Advancing Palliative Care in Patients With CKD: From Ideas to Practice.

A palliative approach to care focuses on what matters most to patients with life-limiting illness, including chronic kidney disease (CKD). Despite recent publication of related clinical practice guidelines in nephrology, there is limited information about how to practically implement these recommendations. In this Perspective, we describe our experience integrating a palliative approach within routine care of patients with CKD glomerular filtration rate categories 4 and 5 (G4-G5) across a provincial kidney care network during the past 15 years. The effort was led by a multidisciplinary group, tasked with building capacity and developing tools and resources for practical integration within a provincial network structure. We used an evidence-based framework that includes recommendations for 4 pillars of palliative care to guide our work: (1) patient identification, (2) advance care planning, (3) symptom assessment and management, and (4) caring of the dying patient and bereavement. Activities within each pillar have been iteratively implemented across all kidney care programs using existing committees and organizational structures. Key quality indicators were used to guide strategic planning and improvement. We supported culture change through the use of multiple strategies simultaneously. Altogether, we established and integrated palliative care activities into routine CKD G4-G5 care across the continuum from nondialysis to dialysis populations.

External validation and clinical utility of a prediction model for 6-month mortality in patients undergoing hemodialysis for end-stage kidney disease.

BACKGROUND: End-stage kidney disease is associated with poor prognosis. Health care professionals must be prepared to address end-of-life issues and identify those at high risk for dying. A 6-month mortality prediction model for patients on dialysis derived in the United States is used but has not been externally validated. AIM: We aimed to assess the external validity and clinical utility in an independent cohort in Canada. DESIGN: We examined the performance of the published 6-month mortality prediction model, using discrimination, calibration, and decision curve analyses. SETTING/PARTICIPANTS: Data were derived from a cohort of 374 prevalent dialysis patients in two regions of British Columbia, Canada, which included serum albumin, age, peripheral vascular disease, dementia, and answers to the "the surprise question" ("Would I be surprised if this patient died within the next year?"). RESULTS: The observed mortality in the validation cohort was 11.5% at 6 months. The prediction model had reasonable discrimination (c-stat = 0.70) but poor calibration (calibration-in-the-large = -0.53 (95% confidence interval: -0.88, -0.18); calibration slope = 0.57 (95% confidence interval: 0.31, 0.83)) in our data. Decision curve analysis showed the model only has added value in guiding clinical decision in a small range of threshold probabilities: 8%-20%. CONCLUSION: Despite reasonable discrimination, the prediction model has poor calibration in this external study cohort; thus, it may have limited clinical utility in settings outside of where it was derived. Decision curve analysis clarifies limitations in clinical utility not apparent by receiver operating characteristic curve analysis. This study highlights the importance of external validation of prediction models prior to routine use in clinical practice.