Recent findings from developmental neuroimaging studies suggest that the enhancement of cognitive processes during development may be the result of a fine-tuning of the structural and functional ...organization of brain with maturation. However, the details regarding the developmental trajectory of large-scale structural brain networks are not yet understood. Here, we used graph theory to examine developmental changes in the organization of structural brain networks in 203 normally growing children and adolescents. Structural brain networks were constructed using interregional correlations in cortical thickness for 4 age groups (early childhood: 4.8-8.4 year; late childhood: 8.5-11.3 year; early adolescence: 11.4-14.7 year; late adolescence: 14.8-18.3 year). Late childhood showed prominent changes in topological properties, specifically a significant reduction in local efficiency, modularity, and increased global efficiency, suggesting a shift of topological organization toward a more random configuration. An increase in number and span of distribution of connector hubs was found in this age group. Finally, inter-regional connectivity analysis and graph-theoretic measures indicated early maturation of primary sensorimotor regions and protracted development of higher order association and paralimbic regions. Our finding reveals a time window of plasticity occurring during late childhood which may accommodate crucial changes during puberty and the new developmental tasks that an adolescent faces.
Using a population-based sampling strategy, the National Institutes of Health (NIH) Magnetic Resonance Imaging Study of Normal Brain Development compiled a longitudinal normative reference database ...of neuroimaging and correlated clinical/behavioral data from a demographically representative sample of healthy children and adolescents aged newborn through early adulthood. The present paper reports brain volume data for 325 children, ages 4.5-18 years, from the first cross-sectional time point. Measures included volumes of whole-brain gray matter (GM) and white matter (WM), left and right lateral ventricles, frontal, temporal, parietal and occipital lobe GM and WM, subcortical GM (thalamus, caudate, putamen, and globus pallidus), cerebellum, and brainstem. Associations with cross-sectional age, sex, family income, parental education, and body mass index (BMI) were evaluated. Key observations are: 1) age-related decreases in lobar GM most prominent in parietal and occipital cortex; 2) age-related increases in lobar WM, greatest in occipital, followed by the temporal lobe; 3) age-related trajectories predominantly curvilinear in females, but linear in males; and 4) small systematic associations of brain tissue volumes with BMI but not with IQ, family income, or parental education. These findings constitute a normative reference on regional brain volumes in children and adolescents.
An estimated 40% of pregnancies globally are unintended. Measurement of pregnancy intention in low- and middle-income countries relies heavily on surveys, notably Demographic and Health Surveys ...(DHS), yet few studies have evaluated survey questions. We examined questions for measuring pregnancy intention, which are already in the DHS, and additional questions and investigated associations with maternity care utilisation and adverse pregnancy outcomes.
The EN-INDEPTH study surveyed 69,176 women of reproductive age in five Health and Demographic Surveillance System sites in Ghana, Guinea-Bissau, Ethiopia, Uganda and Bangladesh (2017-2018). We investigated responses to survey questions regarding pregnancy intention in two ways: (i) pregnancy-specific intention and (ii) desired-versus-actual family size. We assessed data completeness for each and level of agreement between the two questions, and with future fertility desire. We analysed associations between pregnancy intention and number and timing of antenatal care visits, place of delivery, and stillbirth, neonatal death and low birthweight.
Missing data were <2% in all questions. Responses to pregnancy-specific questions were more consistent with future fertility desire than desired-versus-actual family size responses. Using the pregnancy-specific questions, 7.4% of women who reported their last pregnancy as unwanted reported wanting more children in the future, compared with 45.1% of women in the corresponding desired family size category. Women reporting unintended pregnancies were less likely to attend 4+ antenatal care visits (aOR 0.73, 95% CI 0.64-0.83), have their first visit during the first trimester (aOR 0.71, 95% CI 0.63-0.79), and report stillbirths (aOR 0.57, 95% CI 0.44-0.73) or neonatal deaths (aOR 0.79, 95% CI 0.64-0.96), compared with women reporting intended pregnancies. We found no associations for desired-versus-actual family size intention.
