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Record W1998438399 · doi:10.3171/jns.2000.92.6.1050

Modified stereotactic insertion of the Ommaya reservoir

2000· article· en· W1998438399 on OpenAlexaff
Abdul Rahman Al-Anazi, Mark Bernstein

Bibliographic record

VenueJournal of neurosurgery · 2000
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineOmmaya reservoirSurgeryVentricleStereotactic surgeryStereotaxyCatheterExternal ventricular drainHydrocephalusChemotherapyComputer scienceSimulation

Abstract

fetched live from OpenAlex

Ommaya reservoirs are used primarily for the repeated injection of intrathecal chemotherapy for leptomeningeal metastasis from hematopoietic and solid malignancies. Insertion of this device in a relatively large nondisplaced ventricle is not a difficult task, but challenges arise when the ventricle is small and/or displaced. Different techniques have been developed to overcome this difficulty, most of which include the use of stereotactic frames. Further improvements would be beneficial. The technique described in this paper depends on a stereotactic frame; however, the modification proposed by the authors removes the arc system from the surgical field before the actual surgical procedure is begun. Removal of the arc improves access to the surgical field as well as preparation and draping of the surgical site and minimizes potential breaks in sterile technique, which ultimately reduces the incidence of infection. A twist-drill hole along the path of the chosen trajectory becomes an external guide for the ventricular catheter. The technique is easy, user friendly, and results in an unencumbered sterile field and reliable cannulation of small ventricles. A simple stereotactic technique for Ommaya reservoir insertion has been described. It should lower the chance of infection in this group of patients, most of whom have suppressed immune systems.

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)0.000
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 score0.364
Threshold uncertainty score0.228

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 head0.036
GPT teacher head0.274
Teacher spread0.237 · 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

Citations23
Published2000
Admission routes1
Has abstractyes

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