Integrating the Surprise Question, Palliative Care Screening Tool, and Clinical Risk Models to Identify Peritoneal Dialysis Patients With High One-Year Mortality

Abstract

ContextUniversal screening to identify vulnerable patients who may receive limited benefits from life-sustaining treatments can facilitate palliative care in dialysis populations. ObjectivesWe aimed to develop prediction models for one-year mortality in peritoneal dialysis (PD) patients. MethodsThis prospective cohort study included 401 adult Taiwanese prevalent PD patients (average age 56.2 ± 14 years). In addition to obtaining clinical characteristics and laboratory data, the primary care nurses evaluated the surprise question (SQ) and palliative care screening tool (PCST) for each patient in March 2015. Multivariate logistic regression models were conducted to predict the primary outcome of one-year all-cause mortality. ResultsThere were 34 (8.5%) patients who died during the first year of follow-up. Patients allocated to the not surprised group according to the SQ and those who received a score of ≥4 on the PCST had increased odds of death (odds ratio 24.68 [95% CI 10.66–57.13] and 12.18 [95% CI 5.66–26.21], respectively). We also developed a clinical risk model for one-year mortality that included sex, dialysis vintage, coronary artery disease, malignancy, normalized protein nitrogen appearance, white blood cell count, and serum albumin and sodium levels. Integrating the SQ, PCST, and clinical risk model exhibited good discrimination with an area under the receiver operating characteristic curve of 0.95. Kaplan-Meier analysis showed worse survival in high-risk patients predicted by the integrated model (log-rank P < 0.001). ConclusionScreening with the use of the integrated measurement can identify high-risk PD patients. This approach may facilitate palliative care interventions for at-risk subpopulations.