B2-3: Predicting the Risk of End-Stage Renal Disease in Patients with Stage 3 Chronic Kidney Disease: A Pragmatic Risk Score
Bibliographic record
Abstract
BACKGROUND/AIMS: Chronic kidney disease (CKD) is common, but only progresses to end-stage renal disease (ESRD) in a minority of patients. Developing a tool for early identification of patients likely to progress to ESRD would enable clinicians and medical systems to target resources to patients likely to benefit from interventions. METHODS: We conducted a cohort study by linking data among 38,483 patients with stage 3 CKD. We measured patient characteristics during the year before patients became eligible because of their poor kidney function. The patient characteristics were known from previous studies to predict ESRD. We followed patients for up to one year. Seven routinely measured patient characteristics accurately predicted the risk of ESRD. By combining those characteristics with numeric weights for their importance, the risk score identified the subgroup (top decile or tenth) of patients at the highest risk. RESULTS: We observed 461 patients who developed ESRD, a one-year risk of 1.6 per 100 patients. We judged the risk score’s effectiveness by dividing the cohort into ten equal groups or deciles, which included approximately 3,849 patients. Patients at or above the 90th percentile of predicted risk (top decile) were 60 times more likely to suffer a deep infection when compared with patients below the 10th percentile (bottom decile): 11.0 per 100 patients (top decile) versus 0.2 per 100 (bottom decile). The c-statistic was 0.89. CONCLUSIONS: This pragmatic risk score appears to be the first of its kind for predicting ESRD in patients with stage 3 CKD. Previous risk scores in the KPNW population and other populations have predicted ESRD in both earlier and later stages of CKD and may not be sufficiently accurate for KPNW’s intended application. Our risk score can predict a patient’s absolute risk (e.g., 11 per 100 patients). The risk score can also reveal where a patient’s absolute risk ranks as a percentile. The same seven characteristics are more useful to decision-makers when the hazard ratios (numeric weights) can be combined in a risk score to predict the absolute risk.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".