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Record W2163468171 · doi:10.1161/strokeaha.107.505875

A Randomized, Double-Blind, Placebo-Controlled Pilot Study of Simvastatin in Aneurysmal Subarachnoid Hemorrhage

2008· letter· en· W2163468171 on OpenAlexaff
Sherry H.-Y. Chou, Eric E. Smith, Neeraj Badjatia, Raul G. Nogueira, John R. Sims, Christopher S. Ogilvy, Guy Rordorf, Cenk Ayata

Bibliographic record

VenueStroke · 2008
Typeletter
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsColumbia College
FundersNational Center for Research ResourcesNational Institutes of Health
KeywordsMedicineSimvastatinSubarachnoid hemorrhageVasospasmPlaceboAnesthesiaIschemiaStatinCerebral vasospasmInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Studies suggest statins ameliorate aneurysmal subarachnoid hemorrhage (SAH)-induced cerebral vasospasm and ischemic complications. We tested safety and feasibility of simvastatin 80 mg/d for vasospasm prevention in SAH patients. METHODS: Thirty-nine statin-naïve Fisher grade 3 SAH subjects were double-blind randomized to receive simvastatin 80 mg/d (n=19) or placebo (n=20), stratified by Hunt and Hess grade. Primary end points were death and drug morbidity. RESULTS: Mortality was 3/20 in the placebo and 0/19 in the simvastatin group. Study drug was withdrawn in 1 subject in each treatment group for reversible liver enzyme or creatine phosphokinase elevation. Angiographically-confirmed vasospasm occurred in 8/20 placebo and 5/19 simvastatin-treated subjects. Vasospasm-related ischemic infarcts developed in 5/20 placebo and 2/19 simvastatin-treated subjects. CONCLUSIONS: Simvastatin for the prevention of delayed cerebral ischemia is safe and feasible after SAH. A larger study is needed to test its efficacy.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.039
GPT teacher head0.282
Teacher spread0.243 · 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 designRandomized trial
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

Citations144
Published2008
Admission routes1
Has abstractyes

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