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Previous Spotlights 

Review previous publication spotlights below:

Authors

Olga Charnaya, MD, MS

Pediatric Nephrologist, Johns Hopkins Hospital

The unfinished journey toward transplant equity: an analysis of racial/ethnic disparities for children after the implementation of the Kidney Allocation System in 2014. 

What question did your study aim to answer?

The aim of our study was to broadly assess the landscape of pediatric kidney transplantation in regards to racial and ethnic disparities ranging the entire spectrum of transplant care starting with referral to transplantation, evaluation/listing, waiting time, and posttransplant outcomes.  

What inspired you to conduct this study?

It has been documented in many previous studies and across the world that racial and ethnic minorities often do not have the same access to healthcare and often have worse outcomes. To address this disparity in transplantation, policy changes over the last 10-15 years have been put in place with the aim of ensuring equitable access. Working with a very racially diverse patient population, I was motivated to evaluate the effect of these policy changes and to identify remaining areas where work is needed to improve access and outcomes for my patients.

Which USRDS datasets did you use to conduct your study?

We utilized the CORE and TRANSPLANT datasets for our analysis.

Using plain language, please summarize your study conclusions in two or three points.

  1. Black and Hispanic children are added to the deceased donor waitlist later and are significantly less likely to receive a pre-emptive transplant compared to White children.
  2. The 2014 deceased donor allocation policy change known as the Kidney Allocation System (KAS) has continued to ensure equity in time to deceased donor kidney transplant (DDKT) among children of all races, however time to DDKT increased for all pediatric patients.
  3. Survival of the transplanted kidney has improved for all races after KAS implementation compared to race-specific pre-KAS estimates, but Black children continue to have worse outcomes compared to White children although the difference has narrowed.

Please share a specific insight about working with USRDS data that you learned during the completion of this study.

In addition to the USRDS dataset we also used the SRTR dataset, and interestingly noted differences in how race was identified in the same patients across the two datasets.

Joel T. Adler, MD, MPH

Assistant Professor of Surgery and Perioperative Care, Division of Transplant Surgery, Department of Surgery and Perioperative Care, The University of Texas at Austin

Initial Home Dialysis Is Increased for Rural Patients by Accessing Urban Facilities. 

What question did your study aim to answer?

Advancing American Kidney Health (AAKH) set the goal of 80% of incident ESKD patients receiving home renal replacement therapy or undergoing kidney transplantation by 2025. Historically, access to both quality ESKD care and kidney transplantation has been limited for patients living in rural areas. Our study asked what dialysis facilities were available to rural patients, with a focus on their location, and how likely patients were to achieve home dialysis use.

What inspired you to conduct this study?

AAKH represented a significant change in dialysis policy and reimbursement. Home dialysis and transplantation are associated with improved quality of life for patients, but access to these resources is not distributed in a geographically equitable manner. Such policy changes are always at risk of worsening preexisting disparities and disadvantage; we wanted to assess what resources were available to rural patients to achieve these goals.

Which USRDS datasets did you use to conduct your study?

We utilized the USRDS Standard Analysis Files (SAFs) of Core, Residence, and Treatment History to build the basic patient cohort. Through a special request to USRDS, we also obtained the encrypted dialysis facility provider ID to link facility-level characteristics published in Medicare Dialysis Facility Compare.

Using plain language, please summarize your study conclusions in two or three points.

  1. Despite having access to fewer facilities that offer home dialysis, rural patients with ESKD are more likely to be on home dialysis.
  2. This higher utilization of home dialysis was achieved by rural patients accessing urban dialysis facilities that were more likely to offer home dialysis.
  3. There remains a significant mortality gap between urban and rural patients with ESKD, even when accessing home dialysis.

Please share a specific insight about working with USRDS data that you learned during the completion of this study.

USRDS is an incredibly comprehensive dataset that provides resources for investigators to address questions that are both clinically important and policy relevant. In this study, working closely with the USRDS staff to obtain the correct crosswalk for linkage to Dialysis Facility Compare was crucial to its success. The data is well-documented, and the staff are incredibly helpful and supportive.

Yuzhi Xi, PhD

Postdoctoral Fellow, Emory University 

Effects of short-term ambient PM2.5 exposure on cardiovascular disease incidence and mortality among U.S. hemodialysis patients: a retrospective cohort study.

What question did your study aim to answer?

Is short-term ambient PM2.5 exposure associated with an elevated health risk among in-center hemodialysis patients?

What inspired you to conduct this study?

