To adjust for potential confounders, other pre- and intraoperative factors thought to be associated with conditions included in the definition of major morbidity were explored.
In this paper, the types of goals that were important for older persons with multi-morbidities were explored from the perspectives of patients, their caregivers and physicians.
Association of independent variables with the two outcome measurements (major morbidity and mortality) was explored by using a logistic regression analysis.
The predictive accuracy of nadir ScVO2 and peak lactate for major morbidity and mortality was explored by using the receiver operating characteristic (ROC) curve and the relative area under the curve (AUC).
The association of nadir ScVO2 and peak lactate with major morbidity and mortality was explored by using a logistic regression analysis with odds ratios and 95% confidence intervals (Table 3).
Therefore, an exposure indicator including dew point temperature was chosen for the time series analysis [ 23, 25], and the excess mortality/morbidity associated with specific air masses was explored using a climatologic classification based on synoptic indexes [ 37- 39].
Differences in cost and outcomes associated with patient characteristics such as sex, age, smoking status and existing co-morbidities may be explored through subgroup analysis, dependent on data availability.
As the present study was cross-sectional the cause and effect relationship between systemic inflammation, lung function and morbidity has to be explored in more detail in longitudinal studies.
But how rehabilitation might address the CV co-morbidity has not been explored.
Differences in the likelihood of referral, diagnosis and treatment within target by SEP, age, sex, histology, year of diagnosis, co-morbidity score, stage and PS were explored using logistic regression models mutually adjusted for all co-variables.
