Background: Dexamethasone was the first intervention proven to reduce mortality in patients with COVID-19 being treated in hospital. We aimed to evaluate the adoption of corticosteroids in the treatment of COVID-19 in the UK after the RECOVERY trial publication on June 16, 2020, and to identify discrepancies in care. Methods: We did an audit of clinical implementation of corticosteroids in a prospective, observational, cohort study in 237 UK acute care hospitals between March 16, 2020, and April 14, 2021, restricted to patients aged 18 years or older with proven or high likelihood of COVID-19, who received supplementary oxygen. The primary outcome was administration of dexamethasone, prednisolone, hydrocortisone, or methylprednisolone. This study is registered with ISRCTN, ISRCTN66726260. Findings: Between June 17, 2020, and April 14, 2021, 47 795 (75\u00b72%) of 63 525 of patients on supplementary oxygen received corticosteroids, higher among patients requiring critical care than in those who received ward care (11 185 [86\u00b76%] of 12 909 vs 36 415 [72\u00b74%] of 50 278). Patients 50 years or older were significantly less likely to receive corticosteroids than those younger than 50 years (adjusted odds ratio 0\u00b779 [95% CI 0\u00b770\u20130\u00b789], p=0\u00b70001, for 70\u201379 years; 0\u00b752 [0\u00b746\u20130\u00b758], p<0\u00b70001, for >80 years), independent of patient demographics and illness severity. 84 (54\u00b72%) of 155 pregnant women received corticosteroids. Rates of corticosteroid administration increased from 27\u00b75% in the week before June 16, 2020, to 75\u201380% in January, 2021. Interpretation: Implementation of corticosteroids into clinical practice in the UK for patients with COVID-19 has been successful, but not universal. Patients older than 70 years, independent of illness severity, chronic neurological disease, and dementia, were less likely to receive corticosteroids than those who were younger, as were pregnant women. This could reflect appropriate clinical decision making, but the possibility of inequitable access to life-saving care should be considered. Funding: UK National Institute for Health Research and UK Medical Research Council.
\n \n\n \n \nThe genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3-7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.
\n \n\n \n \nBackgroundHuman-milk oligosaccharides (HMOs) are an abundant component of human milk that have health-related effects on breastfeeding infants. Since variation in HMO composition can be explained by maternal and environmental factors, understanding the diversity in HMOs across settings and identifying context-specific factors associated with HMO abundances is important.ObjectivesThe aim was to describe the HMO profile of Bangladeshi women and to estimate the effect of maternal vitamin D supplementation on HMO composition.MethodsIn a cross-sectional analysis of data and samples from the Maternal Vitamin D for Infant Growth trial in Dhaka, Bangladesh (clinicaltrials.gov; NCT01924013), 192 participants were randomly selected including 96 from each of the placebo and highest-dose vitamin D supplementation groups. In mid-feed breast milk samples collected at a mean (\u00b1SD) postpartum age of 93\u00a0\u00b1\u00a07 d, absolute and relative abundances of 19 HMOs were analyzed by HPLC. \"Secretors\" were defined as participants with 2'fucosyllactose concentrations >350 nmol/mL. Associations between HMO concentrations and selected maternal or environmental factors were estimated by multivariable linear regression, adjusting for vitamin D group allocation and secretor status. HMO profiles of Bangladeshi women were compared with data from other international cohorts.ResultsOverall, 34% (65/192) of participants were nonsecretors. Secretor status was associated with the concentrations of total HMOs and 79% (15/19) of individual HMOs. Vitamin D supplementation did not affect the total or individual concentration of any measured HMO. 3-Fucosyllactose concentration was significantly higher in breast milk samples collected in December to February compared with samples collected in March to May. HMO composition was similar to other previously reported cohorts.ConclusionsThe HMO profile of Bangladeshi women is predominantly determined by secretor status. Context-specific HMO data may improve understanding of the effects of HMOs on the infant microbiome and health and guide the development of HMO-containing interventions.
