47 research outputs found
LOCAL TREATMENT OF PURULENT WOUNDS BY USE OF BANDAGE WITH STELLANIN-PEG 3%
Purpose: to improve the results of treatment of patients with purulent wounds by use of bandages with βStellanin-PEG 3%β.Materials and methods: the research groups included 55 patients with purulent wounds of different origin, local treatment which apply ointment Β«Levomekolβ² or Β«Stellanin-PEG 3%Β». To assess the effectiveness of the treatment we used vulnografy with the measurement area and the volume of the wound, cytology of the center and the edges of the wound, bacteriology at 1, 5 and 10 days.Results: when you use the ointment Β«Stellanin-PEG 3%Β» decline in terms of healing the wounds, surgical complications and length of stay in the hospital until 2 bed-days.Summary: a rapid decline in the number of microorganisms in the wound in treatment of Stellanin, plays a very important role in the healing process of wounds festering
Comparative analysis of self-assessment and objective state of health in students of junior courses of medical and humanitarian specialties
Aim of the study was to determine the level of self-assessment of health-related quality of life (HRQoL) and its relationship with the objective state of health in students of junior courses of medical and humanitarian specialties.Materials and methods. The study has been conducted at the Far Eastern Federal University (FEFU) and at the Pacific State Medical University (TSMU) since December 10, 2017 to June 10, 2018. It was attended by 479 students of junior (1-3) courses, of which 228 (47.5 %) studied medical specialties at FEFU and TSMU, 251 (52.5 %) studied humanitarian specialties (FEFU). The average age of students was 19.5 Β± 1.9 years, the average response rate - 94.2 %. The selection was carried out using the principles of gender-stratified randomization. The state of health of the students was assessed by the presence of chronic diseases and the level of the Charlson comorbidity index. In the collection of data used outpatient cards (Form 025/y); patient registration logs (Form 001-1/y); medical control cards of followup (Form 062/y). For the self-assessment of HRQoL, a questionnaire was used: Β«A short form of self-assessment of HRQoL, MOS SF-36v2Β» (Medical Outcomes Study Short Form version 2). The demographic and socio-economic status was determined using a special questionnaire.Results and discussion. HRQoL indicator in medical students turned out to be related to the frequency of seeking medical help (r = 0.75; p < 0.01), the comorbidity index (r = 0.43; p < 0.05) and the average number of chronic diseases among respondents (r = 0.49; p < 0.05). The relationship between the total HRQoL and the physical and mental components of QoL self-assessment also proved to be quite strong (r = 0.69; p < 0.01; r = 0.59; p < 0.01, respectively). In students of humanitarian specialties HRQoL appeared (in addition to the physical