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Record W2586285328 · doi:10.1515/jpm-2016-0180

Uterine artery Doppler pulsatility index at 11–38 weeks in ICSI pregnancies with egg donation

2017· article· en· W2586285328 on OpenAlexaff
Annalisa Inversetti, L. Mandia, Massimo Candiani, Irene Cetin, Alessandro Larcher, Valeria Savasi, Enrico Papaleo, Paolo Ivo Cavoretto

Bibliographic record

VenueJournal of Perinatal Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicinePulsatility indexUterine arteryGynecologyConfidence intervalBody mass indexGestational ageObstetricsPregnancyGestationFetusInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Uterine artery Doppler pulsatility index (UtA-PI) may be different in pregnancies with egg donation (ICSI-ED) as compared to conceptions with autologous intra-cytoplasmatic sperm injection (autologous ICSI) and to spontaneous conceptions (SC). METHODS: One hundred and ninety-four pregnant women with different modes of conception (MC) were prospectively evaluated: 53 ICSI-ED, 36 autologous ICSI and 105 SC. To evaluate the effects of different MC on PI, multivariable linear regression (MLR) models predicting UtA-PI were fitted after adjustment for maternal age, body mass index, race, parity, smoking status and gestational age. RESULTS: In the first trimester, at MLR, autologous ICSI was not associated with a significantly different UtA-PI [estimate (EST) 0.01; 95% confidence interval (CI) -0.19, 0.2; P=0.9] when compared to SC. Conversely, MC by ICSI-ED was associated with lower first trimester UtA-PI (EST -0.32; CI -0.55, -0.08; P=0.01) when compared to SC. At MLR, MC by autologous ICSI and by ICSI-ED were not associated with significant differences in the second and third trimester UtA-PI when compared to SC. CONCLUSION: ICSI-ED conception presented lower UtA-PI when compared to SC at 11+0-13+6 weeks but not at later assessments. Correction of UtA-PI measurement specifying the origin of oocyte may be useful in first trimester screening.

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)0.001
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 score0.016
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.028
GPT teacher head0.311
Teacher spread0.283 · 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

Citations24
Published2017
Admission routes1
Has abstractyes

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