Accreditation Expired
FSGS: Classification and risk prediction
GlobalA discussion of the challenges in classification and prediction of progression risk in FSGS
FSGS is not a single disease, but a pattern of injury seen in glomeruli. Understanding the cause is critical when making management decisions, but there is currently no singular urine or plasma biomarker that allows for simple differentiation; classification relies on accurate interpretation of clinical and histological features.
Here Prof. An De Vriese discusses her view on classification and prognostication of FSGS. Prof. De Vriese is head of the Division of Nephrology and Infectious Disease at the AZ Sint-Jan hospital in Bruges, Belgium.
By completing this module, you can qualify for 0.25 CME credits. To claim your credits, you must watch the video and successfully pass the post-module assessment.
Nephrologists
After taking part in this activity, learners will be able to :
Professor An De Vriese has no financial relationships to disclose
Liberum IME staff, ACHL staff and others involved with the planning, development, and review of the content for this activity have no relevant affiliations or financial relationships to disclose.
The Academy for Continued Healthcare Learning (ACHL) requires that the faculty participating in an accredited continuing education activity disclose all affiliations or other financial relationships (1) with the manufacturers of any commercial product(s) and/or provider(s) of commercial services discussed in an educational presentation and (2) with any commercial supporters of the activity. All conflicts of interest have been mitigated prior to this activity.
This episode is supported by an educational grant from Travere Therapeutics, who have no influence on the content or choice of faculty.
This module was accredited on the 9th June 2022 and will expire on the 9th June 2023.
The information and data provided in this program was updated and correct at the time of the program development, but may be subject to change.
A discussion of the challenges in classification and prediction of progression risk in FSGS