Estimating the survival of elderly patients diagnosed with dementia in Taiwan: A longitudinal study

Kwo-Chen Lee, Wen-Hsuan Hsu, Po-Han Chou, Jia-Jean Yiin, Chih-Hsin Muo and Yun-Ping Lin

PLOS ONE, 2018, vol. 13, issue 7, 1-12

Abstract: Background: Dementia is characterized by prolonged progressive disability. Therefore, predicting mortality is difficult. An accurate prediction tool may be useful to ensure that end-of-life patients with dementia receive timely palliative care. Purpose: This study aims to establish a survival prediction model for elderly patients with dementia in Taiwan. Methods: Data from the 2001 to 2010 National Health Insurance Research Database in Taiwan were used to identify 37,289 patients with dementia aged ≥65 years for inclusion in this retrospective longitudinal study. Moreover, this study examined the mortality indicators for dementia among demographic characteristics, chronic physical comorbidities, and medical procedures. A Cox proportional hazards model with time-dependent covariates was used to estimate mortality risk, and risk score functions were formulated using a point system to establish a survival prediction model. The prediction model was then tested using the area under the receiver operating characteristic curve. Results: Thirteen mortality risk factors were identified: age, sex, stroke, chronic renal failure, liver cirrhosis, cancer, pressure injury, and retrospectively retrieved factors occurring in the 6 months before death, including nasogastric tube placement, supplemental oxygen supply, ≥2 hospitalization, receiving ≥1 emergency services, ≥2 occurrences of cardiopulmonary resuscitation, and receiving ≥2 endotracheal intubations. The area under the receiver operating characteristic curves for this prediction model for mortality at 6 and 12 months were 0.726 and 0.733, respectively. Conclusions: The survival prediction model demonstrated moderate accuracy for predicting mortality at 6 and 12 months before death in elderly patients with dementia. This tool may be valuable for helping health care providers and family caregivers to make end-of-life care decisions.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0178997

DOI: 10.1371/journal.pone.0178997

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