As the health status of patients can improve or deteriorate during their stay in intensive care, the probability of development of delirium may also change.
Individuals' occupations also affect their daily travel time and their probability of intensive travel.
The dummy variables for the cities impact daily travel times and the probability of intensive travel in the same direction.
Similarly, car-owning households tend to have shorter daily travel times and a lower probability of intensive travel.
We can expect that for most of the explanatory variables, the effect on the average daily travel time and on the probability of intensive travel will be equivalent.
Conversely, the presence of children under the age of 12 in a household tends to reduce the daily travel time and the probability of intensive travel.
All else being equal, the daily travel time and the probability of intensive travel are the lowest in Rennes, which is the city in our sample that most favours car travel, buses providing the only public transport.
Our estimation results show that on average men's hazard rate is 8.6%% lower than women's (Cox model: β = −0.089, hazard ratio = 0.914, p-value < 0.001) and that they also have a higher probability of intensive travel (logit model: β = 0.3212, odds ratio = 1.379, p-value < 0.001).
The relationship between risk score and the predicted probability of intensive care readmission is also shown in Figure 2B which shows a corresponding rise in the predicted risk of CVICU readmission as the APPROACH CVICU risk score rises.
That prospective study, which included some 851 mechanically ventilated patients, was performed to evaluate the predictive ability of, and outcomes associated with, daily clinician estimates of a probability of intensive care unit (ICU) survival under 10%.
