Modifiable Predictors Associated with Having a Gestational Weight Gain Goal

The goal of this paper was to determine predictors of having a weight gain goal in early pregnancy. In 2008, we administered a 48-item survey to 249 pregnant women attending obstetric visits. We examined predictors of women having a goal concordant or discordant with 1990 Institute of Medicine (IOM) guidelines, vs. no goal, using binary and multinomial logistic regression. Of the 292 respondents, 116 (40%) had no gestational weight gain goal, 112 (39%) had a concordant goal and 61 (21%) had a goal discordant with IOM guidelines. Predictors of a guideline-concordant goal, vs. no goal, included sugar sweetened beverage consumption < vs. ≥ 1 serving per week (OR = 2.4, 95%CI: 1.1, 5.7), physical activity ≥ vs. <2.5 h per week (OR = 3.6, 95%CI: 1.7, 7.5), agreeing that `I tried to keep weight down not to look pregnant' (OR = 14.3, 95%CI: 1.4, 140.5). Other predictors only of having a discordant goal (vs. no goal) included agreeing that `as long as I am eating well, I don't care how much I gain' (OR = 0.3, 95%CI: 0.2, 0.8) and agreeing that `if I gain too much weight one month, I try to keep from gaining the next' (OR = 4.1, 95%CI: 1.6, 10.4). Women whose doctors recommended weight gains consistent with IOM guidelines were more likely to have a concordant goal (vs. no goal) (OR = 5.3, 95%CI: 1.5, 18.6). Engaging in healthy behaviors and having health providers offer IOM weight gain recommendations may increase the likelihood of having a concordant gestational weight gain goal, which, in turn, is predictive of actual weight gains that fall within IOM guidelines

A pilot randomized controlled trial to promote healthful fish consumption during pregnancy: The Food for Thought Study

Background: Nutritionists advise pregnant women to eat fish to obtain adequate docosahexaenoic acid (DHA), an essential nutrient important for optimal brain development. However, concern exists that this advice will lead to excess intake of methylmercury, a developmental neurotoxicant. Objective: Conduct a pilot intervention to increase consumption of high-DHA, low-mercury fish in pregnancy. Methods: In April-October 2010 we recruited 61 women in the greater Boston, MA area at 12–22 weeks gestation who consumed = 200mg/d of DHA from fish, compared with 33% in the Advice arm (p=0.005) and 53% in the Advice+GC arm (p=0.0002). We did not detect any differences in mercury intake or in biomarker levels of mercury and DHA between groups. Conclusions: An educational intervention increased consumption of fish and DHA but not mercury. Future studies are needed to determine intervention effects on pregnancy and childhood health outcomes. Trial registration Registered on clinicaltrials.gov as NCT0112676

Ongoing monitoring of data clustering in multicenter studies

Background: Multicenter study designs have several advantages, but the possibility of non-random measurement error resulting from procedural differences between the centers is a special concern. While it is possible to address and correct for some measurement error through statistical analysis, proactive data monitoring is essential to ensure high-quality data collection. Methods: In this article, we describe quality assurance efforts aimed at reducing the effect of measurement error in a recent follow-up of a large cluster-randomized controlled trial through periodic evaluation of intraclass correlation coefficients (ICCs) for continuous measurements. An ICC of 0 indicates the variance in the data is not due to variation between the centers, and thus the data are not clustered by center. Results: Through our review of early data downloads, we identified several outcomes (including sitting height, waist circumference, and systolic blood pressure) with higher than expected ICC values. Further investigation revealed variations in the procedures used by pediatricians to measure these outcomes. We addressed these procedural inconsistencies through written clarification of the protocol and refresher training workshops with the pediatricians. Further data monitoring at subsequent downloads showed that these efforts had a beneficial effect on data quality (sitting height ICC decreased from 0.92 to 0.03, waist circumference from 0.10 to 0.07, and systolic blood pressure from 0.16 to 0.12). Conclusions: We describe a simple but formal mechanism for identifying ongoing problems during data collection. The calculation of the ICC can easily be programmed and the mechanism has wide applicability, not just to cluster randomized controlled trials but to any study with multiple centers or with multiple observers