Our group shares a long-standing interest in understanding the potential impact of environmental exposures on the health of this population with a high burden of disease. Previously, we observed an elevated mortality risk associated with wildfire smoke PM2.5 exposure among US hemodialysis patients. We were curious whether all-sourced ambient PM2.5 exposure, which is much more ubiquitous than wildfire smoke, is also associated with elevated health risk among this population.

Which USRDS datasets did you use to conduct your study?

We utilized USRDS Standard Analysis Files (SAFs) of Core, Transplant, and Hospital to construct the study cohort and extract records on adverse health outcomes.

Using plain language, please summarize your study conclusions in two or three points.

    1. For patients receiving outpatient hemodialysis, exposure to air pollution for a short period of time up to 3 days may increase their chance of having a heart attack, stroke, or dying.
    2. Older patients receiving outpatient hemodialysis appeared to be more susceptible to heart attacks and strokes from air pollution than younger patients.

Please share a specific insight about working with USRDS data that you learned during the completion of this study.

USRDS’s robust data on dialysis clinic visits enables us to accurately link environmental exposures to outcomes on highly granular temporal and spatial scales, which is essential for environmental epidemiological studies but is rarely available from other large datasets.

Julie Paik, MD, ScD, MPH

Assistant Professor of Medicine, Harvard Medical School | Faculty, Division of Renal (Kidney) Medicine and Associate Epidemiologist, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital | Research Scientist and Staff Physician, VA Boston Healthcare System, New England Geriatric Research Education and Clinical Center

Medication Burden and Prescribing Patterns in Patients on Hemodialysis in the USA, 2013-2017.

What question did your study aim to answer?

Our primary goal was to describe the medication burden and prescribing patterns in a contemporary cohort of patients with end-stage kidney disease on hemodialysis.

What inspired you to conduct this study?

As I was seeing patients with kidney disease in my practice who have many comorbidities and take many medications, I wanted to understand whether we were seeing any changes or trends over time in the number and types of medications patients were taking.

Which USRDS datasets did you use to conduct your study?

We used the USRDS database information from January 2013 to December 2017 that included patient and treatment files, as well as claims files for Medicare Parts A, B and D.

Using plain language, please summarize your study conclusions in two or three points.

Patients with ESKD on hemodialysis continued to have a high overall medication burden, with a slight reduction over time accompanied by a decrease in prescribing of several classes of harmful medications. This trend was consistent across subgroups of age, sex, race, and low-income subsidy status. Our study underscores the importance of continually assessing the appropriateness of medications in patients with ESKD on hemodialysis, to avoid exposure to potentially harmful or futile medications.

Please share a specific insight about working with USRDS data that you learned during the completion of this study.

The USRDS data is a remarkable, comprehensive dataset and resource for investigators to address clinically important research questions related to patients with ESKD. The USRDS Researcher’s Guide and support services were very helpful as we conducted our study.

John Danziger, MD, Assistant Professor, Medicine, Harvard Medical School

Associations of Community Water Lead Concentrations with Hemoglobin Concentrations and Erythropoietin-Stimulating Agent Use among Patients with Advanced CKD.

What question did your study aim to answer?

Our primary question was to determine if low levels of lead contamination in drinking water, as found widely in water systems across the United States, might have hematologic toxicity for individuals with advanced kidney disease.

What inspired you to conduct this study?

Patients who choose to do hemodialysis at home must check the quality of their household water. Accordingly, I would frequently review the mineral and metal content of household drinking water. It struck me that drinking water routinely has low levels of environmental toxins, including lead, and made me wonder whether for those with severe kidney disease, whom lack sufficient renal function to excrete ingested metals, with repeated low levels of exposure might lead to progressive metal accumulation and toxicity.

Using plain language, please summarize your study conclusions in two or three points.

Our analysis suggests that ESRD patients living in cities with higher levels of lead in the drinking water have lower hemoglobin concentrations and greater utilization of medications to treat anemia than those without lead contamination. Given that lead toxicity has been linked to a range of neurologic diseases, including depression and cognitive dysfunction, our findings raise important public health questions about the safety of the United States drinking water, and urge further environmental toxicology research.

Please share a specific insight about working with USRDS data that you learned during the completion of this study.

The comprehensive nature of the data, the well described variables, and the ease of use are just amazing! I wish I knew about the USRDS data earlier in my career. My only recommendation is to get the word out about USRDS. As an example, maybe create a training session for fellows annually. We have done this for other Big Data resources.  Termed a Datathon, we pair interested participants with more seasoned investigators, teach them basics, present a question, and then help them extract, analyze, and present their data. A “USRDS Datathon” would be super cool! I would love to participate too.

