Rationale and design of a multicenter Chronic Kidney Disease (CKD) and at-risk for CKD electronic health records-based registry: CURE-CKD

Peter WL, Shubrook JH. Type 2 Diabetes and Chronic Kidney Disease: An Opportunity for Pharmacists to Improve Outcomes

Chronic kidney disease (CKD) is an important contributor to end-stage kidney disease, cardiovascular disease, and death in people with type 2 diabetes (T2D), but current evidence suggests that diagnosis and treatment are often not optimized. This review examines gaps in care for patients with CKD and how pharmacist interventions can mitigate these gaps. We conducted a PubMed search for published articles reporting on real-world CKD management practice and compared the findings with current recommendations. We find that adherence to guidelines on screening for CKD in patients with T2D is poor with particularly low rates of testing for albuminuria. When CKD is diagnosed, the prescription of recommended heart-kidney protective therapies is underutilized, possibly due to issues around treatment complexity and safety concerns. Cost and access are barriers to the prescription of newer therapies and treatment is dependent on racial, ethnic, and socioeconomic factors. Rates of nephrologist referrals for difficult cases are low in part due to limitations of information and communication between specialties. We believe that pharmacists can play a vital role in improving outcomes for patients with CKD and T2D and support the cost-effective use of healthcare resources through the provision of comprehensive medication management as part of a multidisciplinary team. The Advancing Kidney Health through Optimal Medication Management initiative supports the involvement of pharmacists across healthcare systems to ensure that comprehensive medication management can be optimally implemented.

Optimizing Care Delivery in Patients with Chronic Kidney Disease in the United States: Proceedings of a Multidisciplinary Roundtable Discussion and Literature Review

BACKGROUND

Approximately 37 million individuals in the United States (US) have chronic kidney disease (CKD). Patients with CKD have a substantial morbidity and mortality, which contributes to a huge economic burden to the healthcare system. A limited number of clinical pathways or defined workflows exist for CKD care delivery in the US, primarily due to a lower prioritization of CKD care within health systems compared with other areas (e.g., cardiovascular disease [CVD], cancer screening). CKD is a public health crisis and by the year 2040, CKD will become the fifth leading cause of years of life lost. It is therefore critical to address these challenges to improve outcomes in patients with CKD.

METHODS

The CKD Leaders Network conducted a virtual, 3 h, multidisciplinary roundtable discussion with eight subject-matter experts to better understand key factors impacting CKD care delivery and barriers across the US. A premeeting survey identified topics for discussion covering the screening, diagnosis, risk stratification, and management of CKD across the care continuum. Findings from this roundtable are summarized and presented herein.

RESULTS

Universal challenges exist across health systems, including a lack of awareness amongst providers and patients, constrained care team bandwidth, inadequate financial incentives for early CKD identification, non-standardized diagnostic classification and triage processes, and non-centralized patient information. Proposed solutions include highlighting immediate and long-term financial implications linked with failure to identify and address at-risk individuals, identifying and managing early-stage CKD, enhancing efforts to support guideline-based education for providers and patients, and capitalizing on next-generation solutions.

CONCLUSIONS

Payers and other industry stakeholders have opportunities to contribute to optimal CKD care delivery. Beyond addressing the inadequacies that currently exist, actionable tactics can be implemented into clinical practice to improve clinical outcomes in patients at risk for or diagnosed with CKD in the US.

Prescription of guideline-directed medical therapies in patients with diabetes and chronic kidney disease from the CURE-CKD Registry, 2019-2020

AIM

Guideline-directed medical therapy (GDMT) is designed to improve clinical outcomes. The study aim was to assess GDMT prescribing rates and prescribing-persistence predictors in patients with diabetes and chronic kidney disease (CKD) from the Center for Kidney Disease Research, Education, and Hope Registry.

MATERIALS AND METHODS

Data were obtained from adults ≥18 years old with diabetes and CKD between 1 January 2019 and 31 December 2020 (N = 39 158). Baseline and persistent (≥90 days) prescriptions for GDMT, including angiotensin converting enzyme (ACE) inhibitor/angiotensin receptor blocker (ARB), sodium-glucose cotransporter-2 (SGLT2) inhibitor and glucagon-like peptide 1 (GLP-1) receptor agonist were assessed.

