External Validation of the Kidney Failure Risk Equation and Re-Calibration with Addition of Ultrasound Parameters
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Progression of CKD toward ESRD is heterogeneous. The Kidney Failure Risk Equation (KFRE) was developed to identify CKD patients at high risk of ESRD. We aimed to externally validate KFRE and to test whether the addition of predefined Duplex ultrasound markers - renal resistive index (RRI) or difference of resistive indices in spleen and kidney (DI-RISK) - improved ESRD prediction. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: The prospective Cardiovascular and Renal Outcome in CKD 2-4 Patients-The Fourth Homburg evaluation (CARE FOR HOMe) study recruits CKD stage G2-G4 patients referred to a tertiary referral center for nephrologic care. Four hundred three CARE FOR HOMe participants enrolled between 2008 and 2012 had available RRI measurements at study inclusion; they were subsequently followed for a mean of 4.4±1.6 years. This subcohort was used to validate KFRE and to assess the added value of the ultrasound markers (new models KFRE+RRI and KFRE+DI-RISK). Model performance was assessed by log-likelihood ratio test, c-statistic, integrated discrimination improvement metrics (for study participants without subsequent ESRD [IDI No ESRD] and for patients with ESRD [IDI ESRD]), and calibration plots. If either new model improved on KFRE, we determined to validate it in an independent cohort of 162 CKD patients. RESULTS: KFRE predicted ESRD in CARE FOR HOMe participants with a c-statistic of 0.91 (95% confidence interval, 0.83 to 0.99). Adding RRI improved the KFRE model (P<0.001), and the KFRE+RRI model was well calibrated; however, the c-statistic (0.91 [0.83-1.00]) was similar, and overall sensitivity (IDI No ESRD=0.05 [0.00-0.10]) or overall specificity (IDI ESRD=0.00 [0.00-0.01]) did not improve. Adding DI-RISK did not improve the KRFE model. In the external validation cohort, we confirmed that the KFRE+RRI model did not outperform KFRE. CONCLUSIONS: Routine Duplex examinations among CKD patients did not improve risk prediction for progression to ESRD beyond a validated equation.
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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 | 0.073 | 0.115 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".