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Record W2324521335 · doi:10.1055/s-0036-1579820

Sphenoorbital Meningioma: Surgical Series and Design of Intraoperative Management Paradigm

2016· article· en· W2324521335 on OpenAlexaff
Lior Gonen, Eytan Nov, Nir Shimony, Ben Shofty, Georgios Klironomos, Nevo Margalit

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2016
Typearticle
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsToronto Western Hospital
Fundersnot available
KeywordsSkullMeningiomaHyperostosisMedicineSurgeryRadiology

Abstract

fetched live from OpenAlex

Introduction: Sphenoorbital meningiomas (SOMs) are slow-growing infiltrative lesions that are complicated by extensive hyperostosis of the skull base, and characterized by distinct morphological and clinical features. The primary treatment for symptomatic or growing SOM is surgical removal. The main surgical goals are reduction of proptosis and restoration of visual function. Methods: We retrospectively reviewed 27 consecutive patients treated surgically for SOM between 2006 and 2014, with special attention to clinical and radiological presentation, surgical technique, and long-term outcome. Primary outcomes were defined as postoperative visual function and radiological exophthalmos, which were compared with the preoperative baseline. The affect of multiple variables on these outcomes was statistically analyzed, including three specific surgical stages: performing anterior clinoidectomy, placing epidural autologous fat graft, and reconstructing the orbit with rigid material. Results: Study cohort comprised of 24 women and 3 men with mean age of 53.3 ± 12 years (range 27–78 years). Clinical proptosis was the most common presenting sign, followed by visual loss, with rates of 92 and 37%, respectively. Preoperatively, radiological exophthalmos was evident in all patients (EI>1). Complete tumor resection (Simpson grade I/II) was achieved in 51.8%. Extent of resection was limited in 13 cases due to dural invasion to the cavernous sinus (61.5%), superior orbital fissure (84%), and the intraorbital intraconal space (15%). Low rates of both tumor recurrence after complete resection (7.4% in 40.7 average follow-up months) and progression of residual tumor (3.7%) are reported. Surgical resection caused visual improvement in 80% of the patients with impaired vision, and exophthalmos reduction in 77% of the cases. The postoperative reduction of the mean EI was statistically significant ( p < 0.05). Univariate analysis showed two parameters to be statistically significant factors affecting favorable response of visual status to surgical treatment: preoperative visual deficit ( p = 0.0001), and optic canal involvement ( p = 0.04). Two other parameters, cavernous sinus involvement and incomplete tumor resection, showed a tendency toward favorable response, but failed to reach statistical significance. Surgical complications mainly included transient morbidity secondary to cranial nerve injury; Long- term postoperative neurological deficit includes 1 patient with permanent oculomotor nerve palsy (3.7%), and 1 patient (3.7%) with transient decrease in visual acuity that improved gradually. None of the patients experienced postoperative complication that prompted second intervention. Specifically, there were no cases of postoperative epidural hematoma or acute enophthalmos. Conclusions: Surgical goals in the treatment of SOM should be the relief of leading symptoms rather than complete tumor resection, which is commonly limited by tumor invasion to the superior orbital fissure, cavernous sinus, and extraocular muscles. Therefore, tailoring the surgical technique to individual cases is encouraged. According to our experience and review of existing literature, we present an optional intraoperative management paradigm for surgical removal of SOMs, which incorporates selective anterior clinoidectomy, elimination of epidural dead space by placing autologous fat graft, and selective rigid orbital reconstruction. Satisfactory visual, cosmetic and oncological results as well as low morbidity were achieved by following this paradigm.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.044
GPT teacher head0.249
Teacher spread0.206 · 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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