Fetal growth restriction inhibits childhood growth despite catch-up in discordant identical twins: an observational cohort study

OBJECTIVE

Research suggests that postnatal catch-up growth after fetal growth restriction (FGR) occurs frequently. Yet, postnatal growth in singletons may be influenced by multiple factors. Identical twins with discordant prenatal growth, termed selective FGR (sFGR), can be regarded as a natural experiment eliminating these sources of bias.

DESIGN

Observational cohort study.

METHODS

Monochorionic twins with sFGR born between 2002 and 2017 (aged 3-17 years) were eligible. Growth measurements (height, weight, head circumference, and body mass index) were performed at follow-up. Detailed growth curves documented by a systematic primary care system in the Netherlands were collected. Measurements were converted to standard deviation scores (SDSs). A mixed-effects model was used to assess within-pair SDS difference and individual height SDS relative to target height SDS.

RESULTS

Forty-seven twin pairs (94 children) were included at a median age of 11 (interquartile range 8-13) years. At the last measurement, smaller twins at birth had a lower height SDS [-0.6 vs -0.3, P < .001, median difference 0.5 (95%CI 0.4-0.7)], lower weight SDS [-0.5 vs -0.1, P < .001, median difference 0.8 (95%CI 0.5-1.0)], and lower head circumference SDS [-0.5 vs 0.2, P < .001, median difference 0.8 (95%CI 0.6-0.9)] compared to larger twins. These differences persisted until the age of 17. Smaller twins showed rapid catch-up growth in the first 2 years and reached their target height range between 8 and 11 years.

CONCLUSIONS

Identical twins with discordant prenatal growth maintain a modest but significant difference in height, weight, and head circumference, indicating a persistent, inhibitory effect of an adverse intrauterine environment on childhood growth.

Improving early diagnosis of cardiovascular disease in patients with type 2 diabetes and COPD: protocol of the RED-CVD cluster randomised diagnostic trial

INTRODUCTION

The early stages of chronic progressive cardiovascular disease (CVD) generally cause non-specific symptoms that patients often do not spontaneously mention to their general practitioner, and are therefore easily missed. A proactive diagnostic strategy has the potential to uncover these frequently missed early stages, creating an opportunity for earlier intervention. This is of particular importance for chronic progressive CVDs with evidence-based therapies known to improve prognosis, such as ischaemic heart disease, atrial fibrillation and heart failure.Patients with type 2 diabetes or chronic obstructive pulmonary disease (COPD) are at particularly high risk of developing CVD. In the current study, we will demonstrate the feasibility and effectiveness of screening these high-risk patients with our early diagnosis strategy, using tools that are readily available in primary care, such as symptom questionnaires (to be filled out by the patients themselves), natriuretic peptide measurement and electrocardiography.

METHODS AND ANALYSIS

The Reviving the Early Diagnosis-CVD trial is a multicentre, cluster randomised diagnostic trial performed in primary care practices across the Netherlands. We aim to include 1300 (2×650) patients who participate in a primary care disease management programme for COPD or type 2 diabetes. Practices will be randomised to the intervention arm (performing the early diagnosis strategy during the routine visits that are part of the disease management programmes) or the control arm (care as usual). The main outcome is the number of newly detected cases with CVDs in both arms, and the subsequent therapies they received. Secondary endpoints include quality of life, cost-effectiveness and the added diagnostic value of family and reproductive history questionnaires and three (novel) biomarkers (high-sensitive troponin-I, growth differentiation factor-15 and suppressor of tumourigenicity 2). Finally newly initiated treatments will be compared in both groups.

ETHICS AND DISSEMINATION

The protocol was approved by the Medical Ethical Committee of the University Medical Center Utrecht, the Netherlands. Results are expected in 2022 and will be disseminated through international peer-reviewed publications.

TRIAL REGISTRATION NUMBER

NTR7360.

The Role of Cell Tracing and Fate Mapping Experiments in Cardiac Outflow Tract Development, New Opportunities through Emerging Technologies

Whilst knowledge regarding the pathophysiology of congenital heart disease (CHDs) has advanced greatly in recent years, the underlying developmental processes affecting the cardiac outflow tract (OFT) such as bicuspid aortic valve, tetralogy of Fallot and transposition of the great arteries remain poorly understood. Common among CHDs affecting the OFT, is a large variation in disease phenotypes. Even though the different cell lineages contributing to OFT development have been studied for many decades, it remains challenging to relate cell lineage dynamics to the morphologic variation observed in OFT pathologies. We postulate that the variation observed in cellular contribution in these congenital heart diseases might be related to underlying cell lineage dynamics of which little is known. We believe this gap in knowledge is mainly the result of technical limitations in experimental methods used for cell lineage analysis. The aim of this review is to provide an overview of historical fate mapping and cell tracing techniques used to study OFT development and introduce emerging technologies which provide new opportunities that will aid our understanding of the cellular dynamics underlying OFT pathology.