and mental component of QoL) to be interrelated only with the average number of chronic diseases (r = 0.69; p < 0.05). Thus, 76,0 % of students of medical and humanitarian specialties have undergone chronic diseases of internal organs in junior courses. Diseases of the digestive (30-33 %), urogenital (10-14 %), respiratory (7-10 %) and nervous systems (6-10 %) are most common in the student environment. HRQoL in the students of junior courses of medical and humanitarian specialties does not significantly differ and is rated by them as satisfactory
First national survey of anti-tuberculosis drug resistance in Azerbaijan and risk factors analysis.
SETTING: Civilian population of the Republic of Azerbaijan. OBJECTIVES: To determine patterns of anti-tuberculosis drug resistance among new and previously treated pulmonary tuberculosis (TB) cases, and explore their association with socio-demographic and clinical characteristics. DESIGN: National cross-sectional survey conducted in 2012-2013. RESULTS: Of 789 patients (549 new and 240 previously treated) who met the enrolment criteria, 231 (42%) new and 146 (61%) previously treated patients were resistant to any anti-tuberculosis drug; 72 (13%) new and 66 (28%) previously treated patients had multidrug-resistant TB (MDR-TB). Among MDR-TB cases, 38% of new and 46% of previously treated cases had pre-extensively drug-resistant TB (pre-XDR-TB) or XDR-TB. In previously treated cases, 51% of those who had failed treatment had MDR-TB, which was 15 times higher than in relapse cases (OR 15.2, 95%CI 6-39). The only characteristic significantly associated with MDR-TB was a history of previous treatment (OR 3.1, 95%CI 2.1-4.7); for this group, history of incarceration was an additional risk factor for MDR-TB (OR 2.8, 95%CI 1.1-7.4). CONCLUSION: Azerbaijan remains a high MDR-TB burden country. There is a need to implement countrywide control and innovative measures to accelerate early diagnosis of drug resistance in individual patients, improve treatment adherence and strengthen routine surveillance of drug resistance
Objective and subjective health indicators, associated with successful teaching students of younger courses of medical specialties
Objective: Π’ΠΎ study the relationship of performance with self-esteem of physical and mental health and the objective state of morbidity, taking into account the influence of demographic and socio-economic parameters of undergraduate medical students. Materials and methods: The study was conducted from 15.011.2017 to 15.06.2018 at the Far-Eastern Federal University and the Pacific State Medical University, 299 students took part in it 146 (48.8%) were male, and 153 (51.2%) were female, the average age was 21,2 (1.7) years. The average response rate was 94,8%. In the course of the study, the students independently answered the questionnaire of the self-assessment of the demographic, socioeconomic, medical, and