Publication Spotlight: Dr. Jiwani
Interview with Sania Jiwani, MBBS, Cardiac Electrophysiology Fellow, University of Michigan, senior author of Incidence and outcomes of cardiovascular implantable electronic device infections in patients with end-stage kidney disease.
What question did your study aim to answer?
The objective of this study was to assess the incidence, risk predictors, management strategies, and long-term outcomes of cardiac implantable electronic device (CIED) infections and end-stage kidney disease patients (ESKD) undergoing de-novo implantation of these devices.
What inspired you to conduct this study?
Complete hardware removal is a Class I recommendation for CIED infection, with earlier extraction shown to improve survival in the general population. However, we have observed considerable variability in the current clinical practices for managing CIED infections in patients with ESKD. There is a notable lack of data on CIED infections in this patient population, particularly regarding management approaches and outcomes.
Which USRDS datasets did you use to conduct your study?
To conduct this study, we used core files such as patient, payer history, medical evidence, treatment history, and transplant dataset.
Using plain language, please summarize your study conclusions in two or three points.
- Pacemaker and defibrillator infection rates are relatively high in ESKD patients, approaching 1 in 20 during the first 1.3 years after implantation
- The 1- and 3-year mortality after infection is extremely high, with half the patients dead at 1 year and three-quarters dead at 3 years
- Patients who underwent lead extraction had a lower mortality, but only about half the patients were managed with this strategy
Please share a specific insight about working with USRDS data that you learned during the completion of this study.
One positive insight I gained while working with USRDS data during this study was the realization of how comprehensive and rich the dataset was in capturing various patient characteristics and clinical factors. In addition, the USRDS team is extremely helpful and responsive to questions and queries. This allowed for a more detailed analysis, leading to the identification of specific predictors and trends that might have been overlooked in smaller or less structured datasets. Despite the complexities, careful analysis of the data provided a deeper understanding of the current clinical practices that could help improve patient outcomes in the future. This experience reinforced the value of large-scale data in shaping evidence-based practices and improving clinical decision-making.