David Ngendahimana, PhD, MS, Data Scientist, Palo Alto Veterans Institute for Research

Outcomes of Surgical Mitral and Aortic Valve Replacements Among Kidney Transplant Candidates: Implications for Valve Selection.

What question did your study aim to answer?

Since valvular heart disease is highly prevalent among dialysis dependent patients, a frequently encountered question is what type of valve offers them best survival advantage. In addition, whether the best choice of valve is different for those who are listed for kidney transplant. So, we answered those questions: among dialysis patients who are listed for a kidney transplant, what type of valve (bioprosthetic vs. mechanical) is better, in terms of mortality, reoperation and bleeding complications.

What inspired you to conduct this study?

In one of the co-author's nephrology practice, he has seen dialysis patients with both types of valves and did reasonably well after receiving kidney transplant. We had previously reported findings from our systematic review of dialysis patients, when we realized that the question on kidney transplant waitlisted candidates has not been answered before. Kidney transplantation is an instrumental variable in the life expectancy of a dialysis patient and we hypothesized that findings from studies based on dialysis patients may not be extrapolated to transplant waitlisted candidates. Hence, we conducted our study.

Which USRDS datasets did you use to conduct your study?

  • hosp_2010on,
  • hosp_to2009, 
  • patients, 
  • payhist, 
  • TXUNOS_TRR_KI, 
  • death,
  • medevid

Using plain language, please summarize your study conclusions in two or three points.

Our findings suggested that both bioprosthetic and mechanical valves have comparable survival, reoperation rates and major bleeding episodes at both mitral and aortic locations. Hence, the choice of the valve needs to be decided based on individual preferences and through a shared decision-making process.

Please share a specific insight about working with USRDS data that you learned during the completion of this study.

The USRDS data and the research guides are extremely well organized and thoroughly written. In addition, USRDS help desk was easily approachable and responsive to some questions we had during the course of our study. The SAS formats that accompany the USRDS datasets were also very useful and easy to use. One suggestion I have is to consider providing some sample R code snips similar to the SAS snips in the research guide.

Nishank Jain, MD, MPH, Assistant Professor, Division of Nephrology, University of Arkansas for Medical Sciences

Comparative Effectiveness and Safety of Oral P2Y12 Inhibitors in Patients on Chronic Dialysis.

What question did your study aim to answer?

In this study, we wanted to compare effectiveness and safety of commonly prescribed antiplatelet medications (e.g., clopidogrel, prasugrel, and ticagrelor) in patients receiving chronic dialysis treatments.

What inspired you to conduct this study?

Patients on chronic dialysis were systematically excluded from the landmark drug trials in cardiovascular diseases. Compared to the general population, this study population is at a disproportionately higher risk of experiencing cardiovascular events and dying from them. Since antiplatelet drugs are commonly prescribed to patients on dialysis, and scarce data exist to compare choices of one drug over the other for in this population, we wanted to fill this knowledge gap in the literature.

Which USRDS datasets did you use to conduct your study?

We used patient files, treatment files and files including Part A, Part B, and D claims.

Using plain language, please summarize your study conclusions in two or three points.

a. Compared to ticagrelor and clopidogrel users, prasugrel use was associated with a reduction in death from any cause among patients receiving chronic dialysis treatments.

b. This mortality benefit of prasugrel was possibly related to the reduction in the risk for death from cardiovascular cause and for placement of stents in the heart.

c. Since patients on chronic dialysis are at high risk of bleeding from use of antiplatelet drugs, we compared the differences in the risk of bleeding complications in this patient population with the use of P2Y12 inhibitors. Our results demonstrate no differences in the risk of bleeding complications between the drugs.

d. Our work also lays groundwork for clinical trials investigating use of these drugs in patients on dialysis.

Please share a specific insight about working with USRDS data that you learned during the completion of this study.

USRDS data is well structured, and supporting documentation is helpful and thorough. Records of dialysis and transplant history are provided in USRDS data and contain important details about health history.

Babak John Orandi, MD, PhD, MSc, Assistant Professor, School of Medicine - Surgery, University of Alabama Birmingham Medical Center

Obesity as an isolated contraindication to kidney transplantation in the end-stage renal disease population: A cohort study.​

What question did your study aim to answer?

We sought to estimate the number of people on dialysis who have obesity as the sole contraindication to listing for kidney transplant.

What inspired you to conduct this study?