COVID-19 related anxiety in children and adolescents with severe obesity: A mixed-methods study

Recent studies report negative mental health effects of the COVID-19 related lockdown measures in general paediatric cohorts. Since obesity is a risk factor for COVID-19 in adults, children (including adolescents) with obesity might perceive themselves to be vulnerable. Using a combined quantitative and qualitative approach, we explored COVID-19 related anxiety in paediatric patients with severe obesity in the Netherlands using semi-structured telephone interviews and the Paediatric Quality of Life Inventory (PedsQL) questionnaire, which had also been completed by the study population at baseline in the year prior to the COVID-19 outbreak. In total, 75 families participated in the semi-structured telephone interviews during the lockdown, April 2020. Characteristics of included patients were: median age 10.5 years (interquartile range = 7.6-15.2); 52% female; mean BMI standard deviation score 3.8 (SD = 1.0). COVID-19 related anxiety was reported for 24/75 (32%) children. The mean decrease in PedsQL score between baseline visit and COVID-19 outbreak did not differ between children for whom anxiety was reported vs those for whom it was not (mean change -10.3 ± 36.5 vs -3.3 ± 24.4, P = .54). Self-imposed strict quarantine measures were taken by 19/75 (25%) families. During follow-up, several families reported that the previous contact alleviated their anxiety. In conclusion, healthcare professionals should address possible COVID-19 related anxiety in children with severe obesity. Addressing COVID-19 related anxiety could mitigate its potential negative effects.

Quantification of aortic pulse wave velocity from a population based cohort: a fully automatic method

BACKGROUND

Aortic pulse wave velocity (PWV) is an indicator of aortic stiffness and is used as a predictor of adverse cardiovascular events. PWV can be non-invasively assessed using magnetic resonance imaging (MRI). PWV computation requires two components, the length of the aortic arch and the time taken for the systolic pressure wave to travel through the aortic arch. The aortic length is calculated using a multi-slice 3D scan and the transit time is computed using a 2D velocity encoded MRI (VE) scan. In this study we present and evaluate an automatic method to quantify the aortic pulse wave velocity using a large population-based cohort.

METHODS

For this study 212 subjects were retrospectively selected from a large multi-center heart-brain connection cohort. For each subject a multi-slice 3D scan of the aorta was acquired in an oblique-sagittal plane and a 2D VE scan acquired in a transverse plane cutting through the proximal ascending and descending aorta. PWV was calculated in three stages: (i) a multi-atlas-based segmentation method was developed to segment the aortic arch from the multi-slice 3D scan and subsequently estimate the length of the proximal aorta, (ii) an algorithm that delineates the proximal ascending and descending aorta from the time-resolved 2D VE scan and subsequently obtains the velocity-time flow curves was also developed, and (iii) automatic methods that can compute the transit time from the velocity-time flow curves were implemented and investigated. Finally the PWV was obtained by combining the aortic length and the transit time.

RESULTS

Quantitative evaluation with respect to the length of the aortic arch as well as the computed PWV were performend by comparing the results of the novel automatic method to those obtained manually. The mean absolute difference in aortic length obtained automatically as compared to those obtained manually was 3.3 ± 2.8 mm (p < 0.05), the manual inter-observer variability on a subset of 45 scans was 3.4 ± 3.4 mm (p = 0.49). Bland-Altman analysis between the automataic method and the manual methods showed a bias of 0.0 (-5.0,5.0) m/s for the foot-to-foot approach, -0.1 (-1.2, 1.1) and -0.2 (-2.6, 2.1) m/s for the half-max and the cross-correlation methods, respectively.

CONCLUSION

We proposed and evaluated a fully automatic method to calculate the PWV on a large set of multi-center MRI scans. It was observed that the overall results obtained had very good agreement with manual analysis. Our proposed automatic method would be very beneficial for large population based studies, where manual analysis requires a lot of manpower.