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Outcome of Surgical Clipping of Unruptured Aneurysms as it Compares with a 10-year Nonclipping Survival Period

2007· letter· en· W2021134225 on OpenAlexaboutno aff
David A. Steven

Bibliographic record

VenueNeurosurgery · 2007
Typeletter
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineClipping (morphology)BleedAneurysmSubarachnoid hemorrhageSurgeryRadiology

Abstract

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To the Editor: In their recent article, Krisht et al. (1) compared the outcome of surgical clipping of unruptured aneurysms with a 10-year non-clipping survival period. To accomplish this, they extrapolated the 5-year risk of subarachnoid hemorrhage (SAH), as reported by the International Study on Unruptured Intracranial Aneurysms (ISUIA) (2), to a 10-year period and applied this risk to a group of 116 of their own patients. The authors then compared their results with the estimated morbidity and mortality rates if the aneurysms had been left unclipped. There are two items that deserve attention, one of which bolsters and another that detracts from their conclusions. First, there seems to be a miscalculation in the number of expected bleeds if the aneurysms had been left unclipped. In Figure 3 of the article, the authors have calculated the number of expected bleeds over 5 years for the 7 to 12 mm and large aneurysm groups as 1.2 and 4, respectively. The 5-year ISUIA SAH risk seems to have been applied to the percentage of aneurysms rather than the absolute number. The actual number of expected bleeds should be 2.6% × 70 for aneurysms 7 to 12 mm in diameter and 14.5% × 41 for large aneurysms for an expected bleed rate of 1.8 and 5.9, respectively. The calculation for giant aneurysms is correct. The total number of expected bleeds over 5 years should, therefore, be 12.5 rather than 10. Consequently, the 10-year rupture rate and expected morbidity and mortality rates have been underestimated. On the other hand, although the authors have applied the ISUIA rupture rates to their cohort, they did not evaluate surgical outcome in the same manner. In ISUIA, surgical morbidity was defined as a Rankin score of 3 to 5, a score of less than 24 on the MMSE, or a score of less than 27 on a telephone interview for cognitive status. In the study by Krisht et al., only the Rankin score was recorded. In ISUIA, 4.4% of Group 1 patients (no history of SAH) and 2.4% of Group 2 patients (previous history of SAH) had a Rankin score of 3 to 5. This is comparable to the 3.44% observed by the authors. However, the ISUIA investigators identified an additional 5.5% of Group 1 patients and 7.1% of Group 2 patients who had a poor cognitive status that was not reflected in the Rankin score. Unfortunately, Krisht et al. did not measure the cognitive outcomes in their patients and, as a result, were likely to significantly underestimate the true surgical morbidity in their cohort. Although one could argue that these two items balance to some degree, their very presence raises questions about validity of the study's conclusions. David A. Steven London, Canada

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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)0.003
metaresearch head score (Gemma)0.020
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 score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.046
GPT teacher head0.305
Teacher spread0.259 · 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

Citations1
Published2007
Admission routes1
Has abstractyes

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