behavioral status of a university student; Statistical analysis of the information obtained was carried out using the program βStatistica 6.0'. Result: The composite assessment of the KHSSS by the students of FEFU and TSMU practically coincided: 63.4 / 61.3 points (p 0.05). Taking into account the contribution of each parameter to the regression model, the performance was associated with the assessment of the conditions of learning and living (for the FVHU students: r = 0.035 (0.016), p <0.05; r = 0.061 (0.018), p <0.01; for the TSMU students (r = 0.038 (0.024), p <0.05; r = 0.078 (0.017), p <0.01)). In the combined sample, the strongest correlation was found between academic performance and the level of living and training conditions (11.31 (5.91-19.39), p <0.01); quality of life related to health (11.54 (5.23-17.32), p <0.01); the level of family income (5.93 (1.55-10.27), p <0.01) and a number of other indicators. Conclusion: The self-esteem of lifecycle health in young undergraduate medical students enrolled in FEFU and TSMU is in the range of normal values. The regression analysis conducted in the combined sample demonstrates a correlation between the learning success rate index and the KJVP scores, the conditions of learning and living, the quality of learning, the comorbidity index and the level of family income.Π¦Π΅Π»Ρ: ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Π²Π·Π°ΠΈΠΌΠΎΡΠ²ΡΠ·ΠΈ ΡΡΠΏΠ΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ Ρ ΡΠ°ΠΌΠΎΠΎΡΠ΅Π½ΠΊΠΎΠΉ ΡΠΈΠ·ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΈ ΠΏΡΠΈΡ
ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π·Π΄ΠΎΡΠΎΠ²ΡΡ ΠΈ ΠΎΠ±ΡΠ΅ΠΊΡΠΈΠ²Π½ΡΠΌ ΡΠΎΡΡΠΎΡΠ½ΠΈΠ΅ΠΌ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ, Ρ ΡΡΠ΅ΡΠΎΠΌ Π²Π»ΠΈΡΠ½ΠΈΡ Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ² Ρ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² ΠΌΠ»Π°Π΄ΡΠΈΡ
ΠΊΡΡΡΠΎΠ² ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΈΡ
ΡΠΏΠ΅ΡΠΈΠ°Π»ΡΠ½ΠΎΡΡΠ΅ΠΉ. ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ: ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡ Ρ 15.011.2017 ΠΏΠΎ 15.06.2018 Π³ΠΎΠ΄Π° Π² ΠΠ°Π»ΡΠ½Π΅Π²ΠΎΡΡΠΎΡΠ½ΠΎΠΌ ΡΠ΅Π΄Π΅ΡΠ°Π»ΡΠ½ΠΎΠΌ ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΠ΅ ΠΈ Π² Π’ΠΈΡ
ΠΎΠΎΠΊΠ΅Π°Π½ΡΠΊΠΎΠΌ ΠΠΎΡΡΠ΄Π°ΡΡΡΠ²Π΅Π½Π½ΠΎΠΌ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΎΠΌ ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΠ΅, Π² Π½Π΅ΠΌ ΠΏΡΠΈΠ½ΡΠ»ΠΈ ΡΡΠ°ΡΡΠΈΠ΅ 299 ΡΡΡΠ΄Π΅Π½ΡΠΎΠ²: 146 (48,8 %) ΠΌΡΠΆΡΠΊΠΎΠ³ΠΎ, ΠΈ 153 (51,2%) ΠΆΠ΅Π½ΡΠΊΠΎΠ³ΠΎ ΠΏΠΎΠ»Π°, ΡΡΠ΅Π΄Π½ΠΈΠΉ Π²ΠΎΠ·ΡΠ°ΡΡ ΡΠΎΡΡΠ°Π²ΠΈΠ» 21,2 (1,7) Π³ΠΎΠ΄Π°. Π‘ΡΠ΅Π΄Π½ΡΡ ΡΠ°ΡΡΠΎΡΠ° ΠΎΡΠΊΠ»ΠΈΠΊΠ° ΡΠΎΡΡΠ°Π²ΠΈΠ»Π° 94,8%. Π ΠΏΡΠΎΡΠ΅ΡΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ ΡΡΡΠ΄Π΅Π½ΡΡ ΡΠ°ΠΌΠΎΡΡΠΎΡΡΠ΅Π»ΡΠ½ΠΎ ΠΎΡΠ²Π΅ΡΠ°Π»ΠΈ Π½Π° Π²ΠΎΠΏΡΠΎΡΡ Π°Π½ΠΊΠ΅ΡΡ ΡΠ°ΠΌΠΎΠΎΡΠ΅Π½ΠΊΠΈ Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ, ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ, ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΎΠ³ΠΎ ΠΈ ΠΏΠΎΠ²Π΅Π΄Π΅Π½ΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΡΠ°ΡΡΡΠ° ΡΡΡΠ΄Π΅Π½ΡΠ° ΠΠ£ΠΠ°, ΠΈΠ½Π΄Π΅ΠΊΡ ΠΊΠΎΠΌΠΎΡΠ±ΠΈΠ΄Π½ΠΎΡΡΠΈ ΡΠ°ΡΡΡΠΈΡΡΠ²Π°Π»ΡΡ ΠΏΠΎ Π΄Π°Π½Π½ΡΠΌ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΎΠΉ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΠΈΠΈ (ΡΠΎΡΠΌΡ 025/Ρ; 001-1/Π£; 062/Ρ). Π‘ΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ Π±ΡΠ» ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΡ Β«Statistica 6.0Β». Π Π΅Π·ΡΠ»ΡΡΠ°Ρ ΠΠΎΠΌΠΏΠΎΠ·ΠΈΡΠ½Π°Ρ ΠΎΡΠ΅Π½ΠΊΠ° ΠΠΠ‘Π ΡΡΡΠ΄Π΅Π½ΡΠ°ΠΌΠΈ ΠΠΠ€Π£ ΠΈ Π’ΠΠΠ£ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈ ΡΠΎΠ²ΠΏΠ°Π΄Π°Π»Π°: 63,4/61,3 Π±Π°Π»Π»Π° (Ρ 0.05). Π‘ ΡΡΠ΅ΡΠΎΠΌ Π²ΠΊΠ»Π°Π΄Π° ΠΊΠ°ΠΆΠ΄ΠΎΠ³ΠΎ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠ° Π² ΠΌΠΎΠ΄Π΅Π»Ρ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΈ ΡΡΠΏΠ΅Π²Π°Π΅ΠΌΠΎΡΡΡ ΠΎΠΊΠ°Π·Π°Π»Π°ΡΡ ΡΠ²ΡΠ·Π°Π½Π½ΠΎΠΉ Ρ ΠΎΡΠ΅Π½ΠΊΠΎΠΉ ΡΡΠ»ΠΎΠ²ΠΈΠΉ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ ΠΈ ΠΏΡΠΎΠΆΠΈΠ²Π°Π½ΠΈΡ (Ρ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² ΠΠ€ΠΠ£: Π³= 0,035 (0,016), Ρ<0.05; Π³= 0,061 (0,018), Ρ<0.01; Ρ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² Π’ΠΠΠ£ (Π³= 0,038 (0,024), Ρ<0.05; Π³= 0,078 (0,017), Ρ<0.01)). Π ΠΎΠ±ΡΠ΅Π΄ΠΈΠ½Π΅Π½Π½ΠΎΠΉ Π²ΡΠ±ΠΎΡΠΊΠ΅ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΡΠΈΠ»ΡΠ½ΡΡ Π²Π·Π°ΠΈΠΌΠΎΡΠ²ΡΠ·Ρ ΡΠ΄Π°Π»ΠΎΡΡ ΠΎΠ±Π½Π°ΡΡΠΆΠΈΡΡ ΠΌΠ΅ΠΆΠ΄Ρ ΡΡΠΏΠ΅Π²Π°Π΅ΠΌΠΎΡΡΡΡ ΠΈ ΡΡΠΎΠ²Π½Π΅ΠΌ ΡΡΠ»ΠΎΠ²ΠΈΠΉ ΠΏΡΠΎΠΆΠΈΠ²Π°Π½ΠΈΡ ΠΈ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ (11.31 (5.91-19.39), Ρ<0.01); ΠΊΠ°ΡΠ΅ΡΡΠ²ΠΎΠΌ ΠΆΠΈΠ·Π½ΠΈ ΡΠ²ΡΠ·Π°Π½Π½ΡΠΌ ΡΠΎ Π·Π΄ΠΎΡΠΎΠ²ΡΠ΅ΠΌ (11.54 (5.23-17.32), Ρ<0.01); ΡΡΠΎΠ²Π½Π΅ΠΌ ΡΠ΅ΠΌΠ΅ΠΉΠ½ΠΎΠ³ΠΎ Π΄ΠΎΡ
ΠΎΠ΄Π° (5.93 (1.55-10.27), Ρ<0.01) ΠΈ ΡΡΠ΄ΠΎΠΌ Π΄ΡΡΠ³ΠΈΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ. ΠΡΠ²ΠΎΠ΄Ρ: Π‘Π°ΠΌΠΎΠΎΡΠ΅Π½ΠΊΠ° ΠΠΠ‘Π Ρ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² ΠΌΠ»Π°Π΄ΡΠΈΡ
ΠΊΡΡΡΠΎΠ² ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΈΡ
ΡΠΏΠ΅ΡΠΈΠ°Π»ΡΠ½ΠΎΡΡΠ΅ΠΉ, ΠΎΠ±ΡΡΠ°ΡΡΠΈΡ
ΡΡ Π² ΠΠΠ€Π£ ΠΈ Π’ΠΠΠ£ Π½Π°Ρ
ΠΎΠ΄ΠΈΡΡΡ Π² Π΄ΠΈΠ°ΠΏΠ°Π·ΠΎΠ½Π΅ Π½ΠΎΡΠΌΠ°Π»ΡΠ½ΡΡ
Π·Π½Π°ΡΠ΅Π½ΠΈΠΉ. Π Π΅Π³ΡΠ΅ΡΡΠΈΠΎΠ½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ·, ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΠΉ Π² ΠΎΠ±ΡΠ΅Π΄ΠΈΠ½Π΅Π½Π½ΠΎΠΉ Π²ΡΠ±ΠΎΡΠΊΠ΅, Π΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΡΠ΅Ρ ΠΊΠΎΡΡΠ΅Π»ΡΡΠΈΡ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ ΡΡΠΏΠ΅ΡΠ½ΠΎΡΡΠΈ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ Ρ ΠΎΡΠ΅Π½ΠΊΠ°ΠΌΠΈ ΠΠΠ‘Π, ΡΡΠ»ΠΎΠ²ΠΈΠΉ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ ΠΈ ΠΏΡΠΎΠΆΠΈΠ²Π°Π½ΠΈΡ, ΠΊΠ°ΡΠ΅ΡΡΠ²Π° ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ, ΠΈΠ½Π΄Π΅ΠΊΡΠΎΠΌ ΠΊΠΎΠΌΠΎΡΠ±ΠΈΠ΄Π½ΠΎΡΡΠΈ ΠΈ ΡΡΠΎΠ²Π½Π΅ΠΌ ΡΠ΅ΠΌΠ΅ΠΉΠ½ΠΎΠ³ΠΎ Π΄ΠΎΡ
ΠΎΠ΄Π°
ΠΠ°ΠΏΠ°ΡΠΎΡΠΊΠΎΠΏΠΈΡΠ΅ΡΠΊΠ°Ρ ΡΠ°Π΄ΠΈΠΊΠ°Π»ΡΠ½Π°Ρ Π½Π΅ΡΡΡΠΊΡΠΎΠΌΠΈΡ Ρ ΡΡΠΎΠΌΠ±ΡΠΊΡΠΎΠΌΠΈΠ΅ΠΉ ΠΈΠ· Π½ΠΈΠΆΠ½Π΅ΠΉ ΠΏΠΎΠ»ΠΎΠΉ Π²Π΅Π½Ρ I - III ΡΡΠΎΠ²Π½Ρ: ΠΎΠΏΡΡ ΠΎΠ΄Π½ΠΎΠ³ΠΎ ΡΠ΅Π½ΡΡΠ° ΠΈ ΠΎΠ±Π·ΠΎΡ Π»ΠΈΡΠ΅ΡΠ°ΡΡΡΡ.