\n \n\n \n \nBackgroundPreterm birth (<37 weeks), low birth weight (LBW,<2500g), and small for gestational age (SGA,<10th centile of birth weight for gestational age and sex) are markers of newborn vulnerability with a high risk of mortality. We estimated the prevalence of phenotypes combining these three markers and quantified the mortality risk associated with them.MethodsPopulation-based cohort study using routine register-based linked data on all births and deaths in Brazil from January 1, 2011, to December 31, 2018. We estimated the prevalence of preterm, LBW, and SGA individually and for phenotypes combining these characteristics. The mortality risk associated with each phenotype: early neonatal, late neonatal, neonatal, post-neonatal, infant, 1-4 years, and under five years was quantified using mortality rates and hazard ratios (HRs) with 95% confidence interval (CI) were estimated using Cox proportional hazard models.Findings17,646,115 live births were included. Prevalence of preterm birth, LBW and SGA were 9.4%, 9.6% and 9.2%, respectively. Neonatal mortality risk was 16-fold (HR=15.9; 95% CI:15.7-16.1) higher for preterm compared to term, 3 times higher (HR=3.4; (95% CI:3.3-3.4) for SGA compared to adequate for gestational age (AGA), and >25 times higher for LBW (HR=25.8; (95% CI:25.5-26.1) compared to normal birth weight (NBW). 18% of all live births were included in one of the small vulnerable newborn phenotypes. Of those 8.2% were term-SGA (4.7%NBW, 3.5%LBW), 0.6% were term-AGA-LBW, 8.3% preterm-AGA (3.8%NBW, 4.5%LBW) and 1.0% preterm-SGA-LBW. Compared to term-AGA-NBW, the highest mortality risk was for preterm-LBW phenotypes (HR=36.2(95%CI 35.6-36.8) preterm-AGA-LBW, HR=62.0(95%CI 60.8-63.2) preterm-SGA-LBW). The increased mortality risk associated with vulnerable newborn phenotypes was highest in the first month of life, with attenuated but continued high risk in the post-neonatal period and 1-4 years of age.InterpretationOur findings support the value of using more detailed phenotypes to identify those at highest risk. More granular data can inform care at the individual level, advance research, especially for prevention, and accelerate progress towards global targets such as the Sustainable Development Goals.FundingWellcome Trust.
\n \n\n \n \nUltrasound growth measurements are monitored to evaluate if a fetus is growing normally compared with a defined standard chart at a specified gestational age. Using data from the Fetal Growth Longitudinal Study of the INTERGROWTH-21st project, we have modelled the longitudinal dependence of fetal head circumference, biparietal diameter, occipito-frontal diameter, abdominal circumference, and femur length using a two-stage approach. The first stage involved finding a suitable transformation of the raw fetal measurements (as the marginal distributions of ultrasound measurements were non-normal) to standardized deviations (Z-scores). In the second stage, a correlation model for a Gaussian process is fitted, yielding a correlation for any pair of observations made between 14 and 40\u2009weeks. The correlation structure of the fetal Z-score can be used to assess whether the growth, for example, between successive measurements is satisfactory. The paper is accompanied by a Shiny application, see https://lxiao5.shinyapps.io/shinycalculator/.
\n \n\n \n \nBackgroundMost studies on children evaluate longitudinal growth as an important health indicator. Different methods have been used to detect growth patterns across childhood, but with no comparison between them to evaluate result consistency. We explored the variation in growth patterns as detected by different clustering and latent class modelling techniques. Moreover, we investigated how the characteristics/features (e.g. slope, tempo, velocity) of longitudinal growth influence pattern detection.MethodsWe studied 1134 children from The Applied Research Group for Kids cohort with longitudinal-growth measurements [height, weight, body mass index (BMI)] available from birth until 12\u2009years of age. Growth patterns were identified by latent class mixed models (LCMM) and time-series clustering (TSC) using various algorithms and distance measures. Time-invariant features were extracted from all growth measures. A random forest classifier was used to predict the identified growth patterns for each growth measure using the extracted features.ResultsOverall, 72 TSC configurations were tested. For BMI, we identified three growth patterns by both TSC and LCMM. The clustering agreement was 58% between LCMM and TS clusters, whereas it varied between 30.8% and 93.3% within the TSC configurations. The extracted features (n\u2009=\u200967) predicted the identified patterns for each growth measure with accuracy of 82%-89%. Specific feature categories were identified as the most important predictors for patterns of all tested growth measures.ConclusionGrowth-pattern detection is affected by the method employed. This can impact on comparisons across different populations or associations between growth patterns and health outcomes. Growth features can be reliably used as predictors of growth patterns.