We found the pregnancy-specific intention questions to be a much more reliable assessment of pregnancy intention than the desired-versus-actual family size questions, despite a reluctance to report pregnancies as unwanted rather than mistimed. The additional questions were useful and may complement current DHS questions, although these are not the only possibilities. As women with unintended pregnancies were more likely to miss timely and frequent antenatal care, implementation research is required to improve coverage and quality of care for those women.
Preterm birth (gestational age (GA) <37 weeks) is the leading cause of child mortality worldwide. However, GA is rarely assessed in population-based surveys, the major data source in ...low/middle-income countries. We examined the performance of new questions to measure GA in household surveys, a subset of which had linked early pregnancy ultrasound GA data.
The EN-INDEPTH population-based survey of 69,176 women was undertaken (2017-2018) in five Health and Demographic Surveillance System sites in Bangladesh, Ethiopia, Ghana, Guinea-Bissau and Uganda. We included questions regarding GA in months (GAm) for all women and GA in weeks (GAw) for a subset; we also asked if the baby was 'born before expected' to estimate preterm birth rates. Survey data were linked to surveillance data in two sites, and to ultrasound pregnancy dating at <24 weeks in one site. We assessed completeness and quality of reported GA. We examined the validity of estimated preterm birth rates by sensitivity and specificity, over/under-reporting of GAw in survey compared to ultrasound by multinomial logistic regression, and explored perceptions about GA and barriers and enablers to its reporting using focus group discussions (n = 29).
GAm questions were almost universally answered, but heaping on 9 months resulted in underestimation of preterm birth rates. Preference for reporting GAw in even numbers was evident, resulting in heaping at 36 weeks; hence, over-estimating preterm birth rates, except in Matlab where the peak was at 38 weeks. Questions regarding 'born before expected' were answered but gave implausibly low preterm birth rates in most sites. Applying ultrasound as the gold standard in Matlab site, sensitivity of survey-GAw for detecting preterm birth (GAw <37) was 60% and specificity was 93%. Focus group findings suggest that women perceive GA to be important, but usually counted in months. Antenatal care attendance, women's education and health cards may improve reporting.
This is the first published study assessing GA reporting in surveys, compared with the gold standard of ultrasound. Reporting GAw within 5 years' recall is feasible with high completeness, but accuracy is affected by heaping. Compared to ultrasound-GAw, results are reasonably specific, but sensitivity needs to be improved. We propose revised questions based on the study findings for further testing and validation in settings where pregnancy ultrasound data and/or last menstrual period dates/GA recorded in pregnancy are available. Specific training of interviewers is recommended.
Low muscle mass is associated with numerous adverse outcomes independent of other associated comorbid diseases. We aimed to predict and understand an individual’s risk for developing low muscle mass ...using proteomics and machine learning. We identified eight biomarkers associated with low pectoralis muscle area (PMA). We built three random forest classification models that used either clinical measures, feature selected biomarkers, or both to predict development of low PMA. The area under the receiver operating characteristic curve for each model was: clinical-only = 0.646, biomarker-only = 0.740, and combined = 0.744. We displayed the heterogenetic nature of an individual’s risk for developing low PMA and identified two distinct subtypes of participants who developed low PMA. While additional validation is required, our methods for identifying and understanding individual and group risk for low muscle mass could be used to enable developments in the personalized prevention of low muscle mass.
Central venous catheters in the NICU are associated with significant morbidity and mortality because of the risk of central line-associated bloodstream infections (CLABSIs). The purpose of this study ...was to determine the effect of catheter dwell time on risk of CLABSI.
Retrospective cohort study of 13,327 infants with 15,567 catheters (93% peripherally inserted central catheters PICCs, 7% tunneled catheters) and 256,088 catheter days cared for in 141 NICUs. CLABSI was defined using National Health Surveillance Network criteria. We defined dwell time as the number of days from line insertion until either line removal or day of CLABSI. We generated survival curves for each week of dwell time and estimated hazard ratios for CLABSI at each week by using a Cox proportional hazards frailty model. We controlled for postmenstrual age and year, included facility as a random effect, and generated separate models by line type.