RESULTS

The population age (mean ± SD) was 70 ± 14 years, and 49.6% (n = 19 415) were women. Baseline estimated glomerular filtration rate (2021 CKD-Epidemiology Collaboration creatinine equation) was 57.5 ± 23.0 ml/min/1.73 m2 and urine albumin/creatinine 57.5 mg/g (31.7-158.2; median, interquartile range). Baseline and ≥90-day persistent prescribing rates, respectively, were 70.7% and 40.4% for ACE inhibitor/ARB, 6.0% and 5.0% for SGLT2 inhibitors, and 6.8% and 6.3% for GLP-1 receptor agonist (all p < .001). Patients lacking primary commercial health insurance coverage were less likely to be prescribed an ACE inhibitor/ARB [odds ratio (OR) = 0.89; 95% confidence interval (CI) 0.84-0.95; p < .001], SGLT2 inhibitor (OR 0.72; 95% CI 0.64-0.81; p < .001) or GLP-1 receptor agonist (OR 0.89; 95% CI 0.80-0.98; p = .02). GDMT prescribing rates were lower at Providence than UCLA Health.

CONCLUSIONS

Prescribing for GDMT was suboptimal and waned quickly in patients with diabetes and CKD. Type of primary health insurance coverage and health system were associated with GDMT prescribing.

A National Registry for People With All Stages of Kidney Disease: The National Kidney Foundation (NKF) Patient Network

RATIONALE & OBJECTIVE

The National Kidney Foundation (NKF) launched the first national US kidney disease patient registry, the NKF Patient Network, that is open to patients throughout the continuum of chronic kidney disease (CKD). The Network provides individualized education and will facilitate patient-centered research, clinical care, and health policy decisions. Here, we present the overall design and the results of a feasibility study that was conducted July through December 2020.

STUDY DESIGN

Longitudinal observational cohort study of patient-entered data with or without electronic health care record (EHR) linkage in collaboration with health systems.

SETTING & PARTICIPANTS

People with CKD, age≥18 years, are invited through their provider, NKF communications, or national outreach campaign. People self-enroll and share their data through a secure portal that offers individualized education and support. The first health system partner is Geisinger.

EXPOSURE

Any cause and stage of CKD, including dialysis and kidney transplant recipients.

OUTCOME

Feasibility of the EHR data transfer, participants' characteristics, and their perspectives on usability and content.

ANALYTICAL APPROACH

Data were collected and analyzed through the registry portal powered by the Pulse Infoframe healthie 2.0 platform.

RESULTS

During the feasibility study, 80 participants completed their profile, and 42 completed a satisfaction survey. Mean age was 57.5 years, 51% were women, 83% were White, and 89% were non-Hispanic or Latino. Of the participants, 60% were not aware of their level of estimated glomerular filtration rate and 91% of their urinary albumin-creatinine ratio.

LIMITATIONS

Challenges for the Network are lack of awareness of kidney disease for many with CKD, difficulty in recruiting vulnerable populations or those with low digital readiness, and loss to follow-up, all leading to selection bias.

CONCLUSIONS

The Network is positioned to become a national and international platform for real-world data that can inform the development of patient-centered research, care, and treatments.

Making an impact on kidney disease in people with type 2 diabetes: the importance of screening for albuminuria

Albuminuria is useful for early screening and diagnosis of kidney impairment, especially in people with pre-diabetes or type 2 diabetes (T2D), which is the leading cause of chronic kidney disease (CKD) and end-stage kidney disease (ESKD), associated with increased mortality, poor cardiovascular outcomes, and high economic burden. Identifying patients with CKD who are most likely to progress to ESKD permits timely implementation of appropriate interventions. The early stages of CKD are asymptomatic, which means identification of CKD relies on routine assessment of kidney damage and function. Both albuminuria and estimated glomerular filtration rate are measures of kidney function. This review discusses albuminuria as a marker of kidney damage and cardiorenal risk, highlights the importance of early screening and routine testing for albuminuria in people with T2D, and provides new insights on the optimum management of CKD in T2D using albuminuria as a target in a proposed algorithm. Elevated urine albumin can be used to detect CKD in people with T2D and monitor its progression; however, obstacles preventing early detection exist, including lack of awareness of CKD in the general population, poor adherence to clinical guidelines, and country-level variations in screening and treatment incentives. With albuminuria being used as an entry criterion and a surrogate endpoint for kidney failure in clinical trials, and with novel treatment interventions available to prevent CKD progression, there is an urgent need for early screening and diagnosis of kidney function decline in people with T2D or pre-diabetes.

