Refined characterization of the association between kidney function and mortality in patients undergoing cardiac catheterization
Bibliographic record
Abstract
AIMS: Chronic kidney disease is associated with an increased risk of cardiovascular morbidity and mortality. The level of kidney function at which this risk increases remains to be determined. We sought to characterize the relationship between kidney function and survival among patients with cardiovascular disease (CVD) undergoing cardiac catheterization using estimated glomerular filtration rate (eGFR) and graded refinements in the classification of kidney function. METHODS AND RESULTS: We included 8521 of 11 778 (72.3%) consecutive patients undergoing cardiac catheterization between 1 January 1999 and 31 December 2001 from the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease database. eGFR as a categorical and continuous variable was used to define kidney function. The outcome was all-cause mortality. During a median (interquartile range) follow-up of 2.2 (1.5-3.1) years, and after adjustment for clinical risk factors and severity of coronary disease, there was a steady incremental decrease in survival post-catheterization corresponding to a decline in eGFR categories of 10 mL/min/1.73 m(2). When eGFR was modelled as a continuous variable, there was an increased risk of death noted at an eGFR below 79 mL/min/1.73 m(2). Below an eGFR of 70 mL/min/1.73 m,(2), there was an approximate 17.2% relative increase in risk for every 10 unit decrease in eGFR (95% CI 8.4-26.6%). CONCLUSION: The risk of death post-cardiac catheterization is elevated when eGFR is < or =79 mL/min/1.73 m(2). These findings provide considerable refinement in our understanding of eGFR as a powerful prognostic marker in patients with CVD undergoing cardiac catheterization.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".