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dc.contributor.authorKarakina, M. L.en
dc.contributor.authorShershnev, V. N.en
dc.contributor.authorКаракина, М. Л.ru
dc.contributor.authorШершнев, В. Н.ru
dc.date.accessioned2019-07-22T06:44:06Z-
dc.date.available2019-07-22T06:44:06Z-
dc.date.issued2016-
dc.identifier.citationКаракина М. Л. Многофакторный анализ «генеалогических маркеров» у взрослых с первичными иммунодефицитами / М. Л. Каракина, В. Н. Шершнев // Терапевтический архив. — 2016. — Т. 88. — №. 4. — С. 46-52.ru
dc.identifier.issn0040-3660-
dc.identifier.otherhttps://doi.org/10.17116/terarkh201688446-52pdf
dc.identifier.other1good_DOI
dc.identifier.otherb4c32d0a-6c91-42c0-a632-53156c2cdf6apure_uuid
dc.identifier.otherhttp://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=84997822219m
dc.identifier.urihttp://elar.urfu.ru/handle/10995/75159-
dc.description.abstractAim. To study the genealogy of adult patients with primary immunodeficiencies (PID) and to analyze its data in the relatives of these patients. Subjects and methods. A genealogical analysis was carried out in 74 adult patients with PID and 200 adults without this condition, by examining groups of signs in the relatives in at least 4 generations, the genealogical markers were an atypical infectious and inflammatory process; allergic diseases; autoimmune diseases; the presence of relatives with cancers; cases of reproductive dysfunction; deaths from infectious diseases and/or cancers in children; and congenital malformations. The percentage of relatives with the above genealogical markers of the total number of the relatives in 4 generations was used as an indicator. The analysis applied nonparametric methods, such as quartile analysis, Spearmans correlation coefficient, and Mann-Whitney test to verify the statistical significance of differences between the independent groups. Multifactor prediction models were based on the decision theory (Wald-Bayesian analysis) and classification trees. At Stage 1, the investigators made a univariate analysis, the data of which were used to perform a correlation analysis of the indicators. Multifactor prediction models were based on the decision theory (Wald-Bayesian analysis) and classification trees. Results. The genealogical markers were identified and analyzed using different statistical methods and conclusions were made on prognostically significant indicators. Conclusion. The findings may be recommended for practical use in order to enhance the efficiency of work with patients having various immunopathological syndromes.en
dc.format.mimetypeapplication/pdfen
dc.language.isoruen
dc.publisherMedia Sphera Publishing Houseen
dc.publisherИздательство «Медиа Сфера»ru
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.sourceTerapevticheskii Arkhiven
dc.sourceТерапевтический архивru
dc.subjectATYPICAL INFECTIOUS AND INFLAMMATORY PROCESSen
dc.subjectGENEALOGICAL MARKERSen
dc.subjectGENEALOGYen
dc.subjectMULTIVARIATE ANALYSISen
dc.subjectPRIMARY IMMUNODEFICIENCIESen
dc.subjectBIOLOGICAL MARKERen
dc.subjectADULTen
dc.subjectBAYES THEOREMen
dc.subjectGENETIC MARKERen
dc.subjectGENETICSen
dc.subjectHUMANen
dc.subjectIMMUNE DEFICIENCYen
dc.subjectMULTIVARIATE ANALYSISen
dc.subjectADULTen
dc.subjectBAYES THEOREMen
dc.subjectBIOMARKERSen
dc.subjectGENETIC MARKERSen
dc.subjectHUMANSen
dc.subjectIMMUNOLOGIC DEFICIENCY SYNDROMESen
dc.subjectMULTIVARIATE ANALYSISen
dc.titleМногофакторный анализ «генеалогических маркеров» у взрослых с первичными иммунодефицитамиru
dc.title.alternativeMultivariate analysis of genealogical markers in adults with primary immunodeficienciesen
dc.typeArticleen
dc.typeinfo:eu-repo/semantics/articleen
dc.typeinfo:eu-repo/semantics/publishedVersionen
dc.identifier.rsi25870871-
dc.identifier.doi10.17116/terarkh201688446-52-
dc.identifier.scopus84997822219-
local.affiliationInstitute of Immunology and Physiology, Ural Branch, Russian Academy of Sciences, Yekaterinburg, Russian Federationen
local.affiliationSverdlovsk Regional Clinical Hospital One, Yekaterinburg, Russian Federationen
local.affiliationRegional Childrens Clinical Hospital One, Yekaterinburg, Russian Federationen
local.affiliationInstitute of Ecology and Industrial Safety, Ural Branch, Russian Academy of Sciences, Yekaterinburg, Russian Federationen
local.affiliationUral Federal University Named after the First President of Russia B.N. Yeltsin, Yekaterinburg, Russian Federationen
local.contributor.employeeШершнев Виктор Николаевичru
local.description.firstpage46-
local.description.lastpage52-
local.issue4-
local.volume88-
dc.identifier.wos000375628300009-
local.identifier.pure865676-
local.identifier.eid2-s2.0-84997822219-
local.identifier.wosWOS:000375628300009-
Располагается в коллекциях:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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