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Record W1492564831 · doi:10.1002/uog.13849

<scp>OP</scp>22.04: Low pulmonary blood flow demonstrated by Doppler and <scp>MRI</scp> in late onset <scp>IUGR</scp>

2014· article· en· W1492564831 on OpenAlexaff
Liqun Sun, Varsha Thakur, Edgar Jaeggi, John‏ Kingdom, Rory Windrim, John G. Sled, Christopher K. Macgowan, Mike Seed

Bibliographic record

VenueUltrasound in Obstetrics and Gynecology · 2014
Typearticle
Languageen
FieldMedicine
TopicFetal and Pediatric Neurological Disorders
Canadian institutionsHospital for Sick ChildrenMount Sinai HospitalSickKids FoundationUniversity of Toronto
Fundersnot available
KeywordsMedicineFetusUmbilical arteryHemodynamicsCardiologyPulmonary arteryGestational ageInternal medicineMiddle cerebral arteryUmbilical veinBlood flowPregnancy

Abstract

fetched live from OpenAlex

Animal and human studies show a reduction in placental oxygen delivery results in pulmonary vasoconstriction and cerebral vasodilation [1]. We investigated human fetal pulmonary hemodynamics in growth restricted fetuses by US and MRI compared with controls. 26 fetuses (Mean gestational age 35.85 ± 1.23 weeks) were recruited during the third trimester and underwent imaging on commercial 1.5T MR and Ultrasound systems. We measured pulmonary blood flow by PC MRI and T2 in the umbilical vein and main pulmonary artery using T2 mapping, according to previously published techniques [2,3]. Flow velocity waveforms in the middle cerebral artery, umbilical artery and main pulmonary artery branches were characterized using Doppler. Table 1 shows the comparison between US and MRI parameters of fetal hemodynamics in 6 fetuses with IUGR and 20 normal fetuses. There were three IUGR fetuses with retrograde diastolic flow in the pulmonary artery branches and reduced MCA pulsitility index (PI). PBF was inversely proportional to UV T2 and OP22.04: Table 1. Fetal hemodynamics by US and MRI MPA T2, with a trend towards a correlation between fetal DO2 and PBF, as shown in Figure 1. Supporting information can be found in the online version of this abstract Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

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)0.001
metaresearch head score (Gemma)0.065
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.065
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.007
GPT teacher head0.208
Teacher spread0.202 · 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.

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

Citations1
Published2014
Admission routes1
Has abstractyes

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