Renal dysfunction, as measured by the modification of diet in renal disease equations, and outcome in patients with advanced heart failure
Bibliographic record
Abstract
AIMS: This study evaluates the prognostic utility of renal dysfunction estimated by the recently validated modification of diet in renal disease (MDRD) equations and compares it with the currently most promising predictor of prognosis in patients with advanced heart failure. METHODS AND RESULTS: We prospectively studied 182 consecutive patients with advanced chronic heart failure (CHF) referred for consideration of cardiac transplantation, with a median follow-up of 642 days. Glomerular filtration rate (GFR) was estimated using the MDRD equations and plasma taken for NT-proBNP analysis. The primary endpoint of all-cause mortality was reached in 40 patients (13.2% crude 1-year mortality), and the combined secondary endpoint of all-cause mortality or urgent CTx was reached in 44 patients. The mean GFR estimated by MDRD-1 was 58 mL/min/1.73 m(2). The median NT-proBNP concentration was 1505 (517-4014) pg/mL. Although GFR estimated by MDRD-1 was a univariate marker of all-cause mortality, the only predictor of either endpoint independent of other variables was an NT-proBNP concentration above the median. CONCLUSION: NT-proBNP appears superior to GFR estimated by MDRD in patients with advanced CHF. Moreover, NT-proBNP was able to identify patients with a poor prognosis whose GFR was already low.
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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 | 0.001 | 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".