Pillar Risk-Based Treatment for Chronic Kidney Disease in People With Type 2 Diabetes: A Narrative Review
Bibliographic record
Abstract
Chronic kidney disease continues to be a significant burden for people living with type 2 diabetes, despite the available guideline-directed treatment options. Traditionally, a stepwise approach has been implemented for the management of chronic kidney disease and type 2 diabetes, which involves the linear sequential initiation of one therapy after the other on the basis of an individual’s treatment outcomes. However, this approach is not beneficial for all individuals, as it can lead to treatment inertia and subsequent disease progression. Therefore, primary care practitioners should consider implementing a more proactive treatment strategy to optimize care. The pillar risk-based approach is an emerging concept with goals of glucose control and blood pressure control as well as comprising simultaneous or rapid sequential initiation of multiple therapies, such as renin–angiotensin system inhibitors (RASi), sodium–glucose cotransporter 2 inhibitors, a nonsteroidal mineralocorticoid receptor antagonist (finerenone), and glucagon-like peptide-1 receptor agonists, which target the different hemodynamic, metabolic, and fibrotic/inflammatory pathways involved in chronic kidney disease and type 2 diabetes. This approach enables earlier chronic kidney disease risk reduction, and the recently published CONFIDENCE trial reported tolerability and efficacy of simultaneous initiation of two of these therapies (finerenone and empagliflozin) in those already receiving RASi. This review article provides primary care practitioners with practical considerations, discussing current guideline-directed treatment options for chronic kidney disease in people with type 2 diabetes in the context of a historical stepwise approach versus the new patient-centric pillar risk-based approach. Chronic kidney disease is a major complication for people with type 2 diabetes. Treatments for people with type 2 diabetes and chronic kidney disease has traditionally followed a stepwise approach, wherein therapies are introduced sequentially, one by one, on the basis of how the person responds to treatment. This stepwise approach to treatment is slow and may take months or years for a person with chronic kidney disease to be on maximal therapy, thus losing crucial time and nephrons. We discuss a potentially different approach to treatment (the pillar risk-based approach) that offers a more proactive strategy and involves starting multiple therapies early and simultaneously or in a rapid stepwise fashion. This pillar risk-based approach integrates blood glucose control and blood pressure control alongside medications that slow progression of chronic kidney disease. Key treatments include renin–angiotensin system inhibitors, sodium–glucose cotransporter 2 inhibitors, a nonsteroidal mineralocorticoid receptor antagonist, and glucagon-like peptide-1 receptor agonists. By addressing multiple disease mechanisms at the same time, the pillar risk-based approach to treatment aims to reduce the risk for kidney failure requiring dialysis or kidney transplantation, as well as cardiovascular events and death. This review article discusses the current guideline-directed treatment options for chronic kidney disease in people with type 2 diabetes in the context of a historical stepwise approach versus the patient-focused pillar risk-based approach.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".