REVEAL CKD: Estimated Glomerular Filtration Rate (eGFR) Decline Before and After a CKD Diagnosis Among Patients With CKD Stage 3
Bibliographic record
Abstract
Background: Studies have shown considerably high rates of undiagnosed early-stage CKD despite guidelines recommending that CKD should be diagnosed and managed as soon as possible to slow progression and prevent complications. However, the benefit of an early diagnosis is not yet fully understood. The aim of this analysis was to describe the potential change in slope of eGFR before and after a CKD diagnosis using data from the REVEAL-CKD study program. Methods: Data were extracted from the US TriNetX database for patients aged ≥18 years with two consecutive eGFR records ≥30 and <60 mL/min/1.73m2 recorded 91-730 days apart from 2015-2020 with an ICD-9/ICD-10 code for CKD after ≥6 months of follow-up. The eGFR decline was estimated before and after CKD diagnosis by fitting an individual linear regression model with time to diagnosis as the only independent variable for the 2-year period before, and up to 2-year period after CKD diagnosis. Estimated slopes were summarized using medians and compared before and after diagnosis using the Wilcoxon rank sum test. The eGFR trajectories over time were estimated by applying a generalized additive model (GAM). Results: The study cohort included 26,851 patients with diagnosed CKD stage 3. In the 2-year period before CKD diagnosis, the median eGFR decline was -4.12 (95% CI: -4.23, -4.02), and median eGFR decline was -0.30 (95% CI: -0.44, -0.14) in the 2-year period after diagnosis (p<0.001). The decline in eGFR slope before and after CKD diagnosis is shown in Figure 1.Figure 1.: eGFR trajectory before and after CKD diagnosis in US patient with CKD stage 3 (GAM with 95% confidence interval)Conclusions: A significant slowing in eGFR decline was observed after a CKD stage 3 diagnosis. This finding may be partially explained by the natural course of renal function decline, and also improved care post-diagnosis given the marked difference around the time of diagnosis. Future analyses will explore initiation of targeted monitoring and treatment in response to a formal diagnosis. Funding: Commercial Support - AstraZeneca
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".