Self-Care and Its Predictive Factors in Hemodialysis Patients

Introduction: Chronic kidney disease is a serious problem and patients need active self-care. This study focuses on the relationship between self-care and its predictive factors in hemodialysis (HD) patients.

Methods: This multicenter correlational study was conducted on 201 HD patients referring to HD centers in the west of Tehran, Iran. A multi-stage sampling method was used to select the samples. Data were collected using self-care Scale, Paloutzian-Ellison Spiritual Well-Being Scale, and Connor Davidson Resilience Questionnaires. Data were analyzed using SPSS software version 13 and descriptive statistics and linear regression with stepwise method.

Results: The mean (SD) scores of self-care, resilience, and spiritual well-being were 35.5 (5.69), 53.4 (12.94), and 97.4 (17.9), respectively. Univariate analysis showed that self-care had a statistically significant relationship with gender, occupation, education, being diabetic, and hyperlipidemia. Self-care positively correlated with the resilience and negatively correlated with age. Multivariate regression indicated that the resilience (β = 0.78, P = 0.001), being diabetic (β = -0.09, P = 0.01), and age (β = -0.11, P = 0.005) could be predictors of self-care. These variables accounted for 78% of variance in self-care in HD patients.

Conclusion: Our results showed that resilience was positively correlated with self–care, but being diabetic and age were negatively correlated with self-care in HD patients. Therefore, the health care providers should pay more attention to HD patients who are diabetic and older, as they are at a higher risk of having impaired self-care.

Autopopulus: A Novel Framework for Autoencoder Imputation on Large Clinical Datasets

The adoption of electronic health records (EHRs) has made patient data increasingly accessible, precipitating the development of various clinical decision support systems and data-driven models to help physicians. However, missing data are common in EHR-derived datasets, which can introduce significant uncertainty, if not invalidating the use of a predictive model. Machine learning (ML)-based imputation methods have shown promise in various domains for the task of estimating values and reducing uncertainty to the point that a predictive model can be employed. We introduce Autopopulus, a novel framework that enables the design and evaluation of various autoencoder architectures for efficient imputation on large datasets. Autopopulus implements existing autoencoder methods as well as a new technique that outputs a range of estimated values (rather than point estimates), and demonstrates a workflow that helps users make an informed decision on an appropriate imputation method. To further illustrate Autopopulus' utility, we use it to identify not only which imputation methods can most accurately impute on a large clinical dataset, but to also identify the imputation methods that enable downstream predictive models to achieve the best performance for prediction of chronic kidney disease (CKD) progression.

Big Data in Nephrology

A huge array of data in nephrology is collected through patient registries, large epidemiological studies, electronic health records, administrative claims, clinical trial repositories, mobile health devices and molecular databases. Application of these big data, particularly using machine-learning algorithms, provides a unique opportunity to obtain novel insights into kidney diseases, facilitate personalized medicine and improve patient care. Efforts to make large volumes of data freely accessible to the scientific community, increased awareness of the importance of data sharing and the availability of advanced computing algorithms will facilitate the use of big data in nephrology. However, challenges exist in accessing, harmonizing and integrating datasets in different formats from disparate sources, improving data quality and ensuring that data are secure and the rights and privacy of patients and research participants are protected. In addition, the optimism for data-driven breakthroughs in medicine is tempered by scepticism about the accuracy of calibration and prediction from in silico techniques. Machine-learning algorithms designed to study kidney health and diseases must be able to handle the nuances of this specialty, must adapt as medical practice continually evolves, and must have global and prospective applicability for external and future datasets.

