Predicting the risk of end-stage renal disease in the population-based setting: a retrospective case-control study

Abstract Background Previous studies of predictors of end-stage renal disease (ESRD) have limitations: (1) some focused on patients with clinically recognized chronic kidney disease (CKD); (2) others identified population-based patients who developed ESRD, but lacked earlier baseline clinical measures to predict ESRD. Our study was designed to address these limitations and to identify the strength and precision of characteristics that might predict ESRD pragmatically for decision-makers--as measured by the onset of renal replacement therapy (RRT). Methods We conducted a population-based, retrospective case-control study of patients who developed ESRD and started RRT. We conducted the study in a health maintenance organization, Kaiser Permanente Northwest (KPNW). The case-control study was nested within the adult population of KPNW members who were enrolled during 1999, the baseline period. Cases and their matched controls were identified from January 2000 through December 2004. We evaluated baseline clinical characteristics measured during routine care by calculating the adjusted odds ratios and their 95% confidence intervals after controlling for matching characteristics: age, sex, and year. Results The rate of RRT in the cohort from which we sampled was 58 per 100,000 person-years (95% CI, 53 to 64). After excluding patients with missing data, we analyzed 350 cases and 2,114 controls. We identified the following characteristics that predicted ESRD with odds ratios ≥ 2.0: eGFR2 (OR = 20.5; 95% CI, 11.2 to 37.3), positive test for proteinuria (OR = 5.0; 95% CI, 3.5 to 7.1), hypertension (OR = 4.5; 95% CI, 2.5 to 8.0), gout/positive test for uric acid (OR = 2.5; 95% CI, 1.8 to 3.5), peripheral vascular disease (OR = 2.2; 95% CI, 1.4 to 3.6), congestive heart failure (OR = 2.1; 95% CI, 1.4 to 3.3), and diabetes (OR = 2.1; 95% CI, 1.5 to 2.9). Conclusions The clinical characteristics needed to predict ESRD--for example, to develop a population-based, prognostic risk score--were often documented during routine care years before patients developed ESRD and required RRT.</p

Predicting the Risk of Emergency Department Visits in Medicaid Members: Development and Temporal Validation of a Model

Background/Aims: We developed and validated a model to predict the risk of emergency department (ED) visits in adult Medicaid members so that case-managers can identify the highest-risk patients and intervene. We then validated the model on newly enrolled Medicaid patients. Methods: To develop the prediction model, we assembled a retrospective cohort of adult Medicaid members (18–64 years old) enrolled at Kaiser Permanente Northwest between 2010 and 2013. We measured patient characteristics during the 90 days before the start of follow-up that might predict ED visits. We followed patients for up to 180 days to identify the first ED visit. To validate the model, we assembled a distinct cohort of adult Medicaid members who joined Kaiser Permanente Northwest in the first quarter of 2014. We developed and validated separate models for men and women using Cox regression. Results: We observed 2,587 patients who visited the ED during the 180-day follow-up. The overall 180-day risk of an ED visit was 13.9 per 100 (men) and 17.4 per 100 (women). The models discriminated the high- and low-risk patients adequately: concordance or c-statistic was 0.72 (men) and 0.71 (women), respectively. The model’s 10 predictor characteristics explained 35.2% of the variation in ED visits in men and 29.6% of the variation in women. Model calibration (agreement between observed and predicted) revealed that the mean predicted risks in the highest-risk patients underestimated the observed risks of an ED visit by approximately 11 per 100. The model for women validated adequately in the newly enrolled cohort because the c-statistic remained constant while the model for men disappointed because the c-statistic dropped by 0.05. For both men and women, the models continued to underestimate the absolute risk of an ED visit in the highest-risk patients. Conclusion: The models identified the highest-risk patients with only 90 days of clinical history, and the models validated on new Medicaid patients. Time invested in managing the highest-risk patients may offer a superior return on investment compared with a strategy that does not stratify because the highest-risk patients suffer a disproportionate excess risk. The return on time invested may be even higher if recurrent ED visits are considered