With the growing number of patients on dialysis and the rising obesity epidemic, by 2030 nearly 50% of U.S. adults will have obesity and nearly 25% will have severe obesity—many patients have obesity as a major barrier to transplantation. In my practice, I am increasingly encountering the clinical challenge of assisting patients with both end-stage renal disease and obesity achieving the benefits of kidney transplantation. 

Which USRDS datasets did you use to conduct your study?

1/1/2012-12/31/2014. We used information from the Patient file to identify and then exclude patients who within 90 days after their first ESRD service date: died, received a kidney transplant or were added to the kidney/KP waitlists. Among the ESRD patients that remained eligible for inclusion, USRDS identifiers linked to the ESRD CORE RXHIST file identified patients that had recovered, discontinued dialysis, or been lost to follow-up within 90 days after their first ESRD service date. Further exclusions based on patients' comorbidities identified within 90 days of first ESRD service date that contraindicated transplantation. We identified psychological, medical, and functional status comorbidities based on information in the USRDS Core SAF dataset's MEDEVID file, and diagnosis codes from the 2012-2014 Physician/Supplier claims data.

Our primary exposure was BMI at first ESRD service date from the USRDS Core SAF dataset's MEDEVID file. Primary outcome information, e.g., wait-listing, transplantation, death, and information on most potential confounders were from the 2019 USRDS Core SAF dataset's Patient file; however, among those added to the waitlist and analyzed for time to transplantation, we obtained PRA information from the kidney and kidney-pancreas waitlist files.

Using plain language, please summarize your study conclusions in two or three points.

Nearly 40,000 incident dialysis patients from 2012-2014 had obesity as the only contraindication to wait-listing for kidney transplant. These patients were more likely to be Black, female, and younger.

Please share a specific insight about working with USRDS data that you learned during the completion of this study.

Many of the challenges of working with USRDS data can be managed by first referring to and understanding the available documentation, e.g., the "2019 Researcher’s Guide to the USRDS Database." Nonetheless, some of the data files, e.g., claims data, are quite large and require adequate computer resources.

Beini Lyu, PhD, Research Associate, Johns Hopkins Bloomberg School of Public Health

Arteriovenous Access Type and Risk of Mortality, Hospitalization, and Sepsis Among Elderly Hemodialysis Patients: A Target Trial Emulation Approach.​

What question did your study aim to answer?

We aimed to compare the effect of arteriovenous fistula (AVF) vs. arteriovenous graft (AVG) creation on several critical outcomes among elderly patients on hemodialysis.

What inspired you to conduct this study?

It is not clear whether AVF or AVG is more appropriate for elderly patients on hemodialysis. Results from previous observational studies are inconsistent and may suffer from bias. Ideally, this question would be answered by RCT, but we don’t have such data, yet. We aimed to emulate a RCT using data from USRDS to answer this question.

Which USRDS datasets did you use to conduct your study?

We used the Core, Hospital, CROWNWEb Clinical Data, Institutional Claims, Physician/Supplier Claims, pre-ESRD Institutional Claims, and pre-ESRD Physician/Supplier Claims data.

Using plain language, please summarize your study conclusions in two or three points.

We found no differences between AVGs and AVFs with respect to mortality, sepsis, or all-cause, cardiovascular-related, and infection-related hospitalization after accounting for potential bias and confounding factors. Our work supports equipoise between creation of AVFs versus AVGs among elderly patients who initiate hemodialysis with a catheter.

Please share a specific insight about working with USRDS data that you learned during the completion of this study.

USRDS data are very well-organized and documented. The USRDS Researcher's Guide and appendix and analytic methods were extremely helpful when I started exploring USRDS data.

Nilka Rios Burrows, MPH, MT (ASCP), CKD Initiative Acting Team Lead, CDC Division of Diabetes Translation

Sustained Lower Incidence of Diabetes-Related End-Stage Kidney Disease Among American Indians and Alaska Natives, Blacks, and Hispanics in the U.S., 2000-2016

What question did your study aim to answer?

From 1996 to 2013, the incidence of diabetes-related end-stage kidney disease (ESKD-D) among American Indian and Alaska Native (AIAN) and Black adults declined. In light of the leveling off in ESKD-D incidence in the US diabetic population since 2010 and the significant decline in diagnosed diabetes prevalence among AIANs, we explored whether recent trends in ESKD-D incidence by race or ethnicity had changed.

What inspired you to conduct this study?

We first published the remarkable decline in ESKD-D incidence among AIANs in the CDC’s Vital Signs in January 2017. We wanted to update this report with more years of data to assess whether ESKD-D incidence in AIANs had continued to decline.

