Publication Spotlight: Dr. Ngendahimana
Read the below interview with David Ngendahimana, PhD, MS, Data Scientist, Palo Alto Veterans Institute for Research and author of 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?
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.