\n \n\n \n \nChildren's growth status is an important measure commonly used as a proxy indicator of advancements in a country's health, human capital and economic development. We aimed to assess the feasibility of using Super-Imposition by Translation And Rotation (SITAR) models for summarising population-based cross-sectional height-by-age data of children under 5 years across 64 countries. Using 145 publicly available Demographic and Health Surveys of children under 5 years across 64 low-income and middle-income countries from 2000 to 2018, we created a multicountry pseudo-longitudinal dataset of children's heights. SITAR models including two parameters (size and intensity) explained 81% of the between-survey variation in mean boys' height and 80% in mean girls' height. Size parameters for boys and girls (relative to the WHO child growth standards) were distributed non-normally around a mean of -5.2\u2009cm for boys (range: -7.9 cm to -1.6 cm) and -4.9\u2009cm for girls (range: -7.7 cm to -1.2 cm). Boys exhibited 10% slower linear growth compared with the WHO (range: 19.7% slower to 1.6% faster) and girls 11% slower linear growth compared with the WHO (range: 21.4% slower to 1.0% faster). Variation in the SITAR size parameter was \u226590% explained by the combination of average length within the first 60 days of birth (as a proxy for fetal growth) and intensity, regardless of sex, with much greater contribution by postnatal intensity (r\u22650.89 between size and intensity). SITAR models with two random effects can be used to model child linear growth using multicountry pseudo-longitudinal data, and thereby provide a feasible alternative approach to summarising early childhood height trajectories based on survey data. The SITAR intensity parameter may be a novel indicator for specifically tracking progress in the determinants of postnatal growth in low-income and middle-income countries.
\n \n\n \n \nBackground: Small for gestational age (SGA) is a key contributor to premature deaths and long-term complications in life. Improved characterization of maternal risk factors associated with this adverse outcome is needed to inform the development of interventions, track progress, and reduce the disease burden. This study aimed to identify socioeconomic, demographic, and clinical factors associated with SGA in Mexico. Methods: We analyzed administrative data from 1,841,477 singletons collected by the National Information Subsystem of Livebirths during 2017. Small-for-gestational-age was defined as being <10th centiles according to the INTERGROWTH-21st standards. The comparison group was defined as being in \u226510th centiles. We fitted logistic regression models to determine odds ratios for the maternal factors associated with SGA. Results: Among the 1,841,477 singletons, 51% were male, 6.7% were SGA, 6.1% were term-SGA, and 0.5% were preterm-SGA. Maternal education presented a protective gradient of being SGA among mothers who achieved 1 to 6 years of education (adjusted odds ratio (aOR)0.95; 95% CI:0.91,0.99), 7 to 9 years (aOR 0.86; 95% CI:0.83,0.89), 10 to 12 years (aOR 0.75; 95% CI: 0.72, 0.79) and > 12 years (aOR 0.63; 95% CI:0.6,0.66) compared with those without education. SGA was particularly likely to occur among primiparous (aOR 1.42; 95% CI: 1.39, 1.43), mothers living in very high deprivation localities (aOR 1.39; 95% CI: 1.36, 1.43), young (aOR 1.04; 95% CI: 1.02, 1.06), advanced age (aOR 1.14; 95% CI 1.09, 1.19), and mothers living in areas above 2,000 m (aOR 1.69; 95% CI: 1.65, 1.73). Antenatal care was associated with a reduced risk of SGA by 30% (aOR 0.7; 95% CI:0.67,0.73), 23% (OR 0.77; 95% CI:0.74,0.8), and 21% (OR 0.79; 95% CI:0.75,0.83), compared with those mothers who never received antenatal care, when women visited the clinic at the first, second and third trimester, respectively. Conclusion: Almost 7% of live births were found to be SGA. Parity, maternal age, education, place of residence, and social deprivation were significantly associated with this outcome. Antenatal care was protective. These findings imply that interventions focusing on early and adequate contact with health care facilities, reproductive health counseling, and maternal education should reduce SGA in Mexico.
