Cardiometabolic Benefits of Renal Diabetes and Obesity MedicationsChristos Argyropoulos
Presentation I gave to UW's ECHO program on 9/21/22 about the cardiorenal protection afforded by SGLT2i/GLP1 Receptor Agonists and Non-steroidal MRAs (finerenone)
Presentation given to our fellowship program about diabetic kidney disease.
2022 update discussing SGLT2i, MRA (e.g. finerenone), health economics and beyond
Survival analysis is an important method for analysis time to event data for biomedical and reliability applications. It is often done with semiparametric methods e.g. the Cox proportional hazards model. In this presentation I discuss an alternative parametric approach to survival analysis that can overcome some of the limitations of the Cox model and provide additional flexibility to the modeler. This approach may also be justified from a Bayesian perspective and the connection is shown as well. Simulations and case studies that illustrate the flexibility of the GAM approach for survival analysis and its equivalent performance to existing methods for survival data are discussed in the text.
The material presented herein are based on two publications:
1) Argyropoulos C, Unruh ML. Analysis of time to event outcomes in randomized controlled trials by generalized additive models. PLoS One. 2015 Apr 23;10(4):e0123784. doi: 10.1371/journal.pone.0123784. PMID: 25906075; PMCID: PMC4408032.
2)Bologa CG, Pankratz VS, Unruh ML, Roumelioti ME, Shah V, Shaffi SK, Arzhan S, Cook J, Argyropoulos C. High performance implementation of the hierarchical likelihood for generalized linear mixed models: an application to estimate the potassium reference range in massive electronic health records datasets. BMC Med Res Methodol. 2021 Jul 24;21(1):151. doi: 10.1186/s12874-021-01318-6. PMID: 34303362; PMCID: PMC8310602.
Heavily based on a presentation I gave for the CMS 2020 National Quality Forum. Emphasis is on dialysis (particularly home dialysis). Discusses regulatory framework, medical devices used to render the services and outcomes of studies performed to day
Journal Club about the Phase 2 study of Selonsertib in Diabetic Kidney Disease to Our Division on 12/9/19.
Also an intro about the Phase 3 study (MOSAIC) we will be launching before the end of the year
Slidedeck of the presentation I gave during the East by Southwest conference, co-organized by the Division of Nephrology (UNM) and the Renal and Electrolyte Division (UPMC)
Geriatric Nephrology (changes in renal physiology, Chronic Kidney Disease, Advanced Care Planning for the elderly patients with CKD, pharmacotherapy of common medical problems in the older individual with chronic kidney disease)
A limited presentation about a) age related renal functional changes b) management of CKD, including advance care planning and transplantation referral c) management of potentially risky drugs in the elderly with CKD (NOACs)
Cardiometabolic Benefits of Renal Diabetes and Obesity MedicationsChristos Argyropoulos
Presentation I gave to UW's ECHO program on 9/21/22 about the cardiorenal protection afforded by SGLT2i/GLP1 Receptor Agonists and Non-steroidal MRAs (finerenone)
Presentation given to our fellowship program about diabetic kidney disease.
2022 update discussing SGLT2i, MRA (e.g. finerenone), health economics and beyond
Survival analysis is an important method for analysis time to event data for biomedical and reliability applications. It is often done with semiparametric methods e.g. the Cox proportional hazards model. In this presentation I discuss an alternative parametric approach to survival analysis that can overcome some of the limitations of the Cox model and provide additional flexibility to the modeler. This approach may also be justified from a Bayesian perspective and the connection is shown as well. Simulations and case studies that illustrate the flexibility of the GAM approach for survival analysis and its equivalent performance to existing methods for survival data are discussed in the text.
The material presented herein are based on two publications:
1) Argyropoulos C, Unruh ML. Analysis of time to event outcomes in randomized controlled trials by generalized additive models. PLoS One. 2015 Apr 23;10(4):e0123784. doi: 10.1371/journal.pone.0123784. PMID: 25906075; PMCID: PMC4408032.
2)Bologa CG, Pankratz VS, Unruh ML, Roumelioti ME, Shah V, Shaffi SK, Arzhan S, Cook J, Argyropoulos C. High performance implementation of the hierarchical likelihood for generalized linear mixed models: an application to estimate the potassium reference range in massive electronic health records datasets. BMC Med Res Methodol. 2021 Jul 24;21(1):151. doi: 10.1186/s12874-021-01318-6. PMID: 34303362; PMCID: PMC8310602.
Heavily based on a presentation I gave for the CMS 2020 National Quality Forum. Emphasis is on dialysis (particularly home dialysis). Discusses regulatory framework, medical devices used to render the services and outcomes of studies performed to day
Journal Club about the Phase 2 study of Selonsertib in Diabetic Kidney Disease to Our Division on 12/9/19.
Also an intro about the Phase 3 study (MOSAIC) we will be launching before the end of the year
Slidedeck of the presentation I gave during the East by Southwest conference, co-organized by the Division of Nephrology (UNM) and the Renal and Electrolyte Division (UPMC)
Geriatric Nephrology (changes in renal physiology, Chronic Kidney Disease, Advanced Care Planning for the elderly patients with CKD, pharmacotherapy of common medical problems in the older individual with chronic kidney disease)
A limited presentation about a) age related renal functional changes b) management of CKD, including advance care planning and transplantation referral c) management of potentially risky drugs in the elderly with CKD (NOACs)