Mortality, Health Care Burden, and Treatment of CKD: A Multinational, Observational Study (OPTIMISE-CKD)
Bibliographic record
Abstract
Key Points Newly detected, moderately progressed CKD is associated with high clinical risks and health care costs. Most patients with moderately progressed CKD do not have diabetes and are at the same clinical risk as those with diabetes. Substantial inertia with kidney-protective treatment is observed when moderately progressed CKD is detected. Background Kidney-protective treatments (renin–angiotensin system inhibitors and sodium–glucose cotransporter-2 inhibitors [SGLT-2is]) can delay CKD progression, cardiovascular events, and death. Methods This observational cohort study used electronic health records and claims data from Japan, Sweden, and the United States to assess 1-year mortality/hospitalization event rates per 100 patient-years (PYs), cumulative hospital health care costs per patient, and kidney-protective treatment use before/after SGLT-2i (dapagliflozin) approval for CKD (2021) for patients with CKD stage 3–4 with/without type 2 diabetes (T2D). Results Among 449,232 patients (across-country median age range 74–81 years), 79% did not have T2D. Prevalence ranges for atherosclerotic cardiovascular disease and heart failure were 20%–36% and 17%–31%, respectively. Baseline kidney-protective treatment (renin–angiotensin system inhibitor and/or SGLT-2i) use was limited, especially among patients without T2D. Event rates were high for CKD (11.4–44.4/100 PYs) and heart failure (7.4–22.3/100 PYs). Up to 14.6% of patients had died within 1 year. Hospital costs were higher for CKD and heart failure than for atherosclerotic cardiovascular disease. After incident CKD, kidney-protective treatment initiation was low (8%–20%) and discontinuation was high (16%–27%), especially among patients without T2D. Conclusions Incident CKD was associated with substantial morbidity, mortality, costs, and undertreatment, especially in patients without T2D, who represented the majority of patients. This highlights an urgent need for early CKD detection and better kidney-protective treatment use in moderate CKD.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".