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Visual field deficits following anterior temporal lobectomy: Long‐term follow‐up and prognostic implications

2010· article· en· W1516363023 on OpenAlexaff
Debbie Yam, David A. Nicolle, David A. Steven, Donald Lee, Tiiu Hess, Jorge G. Burneo

Bibliographic record

VenueEpilepsia · 2010
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineSurgeryVisual fieldTemporal lobectomyTemporal lobeLicenseAnesthesiaOphthalmologyEpilepsy

Abstract

fetched live from OpenAlex

PURPOSE: The aim of this study was to assess the incidence of mild (<or=90 degrees) versus severe (>90 degrees from vertical) visual field defects (VFDs) in patients after anterior temporal lobectomy (ATL), and their postoperative improvement over time. METHODS: The angles of postoperative VFDs of 75 patients who underwent ATL were recorded at various time points (1, 2, 6, 12, 18, 24, and 36+ months). RESULTS: Of all 23 patients who came in for their <1 month postoperative appointment, 65% of patients had surgically induced VFDs <90 degrees , whereas 35% had VFDs >90 degrees postoperatively. Patients in the latter group were reported for suspension of their driver's license. However, 38% experienced improvement of their VFD to <90 degrees such that their driver's license could be reinstated. Of patients with any VFD, 18-30% improved on average by a magnitude of 38 degrees within the first year postoperatively. DISCUSSION: Although 35% of the VFDs that occur following temporal lobe surgery are severe, approximately 38% of these patients (especially those with starting postoperative VFDs closer to the 90 degrees angle) experience some improvement shortly after surgery. This may increase their chances of having their driver's license reinstated.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.210
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.293
Teacher spread0.276 · 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 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

Citations27
Published2010
Admission routes1
Has abstractyes

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