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Record W2159733393 · doi:10.1177/0883073812449689

Alleviation of Neonatal Sinovenous Compression to Enhance Cerebral Venous Blood Flow

2012· article· en· W2159733393 on OpenAlexaff
Marilyn A. Tan, Elka Miller, Manohar Shroff, Gabrielle deVeber, Adam Kirton

Bibliographic record

VenueJournal of Child Neurology · 2012
Typearticle
Languageen
FieldMedicine
TopicCerebral Venous Sinus Thrombosis
Canadian institutionsAlberta Children's HospitalUniversity of CalgaryChildren's Hospital of Eastern OntarioUniversity of TorontoSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsMedicineSuperior sagittal sinusStraight sinusSupine positionSigmoid sinusCerebral veinsThrombosisRadiologySurgery

Abstract

fetched live from OpenAlex

Occipital bone compression of the superior sagittal sinus occurs in supine neonates. The authors previously showed that this compression is associated with neonatal cerebral sinovenous thrombosis, an important neonatal neurological condition, presumably via increased venous stasis. They hypothesized that a pillow alleviating occipital compression could improve cerebral venous flow. Neonates without cerebral sinovenous thrombosis requiring brain magnetic resonance imaging/venography were prospectively enrolled. Demographics, imaging indications, head position, and superior sagittal sinus compression were recorded. Flow velocities in the anterior and posterior superior sagittal sinus and sigmoid sinus before and after pillow placement were quantified using Doppler ultrasound. A total of 10 neonates (6 female, median postconceptional age 40.6 weeks) were enrolled. Flow velocities increased beyond the superior sagittal sinus compression point following pillow placement: 0.09 ± 0.04 m/sec to 0.15 ± 0.12 m/sec (P = .047) for posterior superior sagittal sinus; 0.10 ± 0.05 m/sec to 0.19 ± 0.15 m/sec (P = .005) for sigmoid sinus. Pillow decompression can improve neonatal cerebral venous flow, representing a potential noninvasive intervention for the prevention and treatment of neonatal cerebral sinovenous thrombosis.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.578

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.267
Teacher spread0.257 · 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

Citations18
Published2012
Admission routes1
Has abstractyes

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