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Record W2370623593 · doi:10.1111/anae.13494

Effect of different surgical positions on the cerebral venous drainage: a pilot study using healthy volunteers

2016· article· en· W2370623593 on OpenAlexaff
Tze Yeng Yeoh, Aaron Hao Tan, Pirjo Manninen, Vincent Chan, Lashmi Venkatraghavan

Bibliographic record

VenueAnaesthesia · 2016
Typearticle
Languageen
FieldMedicine
TopicNeurosurgical Procedures and Complications
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineSupine positionInternal jugular veinAnesthesiaJugular veinExternal jugular veinVenous ValvesVeinSurgery

Abstract

fetched live from OpenAlex

Excessive neck flexion and rotation in certain surgical positions may cause kinking of the internal jugular vein that obstructs cerebral venous blood flow and results in elevated intracranial pressure. The objective of this study was to measure internal jugular vein flow and identify potential impediments to venous flow in supine, prone, and park bench positions using non-anaesthetised volunteers. Twenty-seven volunteers were recruited. Venous flow rate was derived from ultrasound measurements of the vessel cross-sectional area and flow velocity. Change from supine to prone position produced a significant increase in both jugular vein cross-sectional areas without affecting venous flows. In the right park bench position, the right internal jugular vein cross-sectional area decreased from 1.2 to 0.9 cm(2) (p = 0.027) without substantive changes in mean venous flow rate (p = 0.91) when compared with supine. In summary, the internal jugular vein flow was not compromised by either prone or park bench positions in non-anaesthetised volunteers, and careful positioning may prevent kinking of the jugular vein. Further studies in anaesthetised and ventilated patients are needed to validate these results for clinical practice.

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 score0.274
Threshold uncertainty score0.249

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 head0.030
GPT teacher head0.308
Teacher spread0.278 · 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

Citations17
Published2016
Admission routes1
Has abstractyes

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