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Record W2045364545 · doi:10.3171/2009.9.jns09277

Cerebrospinal fluid shunt insertion: techniques of peritoneal catheter placement separate from abdominal fascial and peritoneal incisions

2009· article· en· W2045364545 on OpenAlexaff
Abdurrahim Elashaal, Michael Corrin, Michael D. Cusimano

Bibliographic record

VenueJournal of neurosurgery · 2009
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineAbdominal wallShunt (medical)CatheterSurgeryPeritoneal cavityCerebrospinal fluidAbdominal cavityHydrocephalusInternal medicine

Abstract

fetched live from OpenAlex

Good abdominal wall closure is one of the basic surgical skills and is a common feature of almost all modern-day CSF shunt operations. The fact that some patients require multiple abdominal operations highlights the need for a simple and effective technique for peritoneal catheter insertion through the abdominal wall and abdominal wall closure. Although technically simple, abdominal wall closure becomes more complex when combined with the requirement to maintain CSF shunt function in cases in which the shunt catheter passes through the abdominal wall into the peritoneal cavity. In this report, the authors describe a simple technique for passing the peritoneal catheter of a ventriculoperitoneal shunt through the abdominal wall on a pathway separate from the fascial opening. This technique minimizes the risk of abdominal wall-related complications and is especially important in high-risk patients such as those with obesity and/or diabetes and in children.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.003
Open science0.0010.002
Research integrity0.0020.002
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 head0.024
GPT teacher head0.280
Teacher spread0.255 · 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

Citations3
Published2009
Admission routes1
Has abstractyes

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