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Abstract

The mortality rate from non-cancer is increasing with increasing population aging. Generally, it is difficult to accurately identify the clinical course of non-cancer chronic diseases and to predict their prognoses. If the length of survival in patients with chronic diseases can be predicted, healthcare providers can perform flexible interventions for patients and their families according to clinical stages. Therefore, this study aimed to identify non-cancer patients with a survival prognosis of 1-year by using predictive survival analysis. We conducted a prospective cohort study of 106 patients at home with non-cancer (e.g. cerebrovascular, cardiovascular, musculoskeletal, neurological diseases and dementia) who were receiving home care from Seoul St. Mary鈥檚 Hospital, had Palliative Performance Scale (PPS) scores of less than 40% in their medical records. Upon follow-up with the 1-year survival of patients, there were 35 deceased patients (33.0%) and 69 survived patients (67.0%). The average length of survival of them was 306 days. Among them, 76 were females (71.7%) and the mean age was 80.3 years. They had an average of 1.5 comorbidities. The results of analyzing the Cox Proportional Hazard Model showed that the age (Hazard Ratio: 1.041), number of comorbidities (Hazard Ratio: 1.522), duration of required nursing (Hazard Ratio: 9.445), waist circumference (Hazard Ratio: 0.954) and PPS (Hazard Ratio: 0.530) were the significant prognostic factors that increased the risk of mortality. The results of the present study can be used as baseline data for predicting the length of survival and prognosis of home-based patients with non-cancer chronic diseases.

Biography

E-mail: 88ljwon@naver.com