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Competing event analysis would be a means to reliability estimate the overall sub distribution hazard and event specific hazards [ 48].
However, for the sub distribution hazard models, currently standard procedure is not available in SAS, but SAS macros [ 47], STATA with compet.ado or R-package cmprsk are available.
In addition, we provide evidence that SUB and AN can physically interact and that AN does not influence subcellular SUB distribution.
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Separately examining the positive coefficients and negative coefficients in each sub-distribution reveals that the positive (resp. negative) coefficients are not distributed normally, and are instead skewed to the more extreme values (Table 1).
sub-distribution hazard ratio.
Sub-distribution hazard ratios (sHRs) were developed with covariates using for the construction of the propensity score weighted by the IPTW.
Sub-distribution hazard ratios (sHRs) of ICU-acquired infection were significant for abnormal values at admission (Table 4), with no difference between subnormal and very low lymphocyte counts.
Sub-distribution hazard ratios (sHRs) were developed to assess the independent effects of lymphocyte count at admission and the evolution at day 3 on subsequent risk of ICU-acquired infection.
Independently of baseline lymphocyte count, the absence of lymphocyte count increase at day 3 was associated with ICU-acquired infection (sub-distribution hazard ratio sHR: 1.37 [1.12–1.67], p = 0.002) and with 28-day mortality (sHR: 1.67 [1.37–2.03], p < 0.0001).
Fine and Gray sub-distribution survival models were used, with ICU discharge as competing event, adjusted on comorbidity and illness severity at admission at each landmark, from Day 3 to Day 7. The impact of BWV on ICU stay duration was estimated through a multivariate negative binomial regression model.
Examples and applications as well as comparisons of the EKD and its sub-distributions with other distributions are given.
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