The Human Phenotype Ontology in 2024: phenotypes around the world.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p&lt;0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p&lt;0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p&lt;0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP &gt;5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

Effects of an intervention to promote breastfeeding on maternal adiposity and blood pressure at 11.5 y postpartum:results from the Promotion of Breastfeeding Intervention Trial, a cluster-randomized controlled trial

BACKGROUND: Differences between mothers who do and do not succeed in breastfeeding are likely to confound associations of lactation with later maternal adiposity. OBJECTIVE: We compared adiposity and blood pressure (BP) in women randomly assigned to an intervention to promote prolonged and exclusive breastfeeding or usual care. DESIGN: We performed a cluster-randomized trial at 31 hospitals in Belarus in 1996-1997. RESULTS: Of 17,046 women enrolled at delivery, we assessed 11,867 women (69.6%) at 11.5 y postpartum. The prevalence of exclusive breastfeeding ≥3 mo was 44.5% in 6321 women in the intervention group and 7.1% in 5546 women in the control group. At 11.5 y postpartum, mean (±SD) body mass index (BMI; in kg/m(2)) was 26.5 ± 5.5, the percentage of body fat was 33.6% ± 8.3%, and systolic BP was 124.6 ± 14.6 mm Hg. On intention-to-treat analysis (without imputation) with adjustment for clustering by hospital, mean outcomes were lower in intervention compared with control mothers for BMI (mean difference: -0.27; 95% CI: -0.91, 0.37), body fat (-0.49%; 95% CI: -1.25%, 0.27%), and systolic BP (-0.81 mm Hg; 95% CI: -3.33, 1.71 mm Hg), but effect sizes were small, CIs were wide, and results were attenuated further toward the null after adjustment for baseline characteristics. Results were similar in sensitivity analyses [ie, by using conventional observational analyses disregarding treatment assignment, instrumental variable analyses to estimate the causal effect of breastfeeding, and multiple imputation to account for missing outcome measures (n = 17,046)]. CONCLUSION: In women who initiated breastfeeding, an intervention to promote longer breastfeeding duration did not result in an important lowering of adiposity or BP. This trial was registered at clinicaltrials.gov as NCT01561612 and at Current Controlled Trials as ISRCTN37687716

Ongoing monitoring of data clustering in multicenter studies

Abstract Background Multicenter study designs have several advantages, but the possibility of non-random measurement error resulting from procedural differences between the centers is a special concern. While it is possible to address and correct for some measurement error through statistical analysis, proactive data monitoring is essential to ensure high-quality data collection. Methods In this article, we describe quality assurance efforts aimed at reducing the effect of measurement error in a recent follow-up of a large cluster-randomized controlled trial through periodic evaluation of intraclass correlation coefficients (ICCs) for continuous measurements. An ICC of 0 indicates the variance in the data is not due to variation between the centers, and thus the data are not clustered by center. Results Through our review of early data downloads, we identified several outcomes (including sitting height, waist circumference, and systolic blood pressure) with higher than expected ICC values. Further investigation revealed variations in the procedures used by pediatricians to measure these outcomes. We addressed these procedural inconsistencies through written clarification of the protocol and refresher training workshops with the pediatricians. Further data monitoring at subsequent downloads showed that these efforts had a beneficial effect on data quality (sitting height ICC decreased from 0.92 to 0.03, waist circumference from 0.10 to 0.07, and systolic blood pressure from 0.16 to 0.12). Conclusions We describe a simple but formal mechanism for identifying ongoing problems during data collection. The calculation of the ICC can easily be programmed and the mechanism has wide applicability, not just to cluster randomized controlled trials but to any study with multiple centers or with multiple observers.</p