\n \n\n \n \nChildren with severe acute malnutrition (SAM) remain vulnerable after treatment at nutritional rehabilitation units (NRUs). The objective was to assess the concurrent pathways in a hypothesized model between caregiver body mass index (BMI), the home environment, and child nutritional status, and development (gross motor, fine motor, language, and social domains) in children with SAM following discharge from inpatient treatment. Structural equation modelling (SEM) was performed with data from a cluster-randomized controlled trial at the Moyo Nutritional Rehabilitation and Research Unit in Blantyre, Malawi. This approach was undertaken to explore simultaneous relationships between caregiver BMI, the home environment (Home Observation for Measurement of the Environment Inventory scores), child nutritional status (anthropometric indicators including weight-for-age z-scores [WAZ]), and child development (Malawi Developmental Assessment Tool (MDAT) z-scores as a latent variable) in children with SAM. These data were collected at participants' homes six months after discharge from NRU treatment. This analysis included 85 children aged 6-59 months with SAM and their caregivers recruited to the trial at the NRU and followed up successfully six months after discharge. The model with WAZ as the nutritional indicator fit the data according to model fit indices (\u03c72 = 28.92, p = 0.42). Caregiver BMI was predictive of better home environment scores (\u03b2 = 0.23, p = 0.03) and child WAZ (\u03b2 = 0.30, p = 0.005). The home environment scores were positively correlated with MDAT z-scores (\u03b2 = 0.32, p = 0.001). Child nutritional status based on WAZ was also correlated with MDAT z-scores (\u03b2 = 0.37, p<0.001). This study demonstrates that caregiver BMI could ultimately relate to child development in children with SAM, through its links to the home environment and child nutritional status.
\n \n\n \n \nBackgroundPreterm birth is a leading cause of death among children under five years. Previous estimates indicated global preterm birth rate of 10.6% (14.8 million neonates) in 2014. We aim to update preterm birth estimates at global, regional, and national levels for the period 2010 to 2019.MethodsPreterm birth is defined as a live birth occurring before 37 completed gestational weeks, or <259 days since a woman's last menstrual period. National administrative data sources for WHO Member States with facility birth rates of \u226580% in the most recent year for which data is available will be searched. Administrative data identified for these countries will be considered if \u226580% of UN estimated live births include gestational age information to define preterm birth. For countries without eligible administrative data, a systematic review of studies will be conducted. Research studies will be eligible if the reported outcome is derived from an observational or intervention study conducted at national or sub-national level in population- or facility-based settings. Risk of bias assessments will focus on gestational age measurement method and coverage, and inclusion of special subgroups in published estimates. Covariates for inclusion will be selected a priori based on a conceptual framework of plausible associations with preterm birth, data availability, and quality of covariate data across many countries and years. Global, regional and national preterm birth rates will be estimated using a Bayesian multilevel-mixed regression model.DiscussionAccurate measurement of preterm birth is challenging in many countries given incomplete or unavailable data from national administrative sources, compounded by limited gestational age assessment during pregnancy to define preterm birth. Up-to-date modelled estimates will be an important resource to measure the global burden of preterm birth and to inform policies and programs especially in settings with a high burden of neonatal mortality.Trial registrationPROSPERO registration: CRD42021237861.
\n \n\n \n \n\nBackground\nGestational hypertensive and acute hypotensive disorders are associated with maternal morbidity and mortality worldwide. However, physiological blood pressure changes in pregnancy are insufficiently defined. We describe blood pressure changes across healthy pregnancies from the International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st) Fetal Growth Longitudinal Study (FGLS) to produce international, gestational age-specific, smoothed centiles (third, 10th, 50th, 90th, and 97th) for blood pressure.\n\n\nMethods and findings\nSecondary analysis of a prospective, longitudinal, observational cohort study (2009 to 2016) was conducted across 8 diverse urban areas in Brazil, China, India, Italy, Kenya, Oman, the United Kingdom, and the United States of America. We enrolled healthy women at low risk of pregnancy complications. We measured blood pressure using standardised methodology and validated equipment at enrolment at <14 weeks, then every 5 \u00b1 1 weeks until delivery.