Evaluation of the Risk of Heart Failure in Patients With Chronic Kidney Disease and Type 2 Diabetes Mellitus

Официальное название

Implication of Albuminuria Reduction and Other Cardiorenal Effects on The Risk of Heart Failure in Patients With CKD and T2D

Обзор

The goal of this study, performed entirely with computer programs, is to learn if using a combination of two drugs works better than using one alone, in the treatment of people with chronic kidney disease and type 2 diabetes mellitus. The main questions it aims to answer are: * How many events of heart failure, heart failure hospitalizations, and cardiovascular death happen in each group? * How do serious kidney problems progress in each of the groups? Researchers will compare reference therapy (finerenone) with a combination of finerenone and empagliflozin. There will not be human participants in this study. With the help of artificial intelligence, researchers will recreate a large population of people with chronic kidney disease and type 2 diabetes mellitus. Data on their disease, treatment, and laboratory parameters will be based on and simulated using real data from previous clinical trials conducted with real participants.

Подробное описание

Traditional risk stratification tools, such as the PREVENT (Predicting Risk of cardiovascular disease EVENTs) equations, estimate 10-year risk using static baseline variables. Simply adjusting the UACR input in the PREVENT calculator offers only a crude approximation and does not capture the dynamic, nonlinear effects of ongoing pharmacological treatment, biological hysteresis, and competing risks. To address these limitations, we will develop a high-fidelity digital twin simulation framework powered by the Aeterna Deep computational engine. This in silico trial will project 10-year cardio-renal outcomes for finerenone, empagliflozin, and their combination, while quantifying the mechanistic contribution of UACR reduction relative to other cardio-renal factors. The reference population will be defined according to the CONFIDENCE trial criteria, including adults with chronic kidney disease (eGFR 30-90 ml/min/1.73 m²), type 2 diabetes, and persistent albuminuria (UACR 100-5000 mg/g), receiving maximally tolerated renin-angiotensin system inhibitors. From this base, a synthetic cohort of 100,000 digital twins will be constructed using a four phase instantiation framework designed to ensure biological plausibility. First, marginal distributions for key demographic and clinical variables (age, sex, eGFR, UACR, blood pressure, HbA1c) will be parameterized from validated real-world datasets. Second, nonlinear physiological interdependencies will be reconstructed through multivariate coupling functions to preserve the in vivo covariance structure. Third, individual phenotypes will be generated via high-dimensional stochastic sampling to capture the full range of cardio renal metabolic trajectories. Finally, all instantiated profiles will undergo thermodynamic and biophysical truncation, whereby parameter combinations violating conservation principles or exceeding human homeostatic limits will be excluded and regenerated, ensuring that only physiologically viable digital entities will be retained for downstream analyses.

Первичные конечные точки

• Time to First Occurrence of Incident Heart Failure, Heart Failure Hospitalization, or Cardiovascular Death [Срок оценки: From the beginning of the simulation up to 10 years]
• Time to Onset of End-Stage Kidney Disease, Sustained eGFR <15 ml/min/1.73 m², or ≥40-57% Decline in eGFR from Baseline [Срок оценки: From the beginning of the simulation up to 10 years]

Вторичные конечные точки (4)

• Number of Participants with Non-fatal Acute Myocardial Infarction [Срок оценки: From the beginning of the simulation up to 10 years]
• Number of Participants with Non-fatal Ischemic Stroke [Срок оценки: From the beginning of the simulation up to 10 years]
• Annual Rate of Change in Estimated Glomerular Filtration Rate (eGFR) (ml/min/1.73 m²/year) [Срок оценки: From the beginning of the simulation up to 10 years]
• Proportion of Participants with Transition Between Albuminuria Stages (Normo-, Micro-, Macroalbuminuria) [Срок оценки: From the beginning of the simulation up to 10 years]

Критерии участия

Inclusion Criteria: The same characteristics of the reference population: CONFIDENCE trial (NCT05254002). In brief:

• Patients with chronic kidney disease (eGFR 30-90 ml/min/1.73 m²)
• Persistent albuminuria (UACR 100-5000 mg/g)
• Type 2 diabetes mellitus (T2D) under stable blockade of the renin-angiotensin system (ACEi/ARB)

Exclusion Criteria: The same characteristics of the reference population: CONFIDENCE trial (NCT05254002). In brief:

• Participants with type 1 diabetes (T1D).
• Participant with hepatic insufficiency classified as Child-Pugh C.
• Participants currently treated or who were treated with Finerenone (Kerendia©) within 8 weeks prior to the screening visit.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения

Другое

Центры проведения

Список центров уточняется — проверьте первичный протокол.

