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Univariate analyses of the association between individual variables and outcomes were performed using logistic regression.
Analyses of the radiographic outcomes were performed using computerized linear measurements with image analysis software (Axiovision v. 3.0; Carl Zeiss).
Intercohort comparisons of patient demographic, clinical, and treatment characteristics, and clinical outcomes were performed using Student's t-test.
Data analyses of background information and subgroup analyses of HRQoL outcomes were performed using descriptive statistical methods, using mean values, standard deviations (SD) and proportions.
Correlation analyses between PK, PD, and clinical outcomes were performed using Spearman's rank correlation coefficient, and Wilcoxon signed rank test was used to determine change from pretreatment.
Descriptive statistics and analysis to determine factors associated with developmental outcomes were performed using STATA version 10 (StataCorp 2007. Stata Statistical Software: Release 10. College Station, TX: StataCorpLP).
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The association of the post transplant ICU mechanical ventilation settings and outcomes was performed using logistic regression.
Modeling for possible long-term outcomes was performed using the CORE Diabetes Model (CDM), a documented, validated simulation model for type 2 diabetes that projects life expectancy, quality-adjusted life expectancy (QALE) and total lifetime costs of diabetes-related complications (3).
Univariate linear regression analyses for the primary outcome and logistic regression for the secondary outcome were performed, using additive models.
Comparisons of baseline characteristics between patients with and without sustained favorable long-term outcome were performed using Fisher's exact tests (categorical) and analysis of variance (continuous).
Analyses on long term outcome were performed using the Kaplan Meier method with logrank test for the groups of patients with different degrees of anaemia.
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