Management of Stage 1 Hypertension in Adults With a Low 10-Year Risk for Cardiovascular Disease: Filling a Guidance Gap: A Scientific Statement From the American Heart Association

High blood pressure (BP) is the leading cause of worldwide cardiovascular disease morbidity and mortality. Patients and clinicians dealing with hypertension have benefited from the evidence of event-based randomized controlled clinical trials. One result from those trials has been the development of evidence-based guidelines. The commitment to using evidence from these event-based randomized trials has been a cornerstone in the development of guideline treatment recommendations. However, in some situations, evidence from event-based trials is not available to guideline writers or clinicians for assistance in treatment decision making. Such is the case for the management of many patients with stage 1 hypertension. The purpose of this scientific statement is to provide information complementary to the 2017 Hypertension Clinical Practice Guidelines for the patient with untreated stage 1 hypertension (systolic BP/diastolic BP, 130-139/80-89 mm Hg) with a 10-year risk for atherosclerotic cardiovascular disease <10% who fails to meet the systolic BP/diastolic goal (<130/80 mm Hg) after 6 months of guideline-recommended lifestyle therapy. This statement provides evidence from sources other than event-based randomized controlled clinical trials and offers therapy options for consideration by clinicians.

Clinical Characteristics of and Risk Factors for Chronic Kidney Disease Among Adults and Children: An Analysis of the CURE-CKD Registry

IMPORTANCE

Chronic kidney disease (CKD) is serious and common, yet recognition and public health responses are limited.

OBJECTIVE

To describe clinical features of, prevalence of, major risk factors for, and care for CKD among patients treated in 2 large US health care systems.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study collected data from the Center for Kidney Disease Research, Education, and Hope (CURE-CKD) registry, an electronic health record-based registry jointly curated and sponsored by Providence St Joseph Health and the University of California, Los Angeles. Patients were adults and children with CKD (excluding end-stage kidney disease) and adults at risk of CKD (ie, with diabetes, hypertension, or prediabetes) identified by laboratory values, vital signs, prescriptions, and administrative codes. Data were collected from January 2006 through December 2017, with analyses performed from March 2019 through November 2019.

EXPOSURES

Diabetes, hypertension, and prediabetes.

MAIN OUTCOMES AND MEASURES

Clinical and demographic characteristics, prevalence, and prescribed medications.

RESULTS

Of 2 625 963 adults and children in the sample, 606 064 adults (23.1%) with CKD had a median (interquartile range [IQR]) age of 70 (59-81) years, with 338 785 women (55.9%) and 434 474 non-Latino white individuals (71.7%). A total of 12 591 children (0.4%) with CKD had a median (IQR) age of 6 (1-13) years, with 7079 girls (56.2%) and 6653 non-Latino white children (52.8%). Median (IQR) estimated glomerular filtration rate was 53 (41-61) mL/min/1.73 m2 among adults and 70 (50-95) mL/min/1.73 m2 in children. Prevalence rates for CKD in adults were 4.8% overall (606 064 of 12 669 700) with 1.6% (93 644 of 6 011 129) during 2006 to 2009, 5.7% (393 455 of 6 903 084) during 2010 to 2013, and 8.4% (683 574 of 8 179 860) during 2014 to 2017 (P < .001). A total of 226 693 patients (37.4%) had category 3a CKD; 100 239 (16.5%), category 3b CKD; 39 125 (6.5%), category 4 CKD; and 20 328 (3.4%), category 5 CKD. Among adults with CKD, albuminuria and proteinuria assessments were available in 52 551 (8.7%) and 25 035 (4.1%) patients, respectively. A renin-angiotensin system inhibitor was prescribed to 124 575 patients (20.6%), and 204 307 (33.7%) received nonsteroidal anti-inflammatory drugs or proton pump inhibitors. Of 1 973 258 adults (75.1%) at risk, one-quarter had diabetes or prediabetes (512 299 [26.0%]), nearly half had hypertension (955 812 [48.4%]), and one-quarter had both hypertension and diabetes or prediabetes (505 147 [25.6%]).

CONCLUSIONS AND RELEVANCE

This registry-based cohort study revealed a burgeoning number of patients with CKD and its major risk factors. Rates of identification and use of kidney protective agents were low, while potential nephrotoxin use was widespread, underscoring the pressing need for practice-based improvements in CKD prevention, recognition, and treatment.