ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. ΠΡΠ» ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ Π°Π½Π°Π»ΠΈΠ· ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΠΏΠΎ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Ρ Ρ Π΄Π΅ΡΠ΅ΠΉ ΠΏΠΎ Π΄Π°Π½Π½ΡΠΌ ΡΠ΅Π΄Π΅ΡΠ°Π»ΡΠ½ΠΎΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ (ΡΠΎΡΠΌΡ β 8 ΠΈ β 33) Π² 11 ΠΎΠΊΡΡΠ³Π°Ρ
Π‘Π΅Π²Π΅ΡΠΎ-ΠΠ°ΠΏΠ°Π΄Π½ΠΎΠ³ΠΎ ΡΠ΅Π³ΠΈΠΎΠ½Π° Π·Π° ΠΏΠ΅ΡΠΈΠΎΠ΄ Ρ 2019 ΠΏΠΎ 2021 Π³. ΠΠΆΠ΅Π³ΠΎΠ΄Π½ΡΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ ΠΏΠΎΠ»ΡΡΠ΅Π½Ρ ΠΈΠ· ΠΎΡΠΊΡΡΡΡΡ
Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π΄Π°Π½Π½ΡΡ
Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ (https://www.fedstat.ru). Π‘ΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΡΡ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΡΠ²ΠΎΠ±ΠΎΠ΄Π½ΠΎΠΉ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠΉ ΡΡΠ΅Π΄Ρ Π²ΡΡΠΈΡΠ»Π΅Π½ΠΈΠΉ R (v.3.5.1) ΠΈ ΠΊΠΎΠΌΠΌΠ΅ΡΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΏΠ°ΠΊΠ΅ΡΠ° ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠ³ΠΎ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΡ Statistical Package for the Social Sciences (SPSS Statisticsfor Windows, Π²Π΅ΡΡΠΈΡ 24.0, IBM Corp., 2016). ΠΡΠΈΠΌΠ΅Π½ΡΠ»ΠΈΡΡ ΠΈΠ΅ΡΠ°ΡΡ
ΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΊΠ»Π°ΡΡΠ΅ΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΈ ΠΊΠ»Π°ΡΡΠ΅ΡΠΈΠ·Π°ΡΠΈΡ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ k-ΡΡΠ΅Π΄Π½ΠΈΡ
Ρ Π²ΡΠ±ΠΎΡΠΎΠΌ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π½ΠΈΠ·ΠΊΠΈΡ
ΠΈ Π²ΡΡΠΎΠΊΠΈΡ
Π·Π½Π°ΡΠ΅Π½ΠΈΠΉ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π° ΡΠΎΡΠΌΡΠ»Π° ΡΠ°ΡΡΠ΅ΡΠ° ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° ΠΏΠΎΠ»Π½ΠΎΠ³ΠΎ ΠΎΡ
Π²Π°ΡΠ° ΠΏΡΠΎΡΠΈΠ»Π°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ (ΠΠΠ) Π½Π° ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π· Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ, ΠΊΠΎΡΠΎΡΡΠΉ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΡΠΊΠΎΡΡΠ΅ΠΊΡΠΈΡΠΎΠ²Π°ΡΡ Π°Π½Π°Π»ΠΈΠ·ΠΈΡΡΠ΅ΠΌΡΠ΅ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ Ρ ΡΡΠ΅ΡΠΎΠΌ ΠΌΠ°ΠΊΡΠΈΠΌΠ°Π»ΡΠ½ΠΎ ΠΏΠΎΠ»Π½ΠΎΠ³ΠΎ ΠΎΡ
