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Record W3209073941 · doi:10.1097/fm9.0000000000000131

Fetal Growth in Twin Pregnancies and the Choice of Growth Chart

2021· article· en· W3209073941 on OpenAlexaff
Nir Melamed, Liran Hiersch

Bibliographic record

VenueMaternal-Fetal Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsSunnybrook Health Science CentreHealth Sciences Centre
Fundersnot available
KeywordsSingletonTwin PregnancyObstetricsFetusMedicineFetal growthGestationGrowth chartPregnancyPediatricsBiology

Abstract

fetched live from OpenAlex

Background Twin gestations are associated with an increased risk of pregnancy complications such as preterm birth, hypertensive disorders of pregnancy (HDP), and fetal growth restriction (FGR).1–5 Twin pregnancies are characterized by a slower fetal growth compared to singletons during the third trimester. The mechanisms underlying this phenomenon and whether it represents a pathological FGR or a harmless physiologic adaptation are currently unclear.6 One important implication of these questions relates to the growth charts that should be used by care providers to monitor growth of twins. If the slower growth represents a pathology, then singleton growth charts should be used to identify the small twin fetus which may be at an increased risk of mortality and morbidity. If, however, the slower growth of twins reflects a benign adaptation, then twin-based charts may be preferable to avoid overdiagnosis of FGR in twin gestations.7,8 Differences in fetal growth between twin and singleton fetuses A large number of studies have compared the growth of twin fetuses with that of singletons.9–31 The 50th centile curves of some of these charts are compared in Figure 1 along with a representative singleton chart as a reference. Twin fetuses demonstrate reduced growth rate starting at approximately 26–28 weeks based on either birthweight-based on ultrasound-based charts (Fig. 1). Because of these differences, the use of singleton charts in twin pregnancies may result in a relatively large proportion of twin fetuses suspected to be growth restricted due to either ‘falling off the curve’ or being small for gestational age (SGA, defined as weight <10th centile for gestational age).7,12,17,31Figure 1: Comparison of twin-based fetal growth charts. The 50th centile curves are presented for several birthweight-based (A) and ultrasound-based (B) twin chart. Representative birthweight and ultrasound singletons charts (Alexander 199815 and Hadlock 199162, respectively) are shown for comparison (black lines). The arrow points to the point where the 50th centile curves of twin and singleton fetuses starts to diverge (approximately 28–30 weeks for birthweight charts and 26–28 weeks for ultrasound charts). DC: Dichorionic; NICHD: National Institute of Child Health and Human Development; STORK: Southwest Thames Obstetric Research Collaborative.The slower growth of twin fetuses - pathology or physiology? The most intuitive explanation for the slower growth of twins is the failure of the uteroplacental unit to meet the nutritional demands of two fetuses.32–35 However, some have argued against this explanation based on the observation that twins experience slower growth already early in the third trimester, at a time where nutrient supply by the placenta is unlikely to be a limiting factor.30,36,37 In addition, placentas of SGA twins are less likely to demonstrate histopathological evidence of placental insufficiency compared with SGA singletons.38–40 Others suggested that the slower growth of twins is the result of the physical constraint imposed by the uterine size,32,33 or due to placental crowding.33 However, more recent evidence suggests that the slower growth of twins is a physiologic phenomenon that is the result of fetal programming early in pregnancy41,42 through hormonal43,44 and epigenetic mechanisms. 45–47 This hypothesis is supported by evidence that twins may downregulate their growth rate early in gestation,36,48 as well as by studies on fetal reduction.34,49 Predictive value of twin compared with singleton-based charts Ultimately, the decision on whether to use singleton or twin charts should be based on the diagnostic accuracy of the two types of charts for adverse perinatal outcomes. Several studies compared the outcomes of twin fetuses diagnosed as SGA using singleton vs. twin charts. In a study of 7673 women with a twin pregnancy, the association of SGA with the neonatal morbidity was stronger when SGA was diagnosed using a twin chart compared with a singleton chart.7 In another retrospective of 730 dichorionic twin pregnancies, it was found that the use of twin-based charts can decrease the proportion of SGA by approximately 50% and improve the prediction of perinatal complications.50 In another recent study,51 the use of twin charts to diagnose SGA in twins reduced the rate of SGA without affecting the predictive accuracy of SGA for stillbirth. In another recent study, Proctor et al. compared the association between SGA and HDP in twin pregnancies.8 No association between SGA and HDP was found when a singleton chart was used to diagnose SGA. In contrast, the diagnosis of SGA using a twin-based chart was associated with an increased risk of HDP and the magnitude of this association was similar to that seen in singletons, suggesting that the diagnosis of SGA in twins is more likely to be equivalent to the diagnosis of SGA in singletons when a twin-based chart (rather than a singleton-based chart) is used to diagnose SGA in twins. Finally, in a large population-based study of singleton and twin infants born at 36–42 weeks,52 the authors identified the range of absolute birthweight at each gestational week that was associated with the lowest risk of neonatal mortality and morbidity. The lower threshold of this optimal range of birthweight was lower by approximately 150 g for twins compared with singletons across all gestational weeks, suggesting that the relative smallness of twins is not associated with an increased risk of mortality and morbidity. Taken together, these findings provide support to the hypothesis that the relative smallness of twins represents a physiologic adaptation, and that the use of twin charts can avoid over diagnosis of FGR and may result in a diagnosis of FGR that is more clinically relevant. Discussion The question of whether twin-specific charts should be used in twin pregnancies is important from both clinical and research perspectives and can have a considerable impact on the use of resources, unnecessary interventions, and patient anxiety. There is a growing body of evidence suggesting that the use of twin charts can reduce the rate of SGA without compromising the detection of twin fetuses at risk of adverse outcome due to placental insufficiency. In addition, given that twin fetuses are screened with serial ultrasound growth scans,53–57 it is likely that twin fetuses that are truly growth restricted will be detected by serial ultrasound exams irrespective of which chart is used. Finally, measures such as umbilical and fetal Doppler and intertwin size discordance53,55,58–60 are likely to further contribute to the detection of growth restricted twin fetuses irrespective of which chart is being used.61 Still, it should be kept in mind that most of the available data described above are observational in nature, and are further limited by the fact that twin fetuses are usually being followed more closely than singletons and are delivered by 37–38 weeks of gestation. Therefore, adequately-powered trials are likely needed to confirm that the use of twin charts can decrease the rate of SGA without compromising outcomes in twin pregnancies. Finally, further studies are needed to provide better understanding of the mechanisms responsible for the slower growth in twins through correlation with biochemical and angio-genic biomarkers, placental markers of hypoxia, eigenetic markers in the placenta and the fetus, and through correlation with long-term neonatal outcomes.

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)0.001
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 score0.066
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.019
GPT teacher head0.263
Teacher spread0.244 · 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".

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Citations3
Published2021
Admission routes1
Has abstractyes

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