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Record W2093873136 · doi:10.3171/2014.5.peds13481

Factors associated with ventricular catheter movement and inaccurate catheter location: post hoc analysis of the Hydrocephalus Clinical Research Network Ultrasound-Guided Shunt Placement study

2014· article· en· W2093873136 on OpenAlexaff
William E. Whitehead, Jay Riva-Cambrin, John C. Wellons, Abhaya V. Kulkarni, Samuel R. Browd, David D. Limbrick, Curtis J. Rozzelle, Mandeep S. Tamber, Tamara D. Simon, Chevis N. Shannon, Richard Holubkov, W. Jerry Oakes, Thomas G. Luerssen, Marion L. Walker, James M. Drake, John R. W. Kestle

Bibliographic record

VenueJournal of Neurosurgery Pediatrics · 2014
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersNational Institute of Neurological Disorders and Stroke
KeywordsMedicineCatheterHydrocephalusUnivariate analysisUltrasoundPost-hoc analysisSurgeryShunt (medical)Logistic regressionRadiologyMultivariate analysisInternal medicine

Abstract

fetched live from OpenAlex

OBJECT: Shunt survival may improve when ventricular catheters are placed into the frontal horn or trigone of the lateral ventricle. However, techniques for accurate catheter placement have not been developed. The authors recently reported a prospective study designed to test the accuracy of catheter placement with the assistance of intraoperative ultrasound, but the results were poor (accurate placement in 59%). A major reason for the poor accurate placement rate was catheter movement that occurred between the time of the intraoperative ultrasound image and the first postoperative scan (33% of cases). The control group of non-ultrasound using surgeons also had a low rate of accurate placement (accurate placement in 49%). The authors conducted an exploratory post hoc analysis of patients in their ultrasound study to identify factors associated with either catheter movement or poor catheter placement so that improved surgical techniques for catheter insertion could be developed. METHODS: The authors investigated the following risk factors for catheter movement and poor catheter placement: age, ventricular size, cortical mantle thickness, surgeon experience, surgeon experience with ultrasound prior to trial, shunt entry site, shunt hardware at entry site, ventricular catheter length, and use of an ultrasound probe guide for catheter insertion. Univariate analysis followed by multivariate logistic regression models were used to determine which factors were independent risk factors for either catheter movement or inaccurate catheter location. RESULTS: In the univariate analyses, only age < 6 months was associated with catheter movement (p = 0.021); cortical mantle thickness < 1 cm was near-significant (p = 0.066). In a multivariate model, age remained significant after adjusting for cortical mantle thickness (OR 8.35, exact 95% CI 1.20-infinity). Univariate analyses of factors associated with inaccurate catheter placement showed that age < 6 months (p = 0.001) and a posterior shunt entry site (p = 0.021) were both associated with poor catheter placement. In a multivariate model, both age < 6 months and a posterior shunt entry site were independent risk factors for poor catheter placement (OR 4.54, 95% CI 1.80-11.42, and OR 2.59, 95% CI 1.14-5.89, respectively). CONCLUSIONS: Catheter movement and inaccurate catheter placement are both more likely to occur in young patients (< 6 months). Inaccurate catheter placement is also more likely to occur in cases involving a posterior shunt entry site than those involving an anterior shunt entry site. Future clinical studies aimed at improving shunt placement techniques must consider the effects of young age and choice of entry site on catheter location.

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)0.006
metaresearch head score (Gemma)0.005
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 score0.009
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.097
GPT teacher head0.342
Teacher spread0.245 · 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

Citations19
Published2014
Admission routes1
Has abstractyes

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