Suboptimal Use of Guideline-Directed Medical Therapy Among Patients with Newly Diagnosed CKD in the United States
Bibliographic record
Abstract
Background: With the recent expansion of the KDIGOClinical PracticeGuideline for the Evaluation and Management of Chronic Kidney Disease (CKD) in 2024 and increasing availability of CKD treatments, greater emphasis is being placed on timely utilization of guideline-directed medical therapy, including renin-angiotensin-aldosterone system inhibitors (RAASi), statins, and sodium-glucose co-transporter 2 inhibitors (SGLT2i). This study examines the use of these classes of medications in newly diagnosed adults with CKD in the United States. Methods: A retrospective study using Optum® Market Clarity™ from 2021 to 2023 was conducted. The cohort included adults with two estimated glomerular filtration rate (eGFR) measures <60ml/min/1.73m2, 3-12 months apart, followed by CKD diagnosis. The percentage of patients receiving a RAASi, statin, or SGLT2i within 90 and 365 days of CKD diagnosis and the baseline sociodemographic characteristics are presented annually from 2021-2023. Results: The cohort comprised 82,061 individuals with laboratory-confirmed diagnosis of CKD (mean age: 74 years, SD: 10). Between 2021 and 2023, annual rates of medication fills within 90 days of CKD diagnosis, remained stable for RAASi (52% to 53%), declined approximately 10% for statins (57% to 52%), and nearly doubled for SGLT2i (5% to 9%). Within 365 days, similar patterns were observed, albeit with higher overall use for each medication class relative to within 90 days (Figure 1). From 2021 to 2023, most patients receiving medical therapy had Stage 3 CKD and the average age of patients and the proportion of those insured by Medicare Advantage have generally increased (Figure 2). Conclusion: In this newly diagnosed CKD cohort, use of guideline-directed medical therapy remains low, thus suboptimal, and for statins is declining slightly. There should be an increased focus on guideline-directed medical therapy of CKD by primary care providers and specialists in nephrology, cardiology and endocrinology fostered by the development and implementation of medication-related quality measures. Additional research on the benefits of timely CKD medical therapy is warranted. Funding: Commercial Support - Boehringer Ingelheim
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".