Predicting costs of care in heart failure patients

Abstract Background Identifying heart failure patients most likely to suffer poor outcomes is an essential part of delivering interventions to those most likely to benefit. We sought a comprehensive account of heart failure events and their cumulative economic burden by examining patient characteristics that predict increased cost or poor outcomes. Methods We collected electronic medical data from members of a large HMO who had a heart failure diagnosis and an echocardiogram from 1999–2004, and followed them for one year. We examined the role of demographics, clinical and laboratory findings, comorbid disease and whether the heart failure was incident, as well as mortality. We used regression methods appropriate for censored cost data. Results Of the 4,696 patients, 8% were incident. Several diseases were associated with significantly higher and economically relevant cost changes, including atrial fibrillation (15% higher), coronary artery disease (14% higher), chronic lung disease (29% higher), depression (36% higher), diabetes (38% higher) and hyperlipidemia (21% higher). Some factors were associated with costs in a counterintuitive fashion (i.e. lower costs in the presence of the factor) including age, ejection fraction and anemia. But anemia and ejection fraction were also associated with a higher death rate. Conclusions Close control of factors that are independently associated with higher cost or poor outcomes may be important for disease management. Analysis of costs in a disease like heart failure that has a high death rate underscores the need for economic methods to consider how mortality should best be considered in costing studies.</p

Clinician’s use of automated reports of estimated glomerular filtration rate: A qualitative study

Background There is a growing awareness in primary care of the importance of identifying patients with chronic kidney disease (CKD) so that they can receive appropriate clinical care; one method that has been widely embraced is the use of automated reporting of estimated glomerular filtration rate (eGFR) by clinical laboratories. We undertook a qualitative study to examine how clinicians use eGFR in clinical decision making, patient communication issues, barriers to use of eGFR, and suggestions to improve the clinical usefulness of eGFR reports. Methods Our study used qualitative methods with structured interviews among primary care clinicians including both physicians and allied health providers, recruited from Kaiser Permanente Northwest, a non-profit health maintenance organization. Results We found that clinicians generally held favorable views toward eGFR reporting but did not use eGFR to replace serum creatinine in their clinical decision-making. Clinicians used eGFR as a tool to help identify CKD, educate patients about their kidney function and make treatment decisions. Barriers noted by several clinicians included a desire for greater education regarding care for patients with CKD and tools to facilitate discussion of eGFR findings with patients. Conclusions The manner in which clinicians use eGFRs appears to be more complex than previously understood, and our study illustrates some of the efforts that might be usefully undertaken (e.g. specific clinician education) when encouraging further promulgation of eGFR reporting and usage.</p

Chronic kidney disease and outcomes in heart failure with preserved versus reduced ejection fraction: the Cardiovascular Research Network PRESERVE Study

BACKGROUND: There is scant evidence on the effect that chronic kidney disease (CKD) confers on clinically meaningful outcomes among patients with heart failure with preserved left ventricular ejection fraction (HF-PEF). METHODS AND RESULTS: We identified a community-based cohort of patients with HF. Electronic medical record data were used to divide into HF-PEF and reduced left ventricular EF on the basis of quantitative and qualitative estimates. Level of CKD was assessed by estimated glomerular filtration rate (eGFR) and by dipstick proteinuria. We followed patients for a median of 22.1 months for outcomes of death and hospitalization (HF-specific and all-cause). Multivariable Cox regression estimated the adjusted relative-risk of outcomes by level of CKD, separately for HF-PEF and HF with reduced left ventricular EF. We identified 14 579 patients with HF-PEF and 9762 with HF with reduced left ventricular EF. When compared with patients with eGFR between 60 and 89 mL/min per 1.73 m(2), lower eGFR was associated with an independent graded increased risk of death and hospitalization. For example, among patients with HF-PEF, the risk of death was nearly double for eGFR 15 to 29 mL/min per 1.73 m(2) and 7x higher for eGFR/min per 1.73 m(2), with similar findings in those with HF with reduced left ventricular EF. CONCLUSIONS: CKD is common and an important independent predictor of death and hospitalization in adults with HF across the spectrum of left ventricular systolic function. Our study highlights the need to develop new and effective interventions for the growing number of patients with HF complicated by CKD