Creation of a Risk-scoring Algorithm for Early Mortality Among Elderly ESRD Patients Background. The rate of early deaths, those occurring within the three months following the diagnosis of end-stage renal disease (ESRD), are disproportionately high among patients who are 65 and older. Inexorable increases in the incidence of patients with both chronic kidney disease (CKD) and ESRD impel efforts to slow and reverse this urgent public health problem. This study aims to develop a risk-scoring system to aid in the clinical prediction of early death among elderly (>65 years) ESRD patients. Objective. We hypothesize that patients with high rates of "early mortality" soon after dialysis initiation have significant pre-dialysis medical conditions combined with inadequate renal disease management that does not prepare them appropriately for long- term dialysis. Our exploratory research project will identify factors associated with mortality within the first three months after starting permanent dialysis. We propose to examine the following associated with early mortality: 1) comorbid conditions found within one year prior to dialysis (e.g., cardiovascular events, acute renal failure, sepsis, hypertensive emergencies);2) medical management prior to dialysis including involvement of a nephrology specialist, management of anemia, nutritional status, and vascular access preparation for dialysis that differentiates the 'emergent versus elective'(i.e., acute onset 'crash and burn'versus planned) transition to ESRD;and 3) use of health services in the latter stages of CKD. Results from these analyses will be used to develop a prognostic model and scoring algorithm for early mortality among dialysis patients. Methods. Using historical Medicare claims data, we propose to conduct a retrospective cohort study to develop a user friendly prognostic index. To identify the study population, we will construct a complete renal failure patient history by linking the pre-dialysis and post dialysis data to assess the predictors of early death. The proposed study is unique in linking the 2000-2009 ESRD data files to the 5% Chronic Kidney Disease (CKD) sample that has recently become available for research purposes. The total number of Medicare-eligible CKD patients from this period is approximately 831,000;of these, roughly 10% become ESRD-eligible and form the basis of our study population. Multivariate logistic regression models will b used to test each hypothesis and identify the significant risk factors for early mortality. Significance. We plan to identify potentially "modifiable" factors that are associated with early death among a population that transitions from CKD to ESRD requiring expensive, permanent and life-altering dialysis therapy. Given the high mortality rates during the first year after dialsis, accurate prediction of those destined for early death would be useful to patients and their families, providers, and society in making decisions about treatment.
Creation of a Risk-scoring Algorithm for Early Mortality Among Elderly ESRD Patients The morbidity and mortality rates among chronic kidney disease patients transitioning to end- stage renal disease (ESRD) are 'unacceptably high'according to the NIDDK (1). Healthy People 2010 concludes that medically appropriate care of these patients within 12 months before the start of renal replacement therapy reduces the substantial illness, disability, and death associated with treated chronic kidney failure (2). The National Kidney Foundation's clinical guidelines, Kidney Disease Outcomes Quality Initiative (KDOQI), call for development of a predictive clinical tool - using kidney disease diagnoses, risk factors, and/or other variables - to better predict risk in patients with chronic kidney disease (3). Using existing Medicare databases - linking the pre-dialysis patients to their subsequent transition into the ESRD program - we will develop a prognostic scoring index that will assist nephrologists and elderly patients and their families in identifying those patients at risk for early mortality ater initiating dialysis. (1) National Institute of Diabetes and Digestive and Kidney Diseases, Research Updates in kidney and urologic health, 2000, 18 Oct 2002 http://www.niddk.nih.gov/health/kidney/ Research Updates/sum00/1.htm>(2) U.S. Department of Health and Human Services. Healthy People 2010: Understanding and Improving Health. 2nd ed. Washington, DC: U.S. Government Printing Office, November 2000. (3) K/DOQI Clinical Practice Guidelines for Chronic Kidney Disease: Evaluation, Classification, and Stratification PART 7. Stratification of Risk for Progression of Kidney Disease and Development of Cardiovascular Disease Guideline 15. Association of Chronic Kidney Disease with Cardiovascular Disease.