Effect of Pravastatin on Rate of Kidney Function Loss in People With or at Risk for Coronary Disease
Bibliographic record
Abstract
BACKGROUND: Limited data suggest that HMG-CoA reductase inhibitors (statins) reduce rates of kidney function loss. We performed this analysis to determine whether pravastatin reduced the rate of kidney function loss over approximately 5 years in people with or at high risk for coronary disease. METHODS AND RESULTS: This was a post hoc subgroup analysis of data from 3 randomized double-blind controlled trials comparing pravastatin 40 mg/d and placebo in subjects with a previous acute coronary syndrome or who were at high cardiovascular risk. The primary outcome was the rate of change in estimated glomerular filtration rate (GFR; in mL/min per 1.73 m2/y). The Modified Diet and Renal Disease Study (MDRD) and Cockcroft-Gault equations were used to estimate GFR. We studied 18,569 participants, 3402 (18.3%) of whom had moderate chronic kidney disease as defined by an estimated GFR of 30 to 59.9 mL/min per 1.73 m2 body surface area. In subjects with moderate chronic kidney disease at baseline, pravastatin reduced the adjusted rate of kidney function loss by approximately 34%, although the absolute reduction in the rate of loss was small (0.22 mL/min per 1.73 m2/y by MDRD-GFR; 95% CI, 0.07 to 0.37). Pravastatin did not reduce the frequency of > or =25% decreases in kidney function in this group when MDRD-GFR was used to estimate GFR (relative risk [RR], 0.84; 95% CI, 0.66 to 1.06). When all 18,569 subjects were considered, pravastatin reduced the adjusted rate of kidney function loss by 8% (0.08 mL/min per 1.73 m2/y by MDRD-GFR; 95% CI, 0.01 to 0.15) and the risk of acute renal failure (RR, 0.60; 95% CI, 0.41 to 0.86) but did not significantly reduce the frequency of a > or =25% decline in kidney function by MDRD-GFR (RR, 0.94; 95% CI, 0.88 to 1.01). CONCLUSIONS: Pravastatin modestly reduced the rate of kidney function loss in people with or at risk for cardiovascular disease. However, the primary indication for the use of statins in people with or at risk for coronary events remains the reduction in mortality that results from their use.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".