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Predictors of mortality by multivariable analysis included renal insufficiency (OR, 12.51; P=.02) or infection with Candida species (OR, 4.93; P=.03) or gram-negative bacilli (OR, 9.12; P=.01).
Potential factors not statistically associated with HIV-infection in the multivariable analysis included male circumcision and sex in the last 12 months.
Logistic regression was used to calculate odds ratios and the multivariable analysis included gestational age at sample collection, smoking, maternal age, race or ethnic group, body mass index and study treatment group (i.e., aspirin or placebo).
23 Overadjustment would occur if multivariable analysis included intermediate variables.
Risk factors identified in multivariable analysis included low vegetation density and highway proximity.
Therefore, multivariable analysis included all variables with a P value <0.30.
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Multivariable analysis including variables significantly associated with death was performed using a Cox proportional hazard model with VAP as a time-dependent variable.
We next performed multivariable analysis including the prognostic factors age, gender, pT, pN pM stage as well as post-operative therapy and determined the added benefit of stratifying patients with tumors with higher amounts of CD8+ TILs by TIA-1.
Multivariable analysis includes year, maternal age and parity.
Even though, we found no change after multivariable analysis including co-existence of diabetes.
It did not remain significant in multivariable analysis including primary clinico-pathological characteristics (thickness, mitotic count, ulceration, vessel invasion).
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