Discriminant analysis for defining quality of life patients with comorbid pathology of osteoarthrosis

Abstract

There has been a shift in medicine from relying on clinical biomarkers to including patient-reported outcome measures. From a healthcare perspective, health-related quality of life (HRQOL) measures can be used to enhance patient care and reducing treatment cost for patients. Given the possible importance of Medical Outcome Study in medicine, and the conflicting reports in literature about its use in healthcare, it is important to identify its utility within the medical community. In this study 150 people were recruited prospectively from patients at the Hospital and the emergency сenter №1 in Zaporizhzhya, Ukraine. Four groups were formed. The inclusion criteria to group were different comorbid pathology of osteoarthrosis. We assessed patients HRQOL SF-36 SF-36 changes before and after pharmacotherapy (over 1 year), than it were compared with the control group. The validity of the construct has been analyzed by discriminant analysis. To assess SF-36 ability identifying discriminating functions were developed, determine its prediction value, define which scales of SF-36 are the best predictors for every groups. In addition, canonical analysis demonstrates SF-36 ability to estimate effect of pharmacotherapy. Statistical analysis show that all indices quality of life through SF – 36 scales except of third (physical role functioning, physical functioning, emotional role functioning) have prognostic value (p>0.05) and validity of SF-39 scales for examination of the patients with coexisting disease is statistically significant(p<0.05).

Health-related Quality of life and its related factors in patients undergoing Coronary angioplasty, Zanjan, northwest Iran

“…One of the successful tools in measuring quality of life related to health is the 36-items Short Form Health Survey questionnaire ) SF-36) (9). This questionnaire has been used to assess health related quality of life in various samples, for instance in heart disease (10), diabetes (11), kidney (12), gastrointestinal (13), osteoarthritis (14) etc., as well as healthy samples of the community (15).…”