Objective. Radical nephrectomy with thrombectomy of the inferior vena cava is the preferred treatment for renal cell carcinoma with an tumor thrombosis. We describe our experience and presentreview of the literature evaluating the feasibility and safety of laparoscopic nephrectomy with inferior vena cava thrombectomy.Materials and methods. The study included 37 patients who underwent laparoscopic radical nephrectomy with level IβIII thrombectomy for renal cell carcinoma in our institution from 2018 to 2021. We analyzed the clinical, radiographic, intraoperative, pathological and postoperative parameters of the patients. The literature was reviewed by the Medline search engine, PubMed, with a review of publications on laparoscopic radical nephrectomy with inferior vena cava levelIβIIIthrombectomy.Results. The mean operation time was 275 Β± 60.1 min, the median blood loss was 450 Β± 81.6 ml (β₯50 % of the circulating blood volume β 32.4 %). Intraoperative complications were observed during 10 (27.0 %) operations. Postoperative complications developed in 29.7 % of patients and reached gradesIIIβIV according to the ClavienβDindo scale on 13.0 % ill. All patients are activated according to the fast track rehabilitation program. The average hospital stay was 5 days. A literature review identified clinical cases and small series demonstrating the technical feasibility and safety of laparoscopic radical nephrectomy with thrombectomy in selected patients.Conclusion. Laparoscopic radical nephrectomy with thrombectomy is a technically feasible approach in carefully selected patients with level IβIII tumor thrombosis. Optimal patient selection, extensive experience in laparoscopy and specialized centers are essential for the safe use of thistechnique.Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ β ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΠΈΡΡ Π½Π΅ΠΏΠΎΡΡΠ΅Π΄ΡΡΠ²Π΅Π½Π½ΡΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ Π»Π°ΠΏΠ°ΡΠΎΡΠΊΠΎΠΏΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠ°Π΄ΠΈΠΊΠ°Π»ΡΠ½ΠΎΠΉ Π½Π΅ΡΡΡΠΊΡΠΎΠΌΠΈΠΈ Ρ ΡΡΠΎΠΌΠ±ΡΠΊΡΠΎΠΌΠΈΠ΅ΠΉ ΠΈΠ· Π½ΠΈΠΆΠ½Π΅ΠΉ ΠΏΠΎΠ»ΠΎΠΉ Π²Π΅Π½Ρ IβIII ΡΡΠΎΠ²Π½Π΅ΠΉ Π² ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΠΎΠ΄Π½ΠΎΠ³ΠΎ ΠΎΠ½ΠΊΠΎΡΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΡΠ°ΡΠΈΠΎΠ½Π°ΡΠ°.ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. Π ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Π±ΡΠ»ΠΈ Π²ΠΊΠ»ΡΡΠ΅Π½Ρ 37 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ², ΠΏΠ΅ΡΠ΅Π½Π΅ΡΡΠΈΡ
