Kidney Week

Abstract: FR-PO908

External Validation of a Short-Term Prognostic Model for Patients Who Are on Maintenance Hemodialysis

Session Information

• Dialysis: Palliative and End-of-Life Care
  November 03, 2017 | Location: Hall H, Morial Convention Center
  Abstract Time: 10:00 AM - 10:00 AM

Category: Dialysis

• 609 Dialysis: Palliative and End-of-Life Care

Authors

• Kittanamongkolchai, Wonngarm, Mayo Clinic, Rochester, Minnesota, United States

Wonngarm Kittanamongkolchai,

• Gonzalez Suarez, M. Lourdes, Mayo Clinic, Rochester, Minnesota, United States

M. Lourdes Gonzalez Suarez,

• Gregoire, James Robert, Mayo Clinic, Rochester, Minnesota, United States

James Robert Gregoire,

Background

Simple and accurate instruments for prognostication are needed to enable nephrologists to identify dialysis patients who have a poor prognosis and benefit from palliative care and advance care planning. Prognostic models have been developed but external validation studies are scarce. We aimed to externally validate a short-term prognostic model among our dialysis patients.

Methods

Between October 1 to October 31 2015, all of the adult HD patients (n =89) at a single dialysis facility in Rochester, MN were screened. Patient charts were reviewed for actuarial predictors (age, serum albumin, dementia and peripheral vascular disease) and nephrologists answered the “surprise” question, “Would I be surprised if this patient died within the next 6 months?”. One-year survival was calculated using the prognostic calculator tool derived from a study by Cohen et al¹( H:\QI palliative\Prospective study\Prognosis calculator.htm ) with each patient’s individual covariates. Survival was monitored for 12 months. We assessed the predictive accuracy of the short-term prognostic model by calculating c-index based on the receiver operating characteristic curve.

Results

The mean predicted 1-year mortality was 19% compared with the observed mortality of 12%. The model had a C-index of 0.82 (p = 0.0001). Thirty eight percent of patients with 1-y predicted survival rate in the lowest quartile (equal or less than 66%) died compared to 3% of those with 1-Y predicted survival rate more than 66%. As seen in Figure 1, the model successfully predicted which patients had worse and better survival over time.

Conclusion

The short-term prognostic tool for dialysis patients may be of value for clinicians to improve end-of-life care by providing more accurate prognostic information.

Reference:
1. Cohen LM, et al. Clin J Am Soc Nephrol. 2010 Jan;5(1):72-9

Figure 1: Survival of patients with predicted 1-Y survival in the lowest quartile (blue line) and higher quartiles (red line)