33 research outputs found

    Роль дисплазии Π³Π»Π΅Π½ΠΎΠΈΠ΄Π° Π² ΠΏΠ°Ρ‚ΠΎΠ³Π΅Π½Π΅Π·Π΅ хроничСской Π½Π΅ΡΡ‚Π°Π±ΠΈΠ»ΡŒΠ½ΠΎΡΡ‚ΠΈ ΠΏΠ»Π΅Ρ‡Π΅Π²ΠΎΠ³ΠΎ сустава

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    The purpose - to analyze computerized tomography data in patients with recurrent shoulder instability for signs of glenoid dysplasia. Methods. We studied the diagnostic data and the results of surgical treatment of 168 patients (137 men and 31 women) mostly of young age (under 30 years) who addressed to the clinic during the period from 2010 to 2014 with the symptoms of recurrent anterior shoulder instability. A risk group has been defined with alleged glenoid dysplasia in the amount of 27 patients who were studied by glenoid dimensions (height, width, area), glenoid version (anteversion, retroversion) and inclination angle of the glenoid. Results. In 22 cases, there has been a change in the normal anatomy of the glenoid as its excessive anteversion, increased angle of inclination, and decrease of its absolute area. Research has identified a pathogenic role of changes in the normal anatomy of the glenoid because recurrence of chronic instability in some cases after surgery, as well as in cases of nontraumatic instability in patients without anatomic lesions. Conclusions. Dysplastic changes of bony structures of the shoulder represent the risk factor for recurrent instability and can serve as one of the causes of recurrence after surgical treatment. When choosing a treatment strategy in patients of modern population is advisable to suggest the possible presence of dysplastic changes glenoid. In the event of recurrence after surgical treatment is shown holding computerized tomography to rule out dysplastic changes.ЦСль исслСдования - выявлСниС ΠΏΡ€ΠΈΠ·Π½Π°ΠΊΠΎΠ² дисплазии Π³Π»Π΅Π½ΠΎΠΈΠ΄Π° Ρƒ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с хроничСской Π½Π΅ΡΡ‚Π°Π±ΠΈΠ»ΡŒΠ½ΠΎΡΡ‚ΡŒΡŽ ΠΏΠ»Π΅Ρ‡Π΅Π²ΠΎΠ³ΠΎ сустава Π½Π° основании Π΄Π°Π½Π½Ρ‹Ρ… ΠΊΠΎΠΌΠΏΡŒΡŽΡ‚Π΅Ρ€Π½ΠΎΠΉ Ρ‚ΠΎΠΌΠΎΠ³Ρ€Π°Ρ„ΠΈΠΈ. ΠœΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π» ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹. Π‘Ρ‹Π»ΠΈ ΠΈΠ·ΡƒΡ‡Π΅Π½Ρ‹ диагностичСскиС Π΄Π°Π½Π½Ρ‹Π΅ ΠΈ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ хирургичСского лСчСния 168 ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² (137 ΠΌΡƒΠΆΡ‡ΠΈΠ½ ΠΈ 31 ΠΆΠ΅Π½Ρ‰ΠΈΠ½Π°) прСимущСствСнно ΠΌΠΎΠ»ΠΎΠ΄ΠΎΠ³ΠΎ возраста (Π΄ΠΎ 30 Π»Π΅Ρ‚), ΠΎΠ±Ρ€Π°Ρ‚ΠΈΠ²ΡˆΠΈΡ…ΡΡ Π² ΠΊΠ»ΠΈΠ½ΠΈΠΊΡƒ Π² ΠΏΠ΅Ρ€ΠΈΠΎΠ΄ с 2010 ΠΏΠΎ 2014 Π³. ΠΏΠΎ ΠΏΠΎΠ²ΠΎΠ΄Ρƒ симптомов Ρ€Π΅Ρ†ΠΈΠ΄ΠΈΠ²ΠΈΡ€ΡƒΡŽΡ‰Π΅ΠΉ ΠΏΠ΅Ρ€Π΅Π΄Π½Π΅ΠΉ Π½Π΅ΡΡ‚Π°Π±ΠΈΠ»ΡŒΠ½ΠΎΡΡ‚ΠΈ ΠΏΠ»Π΅Ρ‡Π΅Π²ΠΎΠ³ΠΎ сустава. Π‘Ρ‹Π»Π° Π²Ρ‹Π΄Π΅Π»Π΅Π½Π° Π³Ρ€ΡƒΠΏΠΏΠ° ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с ΠΏΡ€Π΅Π΄ΠΏΠΎΠ»Π°Π³Π°Π΅ΠΌΠΎΠΉ дисплазиСй Π³Π»Π΅Π½ΠΎΠΈΠ΄Π° Π² количСствС 27 ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ², Ρƒ ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… Π±Ρ‹Π»ΠΈ ΠΈΠ·ΡƒΡ‡Π΅Π½Ρ‹ Ρ€Π°Π·ΠΌΠ΅Ρ€Ρ‹ Π³Π»Π΅Π½ΠΎΠΈΠ΄Π° (высота, ΡˆΠΈΡ€ΠΈΠ½Π°, ΠΏΠ»ΠΎΡ‰Π°Π΄ΡŒ), ΠΏΠΎΠ²ΠΎΡ€ΠΎΡ‚ (антСвСрсия, рСтровСрсия) ΠΈ ΡƒΠ³ΠΎΠ» Π½Π°ΠΊΠ»ΠΎΠ½Π° Π³Π»Π΅Π½ΠΎΠΈΠ΄Π°. Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹. Π’ 22 случаях ΠΈΠΌΠ΅Π»ΠΎ мСсто ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ Π½ΠΎΡ€ΠΌΠ°Π»ΡŒΠ½ΠΎΠΉ Π°Π½Π°Ρ‚ΠΎΠΌΠΈΠΈ Π³Π»Π΅Π½ΠΎΠΈΠ΄Π° Π² Π²ΠΈΠ΄Π΅ Π΅Π³ΠΎ ΠΈΠ·Π±Ρ‹Ρ‚ΠΎΡ‡Π½ΠΎΠΉ антСвСрсии, ΡƒΠ²Π΅Π»ΠΈΡ‡Π΅Π½Π½ΠΎΠ³ΠΎ ΡƒΠ³Π»Π° Π½Π°ΠΊΠ»ΠΎΠ½Π° Π»ΠΈΠ±ΠΎ ΡƒΠΌΠ΅Π½ΡŒΡˆΠ΅Π½ΠΈΠ΅ Π΅Π³ΠΎ Π°Π±ΡΠΎΠ»ΡŽΡ‚Π½ΠΎΠΉ ΠΏΠ»ΠΎΡ‰Π°Π΄ΠΈ. ИсслСдованиС ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ ΠΎΠΏΡ€Π΅Π΄Π΅Π»ΠΈΡ‚ΡŒ ΠΏΠ°Ρ‚ΠΎΠ³Π΅Π½Π΅Ρ‚ΠΈΡ‡Π΅ΡΠΊΡƒΡŽ Ρ€ΠΎΠ»ΡŒ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½Π½ΠΎΠΉ Π½ΠΎΡ€ΠΌΠ°Π»ΡŒΠ½ΠΎΠΉ Π°Π½Π°Ρ‚ΠΎΠΌΠΈΠΈ Π³Π»Π΅Π½ΠΎΠΈΠ΄Π° Π² Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΠΈ Ρ€Π΅Ρ†ΠΈΠ΄ΠΈΠ²ΠΎΠ² хроничСской Π½Π΅ΡΡ‚Π°Π±ΠΈΠ»ΡŒΠ½ΠΎΡΡ‚ΠΈ Π² Π½Π΅ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… случаях послС ΠΎΠΏΠ΅Ρ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ лСчСния, Π° Ρ‚Π°ΠΊΠΆΠ΅ Π² случаях развития нСтравматичСской Π½Π΅ΡΡ‚Π°Π±ΠΈΠ»ΡŒΠ½ΠΎΡΡ‚ΠΈ Ρƒ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² Π±Π΅Π· анатомичСских ΠΏΠΎΠ²Ρ€Π΅ΠΆΠ΄Π΅Π½ΠΈΠΉ. Π’Ρ‹Π²ΠΎΠ΄Ρ‹. ДиспластичСскиС измСнСния костных структур ΠΏΠ»Π΅Ρ‡Π΅Π²ΠΎΠ³ΠΎ сустава ΡΠ²Π»ΡΡŽΡ‚ΡΡ Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠΌ риска развития хроничСской Π½Π΅ΡΡ‚Π°Π±ΠΈΠ»ΡŒΠ½ΠΎΡΡ‚ΠΈ ΠΈ ΠΌΠΎΠ³ΡƒΡ‚ ΡΠ»ΡƒΠΆΠΈΡ‚ΡŒ ΠΎΠ΄Π½ΠΎΠΉ ΠΈΠ· ΠΏΡ€ΠΈΡ‡ΠΈΠ½ Ρ€Π΅Ρ†ΠΈΠ΄ΠΈΠ²ΠΎΠ² послС ΠΎΠΏΠ΅Ρ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ лСчСния. ΠŸΡ€ΠΈ Π²Ρ‹Π±ΠΎΡ€Π΅ Ρ‚Π°ΠΊΡ‚ΠΈΠΊΠΈ лСчСния Ρƒ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² соврСмСнной популяции цСлСсообразно ΠΏΡ€Π΅Π΄ΠΏΠΎΠ»Π°Π³Π°Ρ‚ΡŒ Π½Π°Π»ΠΈΡ‡ΠΈΠ΅ диспла- стичСских ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ Π³Π»Π΅Π½ΠΎΠΈΠ΄Π°. ΠŸΡ€ΠΈ Π²ΠΎΠ·Π½ΠΈΠΊΠ½ΠΎΠ²Π΅Π½ΠΈΠΈ Ρ€Π΅Ρ†ΠΈΠ΄ΠΈΠ²ΠΎΠ² послС ΠΎΠΏΠ΅Ρ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ лСчСния ΠΏΠΎΠΊΠ°Π·Π°Π½ΠΎ ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠ΅ ΠΊΠΎΠΌΠΏΡŒΡŽΡ‚Π΅Ρ€Π½ΠΎΠΉ Ρ‚ΠΎΠΌΠΎΠ³Ρ€Π°Ρ„ΠΈΠΈ для ΠΈΡΠΊΠ»ΡŽΡ‡Π΅Π½ΠΈΡ диспластичСских ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ

    Assessing the Influence of Environmental Parameters on Amur Tiger Distribution in the Russian Far East Using a MaxEnt Modeling Approach

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    A better understanding of which biological and anthropogenic parameters are strong predictors of suitable habitats for tigers will help address conservation planning in those areas, which is crucial for maintaining connectivity and preventing further population fragmentation. The aim of this study was to develop a spatial model based on a number of environmental and anthropogenic variables as well as tiger presence data from a 2005 large-scale winter survey to predict Amur tiger distribution within its range in the RFE. Modeling the geographic distribution of Amur tigers required an application of the MaxEnt algorithm using a dataset of 1027 tiger track records and a set of environmental variables, such as distance to rivers, elevation and habitat type, and anthropogenic variables, such as distance to forest and main roads, distance to settlements and vegetation cover change. The models were divided into two groups based on elevation and habitat type. Elevation (AUC = 0.821) appeared to be a better predictor of habitat suitability for tigers than habitat type (AUC = 0.784)
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