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Effect of Pravastatin on Loss of Renal Function in People with Moderate Chronic Renal Insufficiency and Cardiovascular Disease

2003· article· en· W2146311281 on OpenAlexaff
Marcello Tonelli, Lemuel A. Moyé, Frank M. Sacks, Thom Cole, Gary C. Curhan

Bibliographic record

VenueJournal of the American Society of Nephrology · 2003
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPravastatinRenal functionMedicinePlaceboInternal medicineKidney diseaseUrologyEndocrinologyCardiologyCholesterol

Abstract

fetched live from OpenAlex

Limited data suggest that HMG-CoA reductase inhibitors (statins) may slow loss of renal function in individuals with chronic renal insufficiency. This study was conducted to determine whether pravastatin reduced rates of loss of renal function in people with moderate chronic renal insufficiency. This was a post hoc subgroup analysis of a randomized double-blind placebo controlled trial. Data were analyzed from the CARE study (a randomized trial of pravastatin versus placebo in 4159 participants with previous myocardial infarction and total plasma cholesterol < 240 mg/dl). Participants with estimated GFR (MDRD-GFR) < 60 ml/min per 1.73 m(2) body surface area at baseline were considered to have moderate chronic renal insufficiency. Multivariate regression was used to calculate rates of decline in MDRD-GFR for individuals receiving pravastatin and placebo, controlling for prospectively determined covariates that might influence rates of renal function loss. Change in renal function could be calculated in 3384 individuals, of whom 690 (20.4%) had MDRD-GFR < 60 ml/min per 1.73 m(2) and were eligible for inclusion. Among all individuals with MDRD-GFR < 60 ml/min per 1.73 m(2)), the MDRD-GFR decline in the pravastatin group was not significantly different from that in the placebo group (0.1 ml/min per 1.73 m(2)/yr slower; 95% CI, -0.2 to 0.4; P = 0.49). However, there was a significant stepwise inverse relation between MDRD-GFR before treatment and slowing of renal function loss with pravastatin use, with more benefit in those with lower MDRD-GFR at baseline (P = 0.04). Rate of change in MDRD-GFR in the pravastatin group was 0.6 ml/min per 1.73 m(2)/yr slower than placebo (95% CI, -0.1 to 1.2; P = 0.07) in those with MDRD-GFR < 50 ml/min, and 2.5 ml/min per 1.73 m(2)/yr slower (95% CI, 1.4 to 3.6 slower; P = 0.0001) in those with MDRD-GFR < 40 ml/min per 1.73 m(2)/yr. Pravastatin also reduced rates of renal loss to a greater extent in participants with than without proteinuria at baseline (P = 0.006). It is concluded that pravastatin may slow renal function loss in individuals with moderate to severe kidney disease, especially those with proteinuria. These findings require confirmation by a large randomized trial conducted specifically in people with chronic renal insufficiency.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.006
GPT teacher head0.236
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations310
Published2003
Admission routes1
Has abstractyes

Explore more

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