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Record W2086301745 · doi:10.1177/088307380101600701

Idiopathic "Benign" Intracranial Hypertension: Case Series and Review

2001· article· en· W2086301745 on OpenAlexaff
Michael S. Salman, Fenella J. Kirkham, Daune MacGregor

Bibliographic record

VenueJournal of Child Neurology · 2001
Typearticle
Languageen
FieldMedicine
TopicCerebral Venous Sinus Thrombosis
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsMedicinePapilledemaAcetazolamidePseudotumor cerebriVisual acuityLumbar punctureNauseaVomitingSurgeryPediatricsIntracranial pressureAnesthesiaInternal medicineCerebrospinal fluid

Abstract

fetched live from OpenAlex

Idiopathic "benign" intracranial hypertension is an uncommon but important cause of headache that can lead to visual loss. This study was undertaken to review our experience in the diagnosis and management of idiopathic intracranial hypertension, giving special attention to treatments used. A retrospective chart review was conducted on 32 patients diagnosed with idiopathic intracranial hypertension between 1984 and 1995. Subjects included 23 females and ranged in age from 2 to 17.5 years. Headache was the most common symptom, followed by nausea and vomiting, double vision, and visual loss. Papilledema was the most common sign. Others were VIth cranial nerve palsy and compromised visual acuity at or within 3 months of presentation. Management included administration of acetazolamide or corticosteroids, lumboperitoneal shunt, optic nerve fenestration, and repeat lumbar puncture. Treatment combinations were used in 40% of cases. During follow-up, headache, papilledema, and decreased visual acuity persisted for longer than 10 months in a significant number of patients. We conclude that idiopathic intracranial hypertension causes significant short- and long-term morbidity with no proven effective treatment available. A prospective study is needed to establish the indications for treatment and the efficacy of the treatments used.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.146
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.251
Teacher spread0.234 · 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 teacher head, 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

Citations46
Published2001
Admission routes1
Has abstractyes

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