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Record W2089705358 · doi:10.1111/1471-0528.13180

Are long‐term health risks of pre‐eclampsia and intrauterine growth restriction really the same?

2014· letter· en· W2089705358 on OpenAlexaff
Samantha J. Benton, Peter von Dadelszen

Bibliographic record

VenueBJOG An International Journal of Obstetrics & Gynaecology · 2014
Typeletter
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIntrauterine growth restrictionEclampsiaMedicineObstetricsSmall for gestational agePregnancyPlacental insufficiencyPlacentationDiseasePreeclampsiaPlacentaGestational ageGestationFetusInternal medicineBiology

Abstract

fetched live from OpenAlex

Pre-eclampsia and intrauterine growth restriction (IUGR) represent divergent clinical manifestations of placental disease. Although the underlying aetiology of these complications is of placental origin, the mechanisms leading to the differential maternal and fetal responses are not understood. Likewise, although pre-eclampsia and IUGR are risk factors for future maternal health conditions, it is not clear whether the degree of risk is indeed equal for these women (Smith et al. Lancet 2001;357:2002–2006). In this issue of BJOG, Al-Nasiry et al. compared the metabolic syndrome (defined according to criteria outlined by the WHO) in women with a history of pre-eclampsia, compared with women who were normotensive and who delivered a small-for-gestational age (SGA) infant (defined as birthweight <10th percentile for gestational age at delivery and sex). The calculated odds ratios for the metabolic syndrome and its components several months postpartum were increased for women with a history of pre-eclampsia compared with SGA. These findings suggest that the divergent response to placental disease corresponds to differing health risks for women who develop pre-eclampsia versus those who deliver an SGA infant. The development of pre-eclampsia rather than IUGR may relate to the intrinsic maternal threshold for (mal)adapting to the compensatory mechanisms, primarily inflammation, activated in the presence of abnormal placentation (Ness and Sibai Am J Obstet Gynecol 2006;195:40–49). If there are intrinsic differences for coping with systemic inflammation in women who develop pre-eclampsia versus IUGR, it would seem plausible that long-term health risks would indeed differ between these groups. Better understanding of the interaction between placental disease and maternal threshold will help to refine the association between pre-eclampsia and IUGR and the future health of these mothers. It should be noted that this study used SGA as a (poor) proxy for IUGR. As commented by the authors, their SGA group thus contains both constitutionally small fetuses and those with true growth restriction. We would argue that the majority of the women in this group probably delivered constitutionally small fetuses (RCOG Guideline No. 31, 2013), and thus the true association (if any) between the fetal response to placental disease (IUGR) and subsequent maternal risk of the metabolic syndrome may be masked. Future studies should aim to use more concrete criteria to define IUGR, although we recognise that this is problematic in retrospective studies. Overall, this study highlights a finding of differing risk for the metabolic syndrome for mothers with a history of pre-eclampsia or normotensive SGA. Such studies are needed to clarify the association between these complications and long-term health in order to provide women attending postpartum clinics an accurate estimate of their future health risk mechanisms as well as potentially elucidating the mechanisms leading to the divergent maternal and fetal responses to placental disease. The authors have received unrestricted in-kind funding from Alere International.

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)0.010
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0010.004
Scholarly communication0.0040.007
Open science0.0020.001
Research integrity0.0100.008
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 head0.065
GPT teacher head0.358
Teacher spread0.293 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2014
Admission routes1
Has abstractyes

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