Importance of cystatin C in estimating glomerular filtration rate: the PARADIGM-HF trial
Bibliographic record
Abstract
AIMS: The 2021 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation combining creatinine and cystatin C provides a better estimation of glomerular filtration rate (GFR) compared to the creatinine-only equation. METHODS AND RESULTS: CKD-EPI creatinine-cystatin C equation (creatinine-cystatin) was compared to creatinine-only (creatinine) equation in a subpopulation of Prospective comparison of ARNI with ACEI to Determine Impact on Global Mortality and morbidity in Heart Failure (PARADIGM-HF). Patients were categorized according to difference in eGFR using the two equations: Group 1 (<-10 mL/min/1.73 m2, i.e. creatinine-cystatin more than 10 mL/min lower than creatinine), Group 2 (>-10 and <10 mL/min/1.73 m2), and Group 3 (>10 mL/min/1.73 m2, i.e. creatinine-cystatin more than 10 mL/min higher than creatinine). Cystatin C and creatinine were available in 1966 patients at randomization. Median (interquartile range) eGFR difference was -0.7 (-6.4-4.8) mL/min/1.73 m2. Compared to creatinine, creatinine-cystatin led to a substantial reclassification of chronic kidney disease stages. Overall, 212 (11%) and 355 (18%) patients were reallocated to a better and worse eGFR category, respectively. Compared to patients in Group 2, those in Group 1 (lower eGFR with creatinine-cystatin) had higher mortality and those in Group 3 (higher eGFR with creatinine-cystatin) had lower mortality. Increasing difference in eGFR (due to lower eGFR with creatinine-cystatin compared to creatinine) was associated with increasing elevation of biomarkers (including N-terminal pro-B-type natriuretic peptide and troponin) and worsening Kansas City Cardiomyopathy Questionnaire clinical summary score. The reason why the equations diverged with increasing severity of heart failure was that creatinine did not rise as steeply as cystatin C. CONCLUSION: The CKD-EPI creatinine-only equation may overestimate GFR in sicker patients. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov; Unique Identifier: NCT01035255.
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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 | 0.002 | 0.001 |
| 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".