\nWe enrolled 4,607 (35%) women of 13,108 screened. The mean maternal age was 28\u00b74 (standard deviation [SD] 3.9) years; 97% (4,204/4,321) of women were married or living with a partner, and 68% (2,955/4,321) were nulliparous. Their mean body mass index (BMI) was 23.3 (SD 3.0) kg/m2. Systolic blood pressure was lowest at 12 weeks: Median was 111.5 (95% CI 111.3 to 111.8) mmHg, rising to a median maximum of 119.6 (95% CI 118.9 to 120.3) mmHg at 40 weeks\u2019 gestation, a difference of 8.1 (95% CI 7.4 to 8.8) mmHg. Median diastolic blood pressure decreased from 12 weeks: 69.1 (95% CI 68.9 to 69.3) mmHg to a minimum of 68.5 (95% CI 68.3 to 68.7) mmHg at 19+5 weeks\u2019 gestation, a change of \u22120\u00b76 (95% CI \u22120.8 to \u22120.4) mmHg. Diastolic blood pressure subsequently increased to a maximum of 76.3 (95% CI 75.9 to 76.8) mmHg at 40 weeks\u2019 gestation. Systolic blood pressure fell by >14 mmHg or diastolic blood pressure by >11 mmHg in fewer than 10% of women at any gestational age. Fewer than 10% of women increased their systolic blood pressure by >24 mmHg or diastolic blood pressure by >18 mmHg at any gestational age. The study\u2019s main limitations were the unavailability of prepregnancy blood pressure values and inability to explore circadian effects because time of day was not recorded for the blood pressure measurements.\n\n\nConclusions\nOur findings provide international, gestational age-specific centiles and limits of acceptable change to facilitate earlier recognition of deteriorating health in pregnant women. These centiles challenge the idea of a clinically significant midpregnancy drop in blood pressure.\n
\n \n\n \n \nBackgroundThe INTERGROWTH-21st sex and gestational age (GA) specific newborn size standards (IG-NS) are intended to complement the World Health Organization Child Growth Standards (WHO-GS), which are not GA-specific. We examined the implications of using IG-NS at birth and WHO-GS at postnatal ages in longitudinal epidemiologic studies.ObjectivesThe aim of this study was to quantify the extent to which standardised measures of newborn size and growth are affected when using WHO-GS versus IG-NS at birth among term-born infants.MethodsData from two prenatal trials in Bangladesh (n\u00a0=\u00a0755) and The Gambia (n\u00a0=\u00a0522) were used to estimate and compare size at birth and growth from birth to 3\u00a0months when using WHO-GS only ('WHO-GS') versus IG-NS at birth and WHO-GS postnatally ('IG-NS'). Mean length-for-age (LAZ), weight-for-age (WAZ) and head circumference-for-age (HCAZ), and the prevalence of undernutrition (stunting: LAZ\u00a00/7 -386/7 ), full-term (390/7 -406/7 ) and late-term (410/7 -430/7 )]. We used Bland-Altman plots to compare continuous indices and Kappa statistic to compare categorical indicators.ResultsAt birth, mean LAZ, WAZ and HCAZ, and the prevalence of undernutrition were most similar among newborns between 39 and 40\u00a0weeks of GA when using WHO-GS versus IG-NS. However, anthropometric indices were systematically lower among early-term infants and higher among late-term infants when using WHO-GS versus IG-NS. Early-term and late-term infants demonstrated relatively faster and slower growth, respectively, when using WHO-GS versus IG-NS, with the direction and magnitude of differences varying between anthropometric indices. Individual-level differences in attained size and growth, when using WHO-GS versus IG-NS, were greater than 0.2 SD in magnitude for >60% of infants across all anthropometric indices.ConclusionsUsing IG-NS at birth with WHO-GS postnatally is acceptable for full-term infants but may give a misleading interpretation of growth trajectories among early- and late-term infants.
\n \n\n \n \nBackgroundInvasive pneumococcal disease is a major cause of infant morbidity and death worldwide. Vitamin D promotes anti-pneumococcal immune responses in vitro, but whether improvements in infant vitamin D status modify risks of nasal pneumococcal acquisition in early life is not known.MethodsThis is a secondary analysis of data collected in a trial cohort in Dhaka, Bangladesh. Acute respiratory infection (ARI) surveillance was conducted from 0 to 6\u00a0months of age among 1060 infants of women randomized to one of four pre/post-partum vitamin D dose combinations or placebo. Nasal swab samples were collected based on standardized ARI criteria, and pneumococcal DNA quantified by qPCR. Hazards ratios of pneumococcal acquisition and carriage dynamics were estimated using interval-censored survival and multi-state modelling.ResultsPneumococcal carriage was detected at least once in 90% of infants by 6\u00a0months of age; overall, 69% of swabs were positive (2616/3792). There were no differences between any vitamin D group and placebo in the hazards of pneumococcal acquisition, carriage dynamics, or carriage density (p\u2009>\u20090.05 for all comparisons).ConclusionDespite in vitro data suggesting that vitamin D promoted immune responses against pneumococcus, improvements in postnatal vitamin D status did not reduce the rate, alter age of onset, or change dynamics of nasal pneumococcal colonization in early infancy. Trial registration Registered in ClinicalTrials.gov with the registration number of NCT02388516 and first posted on March 17, 2015.
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