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Record W2948324154 · doi:10.1111/1471-0528.15752

Maternal blood flow to the placenta

2019· article· en· W2948324154 on OpenAlexaff
Federico Prefumo, Stuart Campbell, Eric Jauniaux

Bibliographic record

VenueBJOG An International Journal of Obstetrics & Gynaecology · 2019
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsCReATe Fertility Centre
Fundersnot available
KeywordsMedicinePlacentaBlood flowIntervillous spaceObstetricsNuclear medicinePregnancyCardiologyFetus

Abstract

fetched live from OpenAlex

In the late 1940s, Beker (J Obstet Gynae Br Emp 1948;55:786–65) and Bastiaanse and Mastboom (Ned Tijdschr Geneesk 1949;93:2609–18) hypothesised that placental hypoxia could be the trigger for pre-eclampsia. However, no reliable technique existed at that time to assess maternal blood flow to the placenta. In 1953, McClure Brown and Veall from the Hammersmith Hospital in London described a technique to measure maternal blood flow to the placenta in normotensive and hypertensive pregnancies (J Obstet Gynae Br Emp 1953;60:141–7). They blindly inserted an 18-G needle infusing procaine for analgesia, until they could tap blood from the choriodecidual space. At that point, saline marked with radioactive sodium was rapidly injected with a specially designed tool (Figure 1), and the radioactive decay curve over the placenta was drawn with a Geiger counter. The radioactive sodium washout was thought to be correlated with maternal blood flow, and was slower in hypertensive women, suggesting a 60% reduction in blood flow compared with controls. The Doppler principle was first described by Christian Andreas Doppler in Austria in 1842. Medical applications of ultrasonic Doppler techniques were first implemented by Shigeo Satomura and Yasuhara Nimura at the Institute of Scientific and Industrial Research in Osaka, Japan, in 1955 for the study of cardiac valvular motion and pulsations of peripheral blood vessels (Kaneko Ultrasound Med Biol 1986;12:187–95). The Satomura team, which also included Ziro Kaneko, pioneered transcutaneous Doppler flow measurements in 1959, several years ahead of similar work at the University of Washington in Seattle, USA. It has also become known from the work of Ziro Zaneko and Kanemasa Kato in Satomura's laboratory in 1962, that blood flow can be detected by the ultrasonic Doppler method, largely because blood itself consists of a suspension of ‘uncorrelated point back-scatterers’ (the red cells) with varying density and compressibility, and not because of turbulence in the flow stream as previously thought. In 1966, Kato and Izumi pioneered the directional flow-meter using the local oscillation method where flow directions were detected and displayed. This was a breakthrough in Doppler instrumentation as reverse flow in blood vessels could then be documented. Stuart Campbell and David Griffin at King's College Hospital in London suggested, in 1983, that the shape of the arterial flow velocity waveforms would be more useful in fetal assessment. In the same year, Campbell et al. also reported on the association of abnormal uterine and placental arcuate arterial waveforms with proteinuric hypertension and low birthweight (Lancet 1983;1:675–7). A few years later, Trudinger et al. confirmed that uteroplacental blood flow is reduced in pregnancies complicated by fetal growth restriction or pre-eclampsia (Br J Obstet Gynaecol 1985;92:39–45). This paved the way for non-invasive assessment of uteroplacental blood flow, and for studies on the early prediction of pre-eclampsia, such as the one published by Sovio and Smith in this issue of BJOG (BJOG 2019;126:963–70). The authors declare no conflicts of interest. Completed disclosure of interests form available to view online as supporting information. 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.018
GPT teacher head0.288
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2019
Admission routes1
Has abstractyes

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