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Statin Use Was not Associated with Less Vasospasm or Improved Outcome after Subarachnoid Hemorrhage

2008· article· en· W4250145763 on OpenAlexaboutno aff
Ming-Yuan Tseng, Peter J. Hutchinson, Carole Turner, Marek Czosnyka, Hugh K. Richards, John D. Pickard, Peter J. Kirkpatrick

Bibliographic record

VenueNeurosurgery · 2008
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSubarachnoid hemorrhageVasospasmStatinAnesthesiaCardiologyInternal medicine

Abstract

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To the Editor: The study by Kramer et al. (1) addresses the potential influence of statin therapy after aneurysmal subarachnoid hemorrhage (SAH). This was a retrospective, nonrandomized study comparing the incidence of cerebral vasospasm (detected with computed tomographic angiography), clinical vasospasm, and unfavorable outcome at 6 weeks (measured with the Glasgow Outcome Scale) between those receiving daily simvastatin (80 mg for 14 days [n = 71]), or not (n = 79), after aneurysmal SAH. The authors concluded that statin therapy was not associated with any measurable difference in end points when compared with a similar cohort observed over a 2-year period (1). The authors pointed out that the study was neither a randomized trial nor a matched-controlled study. Hence, the results need to be interpreted with caution. The most important concern relates to the use of historical controls, in that they are known to be prone to many potential biases. Indeed, despite a neutral clinical gain over time, the authors observed significant changes in the management of the culprit aneurysms and the vigilance for detecting vasospasm over the time course of their investigations. Many other confounders may have been missed, and not all of their patients underwent computed tomographic angiography to detect vasospasm. The sample size was small, even though it included the largest number of prospective statin users observed after aneurysmal SAH. Other potential influencing factors were not considered: sepsis, immediate postoperative deficits, hydrocephalus, ventriculitis, and the use of endovascular angioplasty, all of which may have altered the outcome significantly (2,3). Differences in mortality and long-term outcome also were not defined. Thus, the findings may simply reflect a study design that cannot be expected to identify an influence of a given therapy unless that influence is extremely strong. Any positive influence of a single therapy on the complex causes of a poor clinical outcome after aneurysmal SAH is always likely to be relatively small. Nonetheless, given the simplicity, impeccable safety record, short duration of treatment, and very low cost for statin therapy, a small effect is worth pursuing. The closing statement that the influences of statin therapy in aneurysmal SAH can only be determined by means of a large, multicenter, randomized, controlled trial is, of course, correct. Indeed, recruitment for such a study is currently being conducted (SimvaSTatin for Aneurysmal Subarachnoid Haemorrhage [STASH] study; British Heart Foundation SP/08/003; trial size, n = 1600; UK EudraCT 2006-000-277-30, USA Food and Drug Administration IND 75893, Canada CDHA-RS/2007-117). Once completed, STASH will be the largest trial of its type examining the effect of a drug therapy (simvastatin, 40 mg) on clinical outcome (as assessed by the modified Rankin Scale at 6 months) after aneurysmal SAH (4). We would be delighted if Kramer et al. would consider joining us in recruiting to what will hopefully prove a definitive study on the subject (see http://www.stashtrial.com for information on center participation, recruitment details, and trial progress). Ming-Yuan Tseng Peter J. Hutchinson Carole L. Turner Marek Czosnyka Hugh K. Richards John D. Pickard Peter J. Kirkpatrick Cambridge, England

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)0.005
metaresearch head score (Gemma)0.031
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: none
Teacher disagreement score0.006
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.000
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.052
GPT teacher head0.259
Teacher spread0.207 · 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

Citations2
Published2008
Admission routes1
Has abstractyes

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