Short-term change in kidney function and risk of end-stage renal disease
Bibliographic record
Abstract
BACKGROUND: It is unclear what degree of change in the eGFR over a 1-year period indicates clinically significant progression, and whether this change adds additional information beyond that obtained by a single eGFR measure alone. METHODS: We included 598 397 adults who had at least two outpatient eGFR measurements (at least 6 months apart) during 1-year accrual period in Alberta, Canada. Change in kidney function (using the first and last eGFR) was defined by change in kidney function category with confirmation based on percent (%) change in eGFR [(last eGFR - first eGFR)/first eGFR × 100]. The groups for change in kidney function were thus defined as: 'certain drop' (drop in CKD category with ≥25% decrease in the eGFR); 'uncertain drop' (drop in CKD category with <25% decrease in the eGFR); 'stable' (no change in CKD category); 'uncertain rise' (rise in CKD category with <25% rise in the eGFR) and 'certain rise' (rise in CKD category with ≥25% increase in the eGFR). Adjusted end-stage renal disease (ESRD) rates (per 1000 person-years) for each group of change in kidney function were calculated using Poisson regression. Adjusted risks of ESRD associated with change in kidney function, in reference to stable kidney function, were estimated. RESULTS: Among the 598 397 participants, 74.8% (n = 447 570) had stable (no change in CKD category), 3.3% (n = 19 591) had a certain drop and 3.7% (n = 22 171) had a certain rise in kidney function. Participants who experienced a certain change in kidney function (both drop and rise) were older, more likely to be female, and had a higher prevalence of comorbidities, in comparison with those with stable kidney function. There were 1966 (0.3%) ESRD events over a median follow-up of 3.5 years. Compared with participants with stable kidney function, after adjustment for covariates, and the first eGFR measurement, those with certain drop had 5-fold increased risk of ESRD (HR: 5.11; 95% CI: 4.56-5.71), whereas those with an uncertain drop had 2-fold increased risk (HR: 2.13; 95% CI: 1.84-2.47). After adjustment for the eGFR and covariates at the last visit, neither a certain nor uncertain drop in the eGFR was associated with an increased ESRD risk. The ESRD risk associated with the last eGFR level, adjusted for the slope over time, were 2.89 (95% CI: 2.35-3.55), 10.98 (95% CI: 8.69-13.87), 35.20 (95% CI: 27.95-44.32) and 147.96 (116.92-187.23) for categories 2, 3a, 3b and 4, respectively, in reference to category 1. CONCLUSIONS: A change in eGFR category accompanied by ≥25% decline (certain drop) is associated with increased ESRD risk. However, this elevated risk is captured by patient characteristics and eGFR at the last visit, suggesting that eGFR trajectories based on more than two serum creatinine measurements over a period longer than 1 year are required to determine ESRD risk and allow more reliable risk prediction.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".