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Kidney Week

Abstract: TH-PO818

Patient Reported Clinical Symptoms Are Associated with Patient Outcomes

Session Information

Category: Dialysis

  • 607 Dialysis: Epidemiology, Outcomes, Clinical Trials - Non-Cardiovascular

Authors

  • Maddux, Dugan, Fresenius Medical Care North America, Waltham, Massachusetts, United States
  • Han, Hao, Fresenius Medical Care North America, Waltham, Massachusetts, United States
  • Larkin, John W., Fresenius Medical Care North America, Waltham, Massachusetts, United States
  • Usvyat, Len A., Fresenius Medical Care North America, Waltham, Massachusetts, United States
  • van der Sande, Frank, Maastricht University Medical Centre , Maastricht, Netherlands
  • Kooman, Jeroen, Maastricht University Medical Centre , Maastricht, Netherlands
  • Maddux, Franklin W., Fresenius Medical Care North America, Waltham, Massachusetts, United States
Background

Traditional outcomes-related research on dialysis patients typically focuses on biomarkers such as blood pressure, body size, albumin (alb) and hemoglobin. During dialysis treatment, however, nurse-documented “chairside” patient information is also collected, and majorly includes patients’ symptoms that may have an effect on patients’ clinical outcomes. The association of chairside data with patient outcomes has not been well described. We aim to understand the relationship of “shortness of breath” (SOB), a nurse-reported patient symptom, to patient outcomes.

Methods

We included all patients who initiated dialysis treatment in the network of Fresenius Medical Care North America clinics between Jan 1, 2013 and June 30, 2015. Only patients who survived the first 365 days on dialysis were included. Patient laboratory and treatment parameters including The Kidney Disease Quality of Life (KDQOL) survey were computed as averages of the first year on dialysis. Patient hospitalization outcomes were assessed in year 2 on dialysis. We computed percent of treatments where patients experienced SOB symptoms as determined by either nursing notes or checkbox-based assessment in the electronic health record. A Poisson model using hospital admissions as an outcome was utilized to calculate the association of SOB to hospital admissions.

Results

We analyzed data on 39,594 dialysis patients. In a univariate analysis, we noted that the strongest correlation with percent of treatments with SOB were hospital admission rate (r=0.14, p<0.001), alb level (r=-0.09, p<0.001), KDQOL physical composite score (r=-0.12, p<0.001), and KDQOL symptom problem score (r=-0.11, p<0.001). We also observed that the percent of treatments with SOB was clearly significantly associated with more hospital admissions.

Conclusion

Chairside observation and clinician documentation of patient-reported symptoms may be an important predictor of outcomes in dialysis patients. Additional analyses are needed to understand the association of SOB and other symptoms to patient outcomes.

Funding

  • Commercial Support –