Which USRDS datasets did you use to conduct your study?

Patient Core dataset.

Using plain language, please summarize your study conclusions in two or three points.

  • From 2000 to 2016, the rate of new cases of kidney failure from diabetes declined significantly for AIAN (-53%), Hispanic (-33%), and Black adults (-20%); for White adults, however, the rate increased by 10%.
  • Despite these significant declines, kidney failure from diabetes for AIAN, Hispanic, and Black adults in 2016 remained nearly twice as high or higher than for White adults. Continued efforts in diabetes and kidney disease management are very important to sustain the declining trend in these populations.
  • The significant reduction (-53%) in kidney failure from diabetes among AIAN adults parallels sustained improvements in glycemic, lipid, and blood pressure control for AIANs and likely resulted from improvements in patient care and services funded by the Special Diabetes Program for Indians.

Please share a specific insight about working with USRDS data that you learned during the completion of this study. (No detail is too small.)

USRDS data and the publication findings were instrumental in documenting improved outcomes among AIANs with diabetes and in reauthorizing Congressional funding for the Special Diabetes Program for Indians. The Indian Health Service experience serves as a model for diabetes management in other healthcare systems, especially those serving populations at high risk for diabetes complications and as inspiration to replicate their success and impact on kidney disease outcomes.

Thomas Mavrakanas, MD, MSc, Assistant Professor, Department of Medicine, Division of Experimental Medicine, McGill University

Prasugrel and Ticagrelor in Patients with Drug-Eluting Stents and Kidney Failure

What question did your study aim to answer?

To determine whether prasugrel or ticagrelor is associated with improved cardiovascular outcomes compared with clopidogrel in patients with kidney failure on maintenance dialysis treated with drug-eluting stents.

What inspired you to conduct this study?

The high incidence of cardiovascular disease and major bleeding among patients with kidney failure on maintenance dialysis.

Which USRDS datasets did you use to conduct your study?

Core, Institutional Claims 2011-2015, Physician Supplier Claims 2011-2015, Part D 2011-2015, Pre-ESRD Institutional Claims 2011-2015, Pre-ESRD Physician Supplier Claims 2011-2015, Pre-ESRD Part D 2011-2015.

Using plain language, please summarize your study conclusions in two or three points.

The newer, more potent antiplatelet agents, prasugrel and ticagrelor, were of similar effectiveness as clopidogrel in patients on maintenance dialysis treated with a drug-eluting stent, and they were relatively well tolerated, with no significant increase in clinically significant bleeding.  

Both agents could be considered in selected patients on maintenance dialysis with anatomically complex coronary disease treated with drug-eluting stents. The potential benefit should be balanced against a potentially higher risk of clinically relevant bleeding.

Please share a specific insight about working with USRDS data that you learned during the completion of this study.

USRDS is a comprehensive database offering probably the largest dataset of its kind in the world. Although the database is relatively complex to work with, it provides very important information in an understudied population and is an invaluable tool for researchers in kidney failure.

Jesse Schold, PhD, MStat, MEd, Department of Quantitative health Sciences, Cleveland Clinic

Failure to Advance Access to Kidney Transplantation over Two Decades in the United States

What question did your study aim to answer?

Our primary aims were to evaluate rates of patients placed on the kidney transplant waiting list over the past two decades in the United States. In addition, we sought to understand whether rates of waitlist placement had changed over time among groups with historically lower rates.

What inspired you to conduct this study?

Considerable efforts, resources, and research have tried to identify barriers to transplant among patients with end-stage kidney disease in the United States. Our motivation for the study was to evaluate how the culmination of these efforts has led to significant changes in this important process of care for this population.

Which USRDS datasets did you use to conduct your study?

We used the USRDS core research files, including the patient, medevid, waitlist, and transplant files.

Using plain language, please summarize your study conclusions in two or three points.

Despite broad recognition of barriers to transplant and substantial efforts to improve access to transplant, rates of placement on the transplant waiting list have not improved over a two-decade period in the United States. In addition, marked disparities in access to the waiting list among patients have remained stagnant over the same period.  Cumulatively, results suggest that more prominent efforts may be needed to improve access to transplant and attenuate disparities in care in this population.

Please share a specific insight about working with USRDS data that you learned during the completion of this study.

There are unlimited numbers of important research questions to address with these data to inform healthcare policy, clinical care, and the research community. Other extensions of this research and the ability to merge these data with other epidemiologic data would provide additional important insights.

USRDS Coordinating Center (CC)