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Record W2884294018 · doi:10.1055/s-0038-1633805

An Extended Nasoseptal Flap for Anterior Skull Base Reconstruction: Cadaver Study

2018· article· en· W2884294018 on OpenAlexaff
Fatmahalzahra Banaz, Fahad Alkherayf, André Lamothe, Charles Agbi, Mohammad Alkutbi, Shaun Kilty

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2018
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Surgical Oncology
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineSkullCerebrospinal fluid leakLeakNeurovascular bundleCadaverSurgerySinus (botany)Frontal sinusCerebrospinal fluidAnatomy

Abstract

fetched live from OpenAlex

Background The adequate reconstruction of a skull base defect is paramount for good patient outcomes. The goals of reconstruction for defects produced by the expanded endoscopic endonasal approach (EEA) are identical to those of reconstructing conventional external approach and include the complete separation of the cranial cavity from the sinonasal tract, the elimination of dead space, and preservation of neurovascular and ocular function. The use of nonvascularized free grafts for the repair of a cerebrospinal fluid (CSF) leak following endoscopic sinus surgery and trauma generally results in successful repair of small CSF leaks. However, endoscopic reconstruction with multilayered free grafts for larger dural defects following skull base tumors resection is associated with a postoperative leak rate of 20 to 30%. However, with the advent of pedicled vascularized flaps, in particular, the nasoseptal flap, CSF leak rates have decreased. Despite this success, specifically, the nasoseptal flap is limited in its ability to reach extremely anterior defects and to cover defects involving more than one anatomical segment, such as those involving the posterior frontal table, and the planum sphenoidale. We present the cadaver study results of an extension of the nasoseptal flap for reconstruction of very large midline defects following endoscopic expanded endonasal approach to allow for vascularized reconstruction of the skull base.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0030.000

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 head0.059
GPT teacher head0.336
Teacher spread0.277 · 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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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