(survivors) and group 2 (nonsurvivors). Firstly, the
risk factor were evaluated using the binary
modelKorneyev, I.A.,
Alexeeva, T.A.,
Al-Shukri, S.H.,
Bernikov, A.N.,
Erkovich, A.A.,
Kamalov, A.A.,
Kogan, M.I.,
Pavlov, V.N.,
Zhuravlev, V.N.,
Pushkar, D.Y. (2016) An analysis of prevalence and associated common
risk factors of ED and lower urinary tract symptoms
models. Linear regression analyses were performed to estimate the relationship between SNPs and lung
Korytina, G.F.,
Akhmadishina, L.Z.,
Kochetova, O.V.,
Aznabaeva, Y.G.,
Zagidullin, Sh.Z.,
Victorova, T.V. (2016) .0037, OR 2.31 in recessive
model) with COPD were revealed. The disease
risk was higher in carriers
genotype is typical for people of Bashkortostan due to underlying
risk for HFRS. A combination of genotypes
in the swine
model or open beating heart with CPB support on the sheep
model. The posterior mitral leaflet
Avzaletdinova, D.Sh.,
Sharipova, L.F.,
Kochetova, O.V.,
Morugova, T.V.,
Erdman, V.V.,
Mustafina, O.E. (2016) inheritance
models (codominant, dominant, and recessive). At the same time, it was demonstrated that the
riskMike Saji,
Marc Katz,
Gorav Ailawadi,
Dale Fowler,
Damien LaPar,
Leora Yarboro,
Ravi Ghanta,
John Kern,
John Dent,
Michael Ragosta,
Scott Lim (2016) metrics have been reported to guide better patient selection, however, universal
risk stratification