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The high variability in community structure predicted by the model, which is similar to that observed in the natural community, arises from observed variability in parameters of interaction outcomes, growth, recruitment, and mortality of each species.
That is why we aim to describe frequencies, management and mortality of each AHF syndrom in intensive care.
The attributable mortality of each of these two invasive infections remains different mainly because the affected patients are different (more hematologic malignancies in patients with Aspergillus infection).
The foreign-resident prediction is written following the style used in the R package (R Development Core Team [2013]) with separate models for growth and mortality: growth ∼ X + H + X + H S, mortality ∼ X + H + X + H S Model 1. meaning that the growth or mortality of each tree is the response variable, and habitat (X) and home/away (H) are fixed-effect predictors.
Mortality of each group was recorded.
Change in prevalence and mortality of each disease and change in total years of life lived are derived for every five-year age group cohort in the adult population (age 18 years and older) using proportional multi-state lifetable analysis [22].
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Virulence data (percentage mortality and lethal time to mortality (LT)) of each isolate was used in the cluster analysis.
Expected mortality rate of each hospital was highly correlated with observed mortality rate (r = 0.693, p < 0.001).
We estimated the mortality level of each educational group by calculating age-standardized mortality rates (ASMR) using the European population as a standard (WHO).
5. Mortality rates of low risks cases – this refers to the mortality rate of each hospital for cases with conditions that have a low probability of death.
6. Mortality rates of high-risk cases – this refers to the mortality rate of each hospital for cases with conditions that have a high probability of death.
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