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Record W4224114751 · doi:10.3171/case21462

Acetazolamide to treat symptomatic ruptured arachnoid cysts: illustrative cases

2022· article· en· W4224114751 on OpenAlexaff
Isabella Watson, Patrick J. McDonald, Paul Steinbok, Brendon Graeber

Bibliographic record

VenueJournal of Neurosurgery Case Lessons · 2022
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsUniversity of ManitobaBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsAcetazolamideMedicineAsymptomaticSurgeryIntracranial pressurePresentation (obstetrics)NeurosurgeryHydrocephalusAnesthesia

Abstract

fetched live from OpenAlex

BACKGROUND: Arachnoid cysts are benign, often asymptomatic intracranial mass lesions that, when ruptured, may cause seizures, raised intracranial pressure, hemorrhage, and/or loss of consciousness. There is no widely agreed upon treatment, and there is debate as to whether a nonoperative or surgical approach is the best course of action. The carbonic anhydrase inhibitor acetazolamide may be an effective nonoperative approach in treating ruptured arachnoid cysts. OBSERVATIONS: The Pediatric Neurosurgery Clinical Database at BC Children's Hospital from 2000 to 2020 was queried, and four pediatric patients who were treated with acetazolamide after presentation with a ruptured middle cranial fossa arachnoid cyst were identified. All patients showed some degree of symptom improvement. Three of the patients showed complete reabsorption of their subdural collections in the ensuing 6 months. One patient had an inadequate response to acetazolamide and required surgical management. LESSONS: Acetazolamide is a safe and reasonable primary treatment option in pediatric patients with ruptured middle cranial fossa arachnoid cysts, and it may help avoid the need for surgery.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.055
GPT teacher head0.307
Teacher spread0.253 · 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 designCase report
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

Citations6
Published2022
Admission routes1
Has abstractyes

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