Π²Π°ΡΠ° Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΠΠΠ ΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΠΈΡΡ ΠΏΡΠ°Π²ΠΈΠ»ΡΠ½ΠΎΡΡΡ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠ°Π½Π΅Π΅ Π°Π½Π°Π»ΠΈΠ·Π°.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ. Π‘ΠΎΠ³Π»Π°ΡΠ½ΠΎ ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΠΌ Π΄Π°Π½Π½ΡΠΌ, Π² 2017 ΠΈ 2018 Π³. ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΈ Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΡΠΌΠΈ ΡΠ΅Π³ΠΈΠΎΠ½Π°ΠΌΠΈ Π±ΡΠ»ΠΈ ΠΠΎΠ»ΠΎΠ³ΠΎΠ΄ΡΠΊΠ°Ρ ΠΎΠ±Π»Π°ΡΡΡ ΠΈ ΠΠ΅Π½Π΅ΡΠΊΠΈΠΉ Π°Π²ΡΠΎΠ½ΠΎΠΌΠ½ΡΠΉ ΠΎΠΊΡΡΠ³, ΡΠΎΠ³Π΄Π° ΠΊΠ°ΠΊ Π² 2020 ΠΈ 2021 Π³. ΠΠ°Π»ΠΈΠ½ΠΈΠ½Π³ΡΠ°Π΄ΡΠΊΠ°Ρ, ΠΠ΅Π½ΠΈΠ½Π³ΡΠ°Π΄ΡΠΊΠ°Ρ ΠΈ ΠΠΎΠ²Π³ΠΎΡΠΎΠ΄ΡΠΊΠΈΠ΅ ΠΎΠ±Π»Π°ΡΡΠΈ ΡΠ°ΡΡΠ΅Π½Π΅Π½Ρ ΠΊΠ°ΠΊ Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΡΠ΅ ΡΠ΅Π³ΠΈΠΎΠ½Ρ, ΠΊΠΎΡΠΎΡΡΠ΅ ΡΡΠ°Π±ΠΈΠ»ΡΠ½ΠΎ ΡΠ»ΡΡΡΠ°ΡΡ ΡΠ²ΠΎΠΈ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ. Π Π½Π΅Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΡΠΌ ΡΠ΅Π³ΠΈΠΎΠ½Π°ΠΌ ΠΎΡΠ½ΠΎΡΡΡΡΡ ΠΡΠΊΠΎΠ²ΡΠΊΠ°Ρ ΠΎΠ±Π»Π°ΡΡΡ, Π³. Π‘Π°Π½ΠΊΡ-ΠΠ΅ΡΠ΅ΡΠ±ΡΡΠ³ ΠΈ Π Π΅ΡΠΏΡΠ±Π»ΠΈΠΊΠ° ΠΠΎΠΌΠΈ. ΠΡΠΈ ΡΡΠΎΠΌ ΠΏΠ΅ΡΠ²ΡΠ΅ Π΄Π²Π° ΡΠ΅Π³ΠΈΠΎΠ½Π° Π·Π°Π½ΠΈΠΌΠ°ΡΡ Π΄Π°Π½Π½ΡΡ ΠΏΠΎΠ·ΠΈΡΠΈΡ ΡΡΠ°Π±ΠΈΠ»ΡΠ½ΠΎ Ρ 2017 ΠΏΠΎ 2021 Π³. ΠΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° Π½ΠΈΠ·ΠΊΠΎΠ³ΠΎ ΠΎΡ
Π²Π°ΡΠ° ΠΠΠ Π½Π° ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π· ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΠΈΡΡ, ΡΡΠΎ ΠΡΡΠΌΠ°Π½ΡΠΊΠ°Ρ ΠΎΠ±Π»Π°ΡΡΡ, Π³. Π‘Π°Π½ΠΊΡ-ΠΠ΅ΡΠ΅ΡΠ±ΡΡΠ³, ΠΠ΅Π½ΠΈΠ½Π³ΡΠ°Π΄ΡΠΊΠ°Ρ ΠΈ ΠΡΠΊΠΎΠ²ΡΠΊΠ°Ρ ΠΎΠ±Π»Π°ΡΡΠΈ Π² 2020 ΠΈ 2021 Π³. ΡΠ²Π»ΡΡΡΡΡ ΠΏΡΠΎΠ³Π½ΠΎΡΡΠΈΡΠ΅ΡΠΊΠΈ Π½Π΅Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΡΠΌΠΈ ΡΠ΅Π³ΠΈΠΎΠ½Π°ΠΌΠΈ, Π½Π΅ΡΠΌΠΎΡΡΡ Π½Π° ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΠ΅ ΠΎΡΠΈΡΠΈΠ°Π»ΡΠ½ΡΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ ΠΏΠΎ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Ρ. ΠΠΎΠ»ΡΡΠ΅Π½Π½ΡΠ΅ Π΄Π°Π½Π½ΡΠ΅ ΠΊΠΎΡΡΠ΅Π»ΠΈΡΡΡΡ Ρ Π²ΡΡΠΎΠΊΠΈΠΌ ΠΏΡΠΎΡΠ΅Π½ΡΠΎΠΌ ΠΏΠΎΠ»ΠΎΠΆΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΏΡΠΎΠ± Ρ Π°Π»Π»Π΅ΡΠ³Π΅Π½ΠΎΠΌ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π½ΡΠΌ ΡΠ΅ΠΊΠΎΠΌΠ±ΠΈΠ½Π°Π½ΡΠ½ΡΠΌ (ΠΠ’Π ) Ρ Π΄Π΅ΡΠ΅ΠΉ Π² ΠΎΠ±ΠΎΠ·Π½Π°ΡΠ΅Π½Π½ΡΡ
Π²ΡΡΠ΅ ΡΠ΅Π³ΠΈΠΎΠ½Π°Ρ
.ΠΡΠ²ΠΎΠ΄Ρ. ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· Π΄Π°Π½Π½ΡΡ
Π½Π°Π³Π»ΡΠ΄Π½ΠΎ Π΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΡΠ΅Ρ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΈ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΡΡ
ΠΈΠ»ΠΈ Π½Π΅Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΡΡ
ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ², ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ ΡΠ΅ΡΡΡΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ: ΠΎΡ
Π²Π°Ρ ΠΠΠ, ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ Π²Π·ΡΠΎΡΠ»ΠΎΠ³ΠΎ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ, ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ Π΄Π΅ΡΡΠΊΠΎΠ³ΠΎ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ Π² Π²ΠΎΠ·ΡΠ°ΡΡΠ΅ ΠΎΡ 0 Π΄ΠΎ 17 Π»Π΅Ρ ΠΈ ΡΠΌΠ΅ΡΡΠ½ΠΎΡΡΡ ΠΎΡ ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π·Π°. ΠΠ»Π°ΡΡΠ΅ΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· Ρ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ΠΌ Π΄Π°Π½Π½ΡΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ, ΡΠ°ΡΡΠ΅Ρ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ Ρ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ΠΌ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΠΎΠ³ΠΎ ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° Π½ΠΈΠ·ΠΊΠΎΠ³ΠΎ ΠΎΡ
Π²Π°ΡΠ° ΠΠΠ Π½Π° ΡΡΠ±Π΅ΡΠΊΡΠ»Π΅Π· ΠΈ Π°Π½Π°Π»ΠΈΠ· ΠΏΠΎΠ»ΠΎΠΆΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΠΏΠΎ ΠΏΡΠΎΠ±Π΅ Ρ ΠΠ’Π Ρ Π΄Π΅ΡΠ΅ΠΉ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ Π²ΡΡΠ²ΠΈΡΡ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΈ Π½Π΅Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΡΠ΅ ΡΠ΅Π³ΠΈΠΎΠ½Ρ, Π½Π΅ΡΠΌΠΎΡΡΡ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΠ΅ ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΡΠ°ΡΡΠ΅Π½Π΅Π½Ρ ΠΊΠ°ΠΊ Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΡΠ΅
Current possibilities in the diagnosis of intrathoracic lymph node tuberculosis in children
Diagnosing tuberculosis in children is very difficult. There are no clear diagnostic criteria for intrathoracic lymph node (ITLN) tuberculosis, the most common form of tuberculosis in children (78%). Current immunological methods used in combination with computed tomography make it possible to characterize a childβs status more clearly and to establish a correct diagnosis. The positive results of immunological tests in the presence of Mycobacterium tuberculosis infection require a set of radiological examination. ITLN tuberculosis is characterized by the fact that one group or more contains single or multiple ITLNs that measure more than 5 cm and differ in structure and density in the presence of positive immunological tests (Diaskintest and QuantiFERON test)