Публикации

• Zinman B, Wanner C, Lachin JM, Fitchett D, Bluhmki E, Hantel S, Mattheus M, Devins T, Johansen OE, Woerle HJ, Broedl UC, Inzucchi SE; EMPA-REG OUTCOME Investigators. Empagliflozin, Cardiovascular Outcomes, and Mortality in Type 2 Diabetes. N Engl J Med. 2015 Nov 26;373(22):2117-28. doi: 10.1056/NEJMoa1504720. Epub 2015 Sep 17. PMID 26378978
• Silva A, Vale N. Digital Twins in Personalized Medicine: Bridging Innovation and Clinical Reality. J Pers Med. 2025 Oct 22;15(11):503. doi: 10.3390/jpm15110503. PMID 41295204
• Corral-Acero J, Margara F, Marciniak M, Rodero C, Loncaric F, Feng Y, Gilbert A, Fernandes JF, Bukhari HA, Wajdan A, Martinez MV, Santos MS, Shamohammdi M, Luo H, Westphal P, Leeson P, DiAchille P, Gurev V, Mayr M, Geris L, Pathmanathan P, Morrison T, Cornelussen R, Prinzen F, Delhaas T, Doltra A, Sitges M, Vigmond EJ, Zacur E, Grau V, Rodriguez B, Remme EW, Niederer S, Mortier P, McLeod K, Potse PMID 32128588
• Viceconti M, Henney A, Morley-Fletcher E. In silico clinical trials: how computer simulation will transform the biomedical industry. Int J Clin Trials. 2016;3(2):37-46. Doi: 10.18203/2349-3259.ijct20161408
• Heerspink HJL, Greene T, Tighiouart H, Gansevoort RT, Coresh J, Simon AL, Chan TM, Hou FF, Lewis JB, Locatelli F, Praga M, Schena FP, Levey AS, Inker LA; Chronic Kidney Disease Epidemiology Collaboration. Change in albuminuria as a surrogate endpoint for progression of kidney disease: a meta-analysis of treatment effects in randomised clinical trials. Lancet Diabetes Endocrinol. 2019 Feb;7(2):128- PMID 30635226
• Inker LA, Heerspink HJL, Tighiouart H, Levey AS, Coresh J, Gansevoort RT, Simon AL, Ying J, Beck GJ, Wanner C, Floege J, Li PK, Perkovic V, Vonesh EF, Greene T. GFR Slope as a Surrogate End Point for Kidney Disease Progression in Clinical Trials: A Meta-Analysis of Treatment Effects of Randomized Controlled Trials. J Am Soc Nephrol. 2019 Sep;30(9):1735-1745. doi: 10.1681/ASN.2019010007. Epub 2019 PMID 31292197
• Holtkamp F, Gudmundsdottir H, Maciulaitis R, Benda N, Thomson A, Vetter T. Change in Albuminuria and Estimated GFR as End Points for Clinical Trials in Early Stages of CKD: A Perspective From European Regulators. Am J Kidney Dis. 2020 Jan;75(1):6-8. doi: 10.1053/j.ajkd.2019.07.019. Epub 2019 Oct 28. No abstract available. PMID 31672251
• Bansal N, Katz R, Robinson-Cohen C, Odden MC, Dalrymple L, Shlipak MG, Sarnak MJ, Siscovick DS, Zelnick L, Psaty BM, Kestenbaum B, Correa A, Afkarian M, Young B, de Boer IH. Absolute Rates of Heart Failure, Coronary Heart Disease, and Stroke in Chronic Kidney Disease: An Analysis of 3 Community-Based Cohort Studies. JAMA Cardiol. 2017 Mar 1;2(3):314-318. doi: 10.1001/jamacardio.2016.4652. PMID 28002548

Идентификаторы

NCT: NCT07719621 · HF_CKD_T2D001

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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