From progression to remission: a new paradigm for success in chronic kidney disease
Bibliographic record
Abstract
Recent advances in treatment of chronic kidney disease (CKD) have changed the clinical paradigm from slowing inevitable progression to achievable remission. Landmark trials involving SGLT2 inhibitors, nonsteroidal MRAs, GLP-1 receptor agonists, and targeted immunotherapies for IgA nephropathy demonstrate that sustained eGFR preservation and normalization of albuminuria are now realistic goals in both diabetic and glomerular kidney diseases. Remission, defined by eGFR slopes (<1 ml/min per 1.73m 2 per year) and absence of albuminuria with a normal eGFR, is increasingly attainable, especially with early detection and combination therapy. We believe that these findings mandate a shift in nephrology's therapeutic focus—from delaying progression to maintaining kidney health. Population-based screening, risk stratification, and implementation of guideline-directed therapy are essential to scale this opportunity. The time has come to redefine success in CKD: remission is not only possible—it must become our standard of care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.034 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.041 |
| Scholarly communication | 0.016 | 0.030 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.010 | 0.025 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".