Proteinuria, impaired kidney function, and adverse outcomes in people with coronary disease: analysis of a previously conducted randomised trial
Bibliographic record
Abstract
OBJECTIVES: To determine whether data on proteinuria are useful for refining estimates of risk based on kidney function alone, and whether the results of kidney function tests can be a useful adjunct to data on proteinuria. DESIGN: Analysis of data from a randomised trial. Impaired kidney function was defined as low glomerular filtration rate (< 60 ml/min/1.73 m2) and proteinuria (> or = 1+ protein) on dipstick urinalysis. SETTING: Study of cholesterol and recurrent events: a randomised trial of pravastatin 40 mg daily versus placebo. PARTICIPANTS: 4098 men and women with previous myocardial infarction. MAIN OUTCOME MEASURES: All cause mortality and cardiovascular events. RESULTS: 371 participants died in nearly 60 months of follow-up. Compared with participants without proteinuria or impaired kidney function, patients with both characteristics were at high risk (hazard ratio 2.39, 95% confidence interval 1.72 to 3.30), and those with only proteinuria or only impaired kidney function were at intermediate risk (1.69, 1.32 to 2.16; 1.41, 1.12 to 1.79, respectively) of dying from any cause. The results were similar for cardiovascular outcomes, including new cases of heart failure, stroke, and coronary death or non-fatal myocardial infarction. A graded increase in the risk of all cause mortality was seen for severity of renal impairment and degree of proteinuria by dipstick. CONCLUSIONS: The presence or absence of proteinuria on dipstick urinalysis may be used to refine estimates of risk based on kidney function alone.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".