Wald tests were used to assess the significance of fixed effects and covariates when analyzing the relationship between depressive, manic, and total morbidity index and several characteristics of illness course.
According to multiple binary logistic regression analysis, MIG and MOH patients were comparable in terms of demographic characteristics, whereas they differed for some characteristics of illness (age of migraine onset, duration of illness, frequency of headache), disability and QoL, as well as for depression levels.
These scales described important characteristics of illness-related experience within six life domains (i.e., Physical, Mental-Emotional, Interpersonal Receptiveness, Interpersonal Contribution, Transpersonal Receptiveness and Transpersonal Orientation).
Characteristics of acute illness including illness type and severity, are described.
Participants were interviewed broadly on subject characteristics (age, marital status, formal education, and family/community interactions), illness characteristics (nature of illness, severity of illness, perceived cause of illness, and expected benefits of treatment) and service characteristics (appeal, accessibility, quality, communication, and cost).
To identify the clinical characteristics of bipolar illness that best predict medical illness burden group, we entered the variables that were statistically significant at the P<0.05 level in the univariate analyses, shown in Table 4, into a logistic regression model.
Baseline characteristics, severity of illness, and predisposing conditions and ALI risk modifiers differed between patients who did and those who did not develop ALI (Table 1).
Baseline characteristics, severity of illness, predisposing conditions and ALI risk modifiers, and secondary outcomes remained different between patients who did and those who did not develop ALI.
Baseline characteristics, severity of illness, predisposing conditions and ALI risk modifiers, and secondary outcomes maintained their differences between patients who did and did not develop ALI.
In the bivariate analyses, demographic characteristics, year of illness onset, clade of H5N1 virus infection, and underlying medical conditions were similar between fatal and nonfatal cases (Table 4).
characteristics, history of illness and medication use, and physiologic status (pregnancy, fasting time, etc).