Π»Π°ΠΏΠ°ΡΠΎΡΠΊΠΎΠΏΠΈΡΠ΅ΡΠΊΡΡ ΡΠ°Π΄ΠΈΠΊΠ°Π»ΡΠ½ΡΡ Π½Π΅ΡΡΡΠΊΡΠΎΠΌΠΈΡ Ρ ΡΡΠΎΠΌΠ±ΡΠΊΡΠΎΠΌΠΈΠ΅ΠΉ ΠΈΠ· Π½ΠΈΠΆΠ½Π΅ΠΉ ΠΏΠΎΠ»ΠΎΠΉ Π²Π΅Π½Ρ IβIII ΡΡΠΎΠ²Π½Π΅ΠΉ ΠΏΠΎ ΠΏΠΎΠ²ΠΎΠ΄Ρ ΠΏΠΎΡΠ΅ΡΠ½ΠΎ-ΠΊΠ»Π΅ΡΠΎΡΠ½ΠΎΠ³ΠΎ ΡΠ°ΠΊΠ° Π² ΠΠΠΠ¦ ΠΎΠ½ΠΊΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΈΠΌ. Π.Π. ΠΠ΅ΡΡΠΎΠ²Π° Π² ΠΏΠ΅ΡΠΈΠΎΠ΄ Ρ 2018 ΠΏΠΎ 2021 Π³. ΠΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΈΠ΅, ΡΠ΅Π½ΡΠ³Π΅Π½ΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅, ΠΈΠ½ΡΡΠ°ΠΎΠΏΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅, ΠΏΠ°ΡΠΎΠΌΠΎΡΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΈ ΠΏΠΎΡΠ»Π΅ΠΎΠΏΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ². Π ΡΠΈΡΡΠ΅ΠΌΠ°Ρ
Medline ΠΈ PubMed Π²ΡΠΏΠΎΠ»Π½Π΅Π½ ΠΏΠΎΠΈΡΠΊ ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΉ, ΠΏΠΎΡΠ²ΡΡΠ΅Π½Π½ΡΡ
Π»Π°ΠΏΠ°ΡΠΎΡΠΊΠΎΠΏΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠ°Π΄ΠΈΠΊΠ°Π»ΡΠ½ΠΎΠΉ Π½Π΅ΡΡΡΠΊΡΠΎΠΌΠΈΠΈ Ρ ΡΡΠΎΠΌΠ±ΡΠΊΡΠΎΠΌΠΈΠ΅ΠΉ ΠΈΠ· Π½ΠΈΠΆΠ½Π΅ΠΉ ΠΏΠΎΠ»ΠΎΠΉ Π²Π΅Π½Ρ IβIII ΡΡΠΎΠ²Π½Π΅ΠΉ Π·Π° ΠΏΠΎΡΠ»Π΅Π΄Π½ΠΈΠ΅ 10 Π»Π΅Ρ.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. Π‘ΡΠ΅Π΄Π½Π΅Π΅ Π²ΡΠ΅ΠΌΡ ΠΎΠΏΠ΅ΡΠ°ΡΠΈΠΈ ΡΠΎΡΡΠ°Π²ΠΈΠ»ΠΎ 275 Β± 60,1 ΠΌΠΈΠ½, ΠΌΠ΅Π΄ΠΈΠ°Π½Π° ΠΎΠ±ΡΠ΅ΠΌΠ° ΠΊΡΠΎΠ²ΠΎΠΏΠΎΡΠ΅ΡΠΈ β 450 Β± 81,6 ΠΌΠ» (β₯50 % ΠΎΠ±ΡΠ΅ΠΌΠ° ΡΠΈΡΠΊΡΠ»ΠΈΡΡΡΡΠ΅ΠΉ ΠΊΡΠΎΠ²ΠΈ β 32,4 %). ΠΠ½ΡΡΠ°ΠΎΠΏΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΠΎΡΠ»ΠΎΠΆΠ½Π΅Π½ΠΈΡ ΠΎΡΠΌΠ΅ΡΠ΅Π½Ρ Π² 10 (27,0 %) ΡΠ»ΡΡΠ°ΡΡ
. ΠΠΎΡΠ»Π΅ΠΎΠΏΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½ΡΠ΅ ΠΎΡΠ»ΠΎΠΆΠ½Π΅Π½ΠΈΡ ΡΠ°Π·Π²ΠΈΠ»ΠΈΡΡ Ρ 29,7 % ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² ΠΈ Π΄ΠΎΡΡΠΈΠ³Π»ΠΈ IIIβIV ΡΡΠ΅ΠΏΠ΅Π½Π΅ΠΉ ΡΡΠΆΠ΅ΡΡΠΈ ΠΏΠΎ ΡΠΊΠ°Π»Π΅ ClavienβDindo Ρ 13,0 % Π±ΠΎΠ»ΡΠ½ΡΡ
. ΠΡΠ΅ ΠΏΠ°ΡΠΈΠ΅Π½ΡΡ Π°ΠΊΡΠΈΠ²ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ ΠΏΠΎ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ΅ ΡΡΠΊΠΎΡΠ΅Π½Π½ΠΎΠΉ ΡΠ΅Π°Π±ΠΈΠ»ΠΈΡΠ°ΡΠΈΠΈ fast track. Π‘ΡΠ΅Π΄Π½ΡΡ ΠΏΡΠΎΠ΄ΠΎΠ»ΠΆΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΡ ΠΏΡΠ΅Π±ΡΠ²Π°Π½ΠΈΡ Π² ΡΡΠ°ΡΠΈΠΎΠ½Π°ΡΠ΅ ΡΠΎΡΡΠ°Π²ΠΈΠ»Π° 5 ΡΡΡ. ΠΠ±Π·ΠΎΡ Π»ΠΈΡΠ΅ΡΠ°ΡΡΡΡ Π²ΡΡΠ²ΠΈΠ» ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ»ΡΡΠ°ΠΈ ΠΈ Π½Π΅Π±ΠΎΠ»ΡΡΠΈΠ΅ ΡΠ΅ΡΠΈΠΈ, Π΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΡΡΡΠΈΠ΅ ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΡΡ ΠΎΡΡΡΠ΅ΡΡΠ²ΠΈΠΌΠΎΡΡΡ ΠΈ Π±Π΅Π·ΠΎΠΏΠ°ΡΠ½ΠΎΡΡΡ Π»Π°ΠΏΠ°ΡΠΎΡΠΊΠΎΠΏΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠ°Π΄ΠΈΠΊΠ°Π»ΡΠ½ΠΎΠΉ Π½Π΅ΡΡΡΠΊΡΠΎΠΌΠΈΠΈ Ρ ΡΡΠΎΠΌΠ±ΡΠΊΡΠΎΠΌΠΈΠ΅ΠΉ Ρ ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΡ
ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ².ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. ΠΠ°ΠΏΠ°ΡΠΎΡΠΊΠΎΠΏΠΈΡΠ΅ΡΠΊΠ°Ρ ΡΠ°Π΄ΠΈΠΊΠ°Π»ΡΠ½Π°Ρ Π½Π΅ΡΡΡΠΊΡΠΎΠΌΠΈΡ Ρ ΡΡΠΎΠΌΠ±ΡΠΊΡΠΎΠΌΠΈΠ΅ΠΉ β ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈ ΠΎΡΡΡΠ΅ΡΡΠ²ΠΈΠΌΡΠΉ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ Ρ ΡΡΠ°ΡΠ΅Π»ΡΠ½ΠΎ ΠΎΡΠΎΠ±ΡΠ°Π½Π½ΡΡ
ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΠΌ ΡΡΠΎΠΌΠ±ΠΎΠΌ IβIII ΡΡΠΎΠ²Π½Π΅ΠΉ. ΠΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΠΉ ΠΎΡΠ±ΠΎΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ², ΠΎΠ±ΡΠΈΡΠ½ΡΠΉ ΠΎΠΏΡΡ Π»Π°ΠΏΠ°ΡΠΎΡΠΊΠΎΠΏΠΈΠΈ ΠΈ ΡΠΏΠ΅ΡΠΈΠ°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅ ΡΠ΅Π½ΡΡΡ ΡΠ²Π»ΡΡΡΡΡ ΠΏΡΠΈΠ½ΡΠΈΠΏΠΈΠ°Π»ΡΠ½ΡΠΌΠΈ ΡΠ»Π΅ΠΌΠ΅Π½ΡΠ°ΠΌΠΈ Π΄Π»Ρ Π±Π΅Π·ΠΎΠΏΠ°ΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΡΠΎΠ³ΠΎ ΠΌΠ΅ΡΠΎΠ΄Π°
ΠΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΎΠ΅ ΠΏpΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΌΠΈΠ½ΠΈΠΌaΠ»ΡΠ½ΠΎ ΠΈΠ½Π²Π°Π·ΠΈΠ²Π½ΡΡ ΠΌΠ΅ΡΠΎΠ΄oΠ² Π»Π΅ΡΠ΅Π½ΠΈΡ ΠΎΡΠ»ΠΎΠΆΠ½Π΅Π½Π½ΠΎΠ³ΠΎ ΠΎΡΡΡΠΎΠ³ΠΎ ΡΡΠΆΠ΅Π»ΠΎΠ³ΠΎ ΠΏΠ°Π½ΠΊΡΠ΅Π°ΡΠΈΡΠ°
Percutaneous interventions for the purpose of sanation of cavities of pancreatogenic destruction can be one of the ways to treat pancreatic necrosis. This leads to a rapid cleansing of the cavities and is an objective method of monitoring the stages of treatment. We present a case of successful treatment of infected pancreatic necrosis using minimally invasive, percutaneous, X-ray endovascular methods. Procedures performed: superselective embolization of the upper and lower pancreaticoduodenal arteries, embolization of the gastroduodenal artery, embolization of the splenic artery, selective catheterization and embolization of the left gastric artery with microemboli and coils.Π§ΡΠ΅ΡΠΊΠΎΠΆΠ½ΡΠ΅ Π²ΠΌΠ΅ΡΠ°ΡΠ΅Π»ΡΡΡΠ²Π° Ρ ΡΠ΅Π»ΡΡ ΡΠ°Π½Π°ΡΠΈΠΈ ΠΏΠΎΠ»ΠΎΡΡΠ΅ΠΉ ΠΏΠ°Π½ΠΊΡΠ΅Π°ΡΠΎΠ³Π΅Π½Π½ΠΎΠΉ Π΄Π΅ΡΡΡΡΠΊΡΠΈΠΈ ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ oΠ΄Π½ΠΈΠΌ ΠΈΠ· ΡΠΏoΡoΠ±ΠΎΠ² Π»Π΅ΡΠ΅Π½ΠΈΡ ΠΏΠ°Π½ΠΊΡΠ΅ΠΎΠ½Π΅ΠΊΡΠΎΠ·Π°. ΠΡΠΎ ΠΏΡΠΈΠ²ΠΎΠ΄ΠΈΡ ΠΊ Π±ΡΡΡΡΠΎΠΌΡ ΠΎΡΠΈΡΠ΅Π½ΠΈΡ ΠΏΠΎΠ»ΠΎΡΡΠ΅ΠΉ ΠΈ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΠ±ΡΠ΅ΠΊΡΠΈΠ²Π½ΡΠΌ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΠΊΠΎΠ½ΡΡΠΎΠ»Ρ ΡΡΠ°ΠΏΠΎΠ² Π»Π΅ΡΠ΅Π½ΠΈΡ. ΠΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ ΡΠ»ΡΡΠ°ΠΉ ΡΡΠΏΠ΅ΡΠ½ΠΎΠ³ΠΎ Π»Π΅ΡΠ΅Π½ΠΈΡ ΠΈΠ½ΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠ°Π½ΠΊΡΠ΅ΠΎΠ½Π΅ΠΊΡΠΎΠ·Π° Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΌΠΈΠ½ΠΈΠΌΠ°Π»ΡΠ½ΠΎ ΠΈΠ½Π²Π°Π·ΠΈΠ²Π½ΡΡ
