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Record W4411928067 · doi:10.3171/case25174

Technical nuance of ventriculoperitoneal shunt placement in a patient with cutis verticis gyrata: illustrative case

2025· article· en· W4411928067 on OpenAlexaff
Youssef J. Hamade, C. Zhu, Elizabeth Ogando‐Rivas, Mohsin Khan, Jeffrey E. Arle, Emanuela Binello, Ekkehard M. Kasper

Bibliographic record

VenueJournal of Neurosurgery Case Lessons · 2025
Typearticle
Languageen
FieldMedicine
TopicHypertrophic osteoarthropathy and related conditions
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineScalpShunt (medical)HydrocephalusSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Cutis verticis gyrata (CVG) is a rare benign scalp condition that causes the formation of skin ridges and furrows. Because of the altered scalp anatomy, this condition can pose unique challenges in neurosurgical procedures. OBSERVATIONS: The authors report the case of a 47-year-old man with CVG and neurosarcoidosis who developed hydrocephalus requiring a ventriculoperitoneal shunt. Initial shunt placement at Kocher's point proceeded without complications. However, the patient presented several months later with shunt failure caused by migration of the proximal catheter. The cause of this was determined to be related to the patient's scalp hypermobility. After shunt revision and fixation of the hardware using titanium plates and screws, the patient had an uneventful recovery and a stable outcome at follow-up. LESSONS: This case emphasizes the importance of preoperative planning and intraoperative measures tailored to CVG patients. Further research is needed to elucidate the condition's neurosurgical implications and optimize procedural outcomes. https://thejns.org/doi/10.3171/CASE25174.

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)0.000
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0060.005
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 head0.016
GPT teacher head0.285
Teacher spread0.269 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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