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Record W4307988958 · doi:10.3390/brainsci12111482

Endoscopic Treatment of Rathke’s Cleft Cysts: The Case for Simple Fenestration

2022· article· en· W4307988958 on OpenAlex
Matthias Millesi, Carolyn Lai, Ruth Lau, Vincent Chen Ye, Kaiyun Yang, Matheus Leite, Nilesh Mohan, Özgür Mete, Shereen Ezzat, Fred Gentili, Gelareh Zadeh, Aristotelis Kalyvas

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBrain Sciences · 2022
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Anomalies
Canadian institutionsPrincess Margaret Cancer CentreToronto Western HospitalUniversity of TorontoUniversity Health Network
FundersUniversity of TorontoUniversity Health Network
KeywordsMedicineSurgeryFenestrationCystHeadaches

Abstract

fetched live from OpenAlex

Background: Rathke’s cleft cysts (RCC) arise from the pars intermedia because of incomplete regression of the embryologic Rathke pouch. A subset of RCC becomes symptomatic causing headaches, visual and endocrinological disturbances such that surgical intervention is indicated. Several points in surgical management remain controversial including operative strategy (simple fenestration (SF) vs complete cyst wall resection (CWR)) as well as reconstructive techniques. Methods: A retrospective analysis was conducted of pathologically confirmed RCC operated on by endoscopic endonasal approach from 2006 to 2019. Pre-operative symptoms, imaging characteristics, operative strategy, symptom response, complications and recurrences were recorded. Results: Thirty-nine patients were identified. Thirty-three underwent SF and six underwent CWR. Worsening pituitary function was significantly increased with CWR (50%) compared to SF (3%) (p = 0.008). All patients underwent “closed” reconstruction with a post-operative CSF leak rate of 5% (3% SF vs 16% CWR, p = 0.287). Six (15%) recurrences necessitating surgery were reported. Recurrence rates stratified by surgical technique (18% SF vs 0% CWR, p = 0.564) were not found to be significantly different. Conclusions: The current series illustrates variability in the surgical management of RCCs. SF with closed reconstruction is a reasonable operative strategy for most symptomatic RCCs cases while CWR can be reserved for selected cases.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.068
GPT teacher head0.360
Teacher spread0.292 · 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