Π²ΠΌΠ΅ΡΠ°ΡΠ΅Π»ΡΡΡΠ², ΡΡΠ΅ΡΠΊΠΎΠΆΠ½ΡΡ
, ΡΠ΅Π½ΡΠ³Π΅Π½ΡΠ½Π΄ΠΎΠ²Π°ΡΠΊΡΠ»ΡΡΠ½ΡΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ². ΠΡΠΏΠΎΠ»Π½Π΅Π½Ρ: ΡΡΠΏΠ΅ΡΡΠ΅Π»Π΅ΠΊΡΠΈΠ²Π½Π°Ρ ΡΠΌΠ±oΠ»ΠΈΠ·Π°ΡΠΈΡ Π²Π΅ΡΡ
Π½Π΅ΠΉ ΠΈ Π½ΠΈΠΆΠ½Π΅ΠΉ ΠΏΠΎΠ΄ΠΆΠ΅Π»ΡΠ΄ΠΎΡΠ½ΠΎ-Π΄Π²Π΅Π½Π°Π΄ΡΠ°ΡΠΈΠΏΠ΅ΡΡΡΠ½ΡΡ
Π°ΡΡΠ΅ΡΠΈΠΉ, ΡΠΌΠ±ΠΎΠ»ΠΈΠ·Π°ΡΠΈΡ ΠΆΠ΅Π»ΡΠ΄oΡΠ½ΠΎ-Π΄Π²Π΅Π½Π°Π΄ΡΠ°ΡΠΈΠΏΠ΅ΡΡΡΠ½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ, ΡΠΌΠ±ΠΎΠ»ΠΈΠ·Π°ΡΠΈΡ ΡΠ΅Π»Π΅Π·Π΅Π½ΠΎΡΠ½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ, ΡΠ΅Π»Π΅ΠΊΡΠΈΠ²Π½Π°Ρ ΠΊΠ°ΡΠ΅ΡΠ΅ΡΠΈΠ·Π°ΡΠΈΡ ΠΈ ΡΠΌΠ±ΠΎΠ»ΠΈΠ·Π°ΡΠΈΡ Π»Π΅Π²ΠΎΠΉ ΠΆΠ΅Π»ΡΠ΄oΡΠ½ΠΎΠΉ Π°ΡΡΠ΅ΡΠΈΠΈ ΠΌΠΈΠΊΡoΡΠΌΠ±ΠΎΠ»Π°ΠΌΠΈ ΠΈ ΡΠΏΠΈΡΠ°Π»ΡΠΌΠΈ
DETECTION OF OIL POLLUTION HOTSPOTS AND LEAK SOURCES THROUGH THE QUANTITATIVE ASSESSMENT OF THE PERSISTENCE AND TEMPORAL REPETITION OF REGULAR OIL SPILLS IN THE CASPIAN SEA USING REMOTE SENSING AND GIS
The main goal of this research was to detect oil spills, to determine the oil spill frequencies and to approximate oil leak sources
around the Oil Rocks Settlement, the Chilov and Pirallahi Islands in the Caspian Sea using 136 multi-temporal ENVISAT Advanced
Synthetic Aperture Radar Wide Swath Medium Resolution Images acquired during 2006-2010.
The following oil spill frequencies were observed around the Oil Rocks Settlement, the Chilov and Pirallahi Islands: 2-10 (3471.04
sq. km.), 11-20 (971.66 sq. km.), 21-50 (692.44 sq. km.), 51-128 (191.38 sq. km.). The most critical oil leak sources with the
frequency range of 41-128 were observed at the Oil Rocks Settlement. The exponential regression analysis between wind speeds and
oil slick areas detected from 136 multi-temporal ENVISAT images revealed the regression coefficient equal to 63%. The regression
model showed that larger oil spill areas were observed with decreasing wind speeds. The spatiotemporal patterns of currents in the
Caspian Sea explained the multi-directional spatial distribution of oil spills around Oil Rocks Settlement, the Chilov and Pirallahi
Islands. The linear regression analysis between detected oil spill frequencies and predicted oil contamination probability by the
stochastic model showed the positive trend with the regression coefficient of 30%