Median postmenstrual age was 29 weeks (interquartile range 26-33). The overall incidence of CLABSI was 0.93 per 1000 catheter days. Increased dwell time was not associated with increased risk of CLABSI for PICCs. For tunneled catheters, infection incidence was significantly higher in weeks 7 and 9 compared with week 1.
Clinicians should not routinely replace uninfected PICCs for fear of infection but should consider removing tunneled catheters before week 7 if no longer needed. Additional studies are needed to determine what daily maintenance practices may be associated with decreased risk of infection, especially for tunneled catheters.
OBJECTIVE:To investigate the association between periventricular white mater hyperintensities (PVWMH) and biomarkers of elevated cerebral β-amyloid (Aβ) in the Alzheimerʼs Disease Neuroimaging ...Initiative, a large prospective multicenter observational study.
METHODS:The burden of frontal, parietal, and occipital PVWMH on 3T fluid-attenuated inversion recovery MRI was evaluated in 698 cognitively normal participants and participants with mild cognitive impairment (MCI) using a novel semiquantitative visual rating scale. Results were correlated with CSF-Aβ, florbetapir-PET, and fluorodeoxyglucose (FDG)–PET.
RESULTS:Increased burden of parietal, occipital, and frontal PVWMH was associated with elevated cerebral amyloid evidenced by high florbetapir-PET signal (p < 0.01) and low CSF-Aβ (p < 0.01). In logistic regression models, including PVWMH, age, sex, APOE status, vascular risk factors, pulse pressure, vascular secondary prevention medications, education, ethnicity, and race, parietal, occipital, and frontal PVWMH burden was independently associated with high florbetapir-PET uptake (p < 0.05). In a similar logistic regression model, parietal and occipital (p < 0.05) but not frontal (p = 0.05) PVWMH were independently associated with CSF-Aβ. Weaker associations were found between parieto-occipital PVWMH and elevated CSF-tau (p < 0.05) and occipital PVWMH and elevated CSF-phospho-tau (p < 0.05). PVWMH were associated with cerebral hypometabolism on FDG-PET independent of CSF-Aβ levels (p < 0.05). Absolute and consistency of agreement intraclass correlation coefficients were, respectively, 0.83 and 0.83 for frontal, 0.78 and 0.8 for parietal, and 0.45 and 0.75 for occipital PVWMH measurements.
CONCLUSIONS:Increased PVWMH were associated with elevated cerebral amyloid independent of potential confounders such as age, APOE genotype, and vascular risk factors. The mechanisms underlying the association between PVWMH and cerebral amyloid remain to be clarified.
Several studies using magnetic resonance imaging (MRI) scans have shown developmental trajectories of cortical thickness. Cognitive milestones happen concurrently with these structural changes, and a ...delay in such changes has been implicated in developmental disorders such as attention-deficit/hyperactivity disorder (ADHD). Accurate estimation of individuals' brain maturity, therefore, is critical in establishing a baseline for normal brain development against which neurodevelopmental disorders can be assessed. In this study, cortical thickness derived from structural magnetic resonance imaging (MRI) scans of a large longitudinal dataset of normally growing children and adolescents (n=308), were used to build a highly accurate predictive model for estimating chronological age (cross-validated correlation up to R=0.84). Unlike previous studies which used kernelized approach in building prediction models, we used an elastic net penalized linear regression model capable of producing a spatially sparse, yet accurate predictive model of chronological age. Upon investigating different scales of cortical parcellation from 78 to 10,240 brain parcels, we observed that the accuracy in estimated age improved with increased spatial scale of brain parcellation, with the best estimations obtained for spatial resolutions consisting of 2560 and 10,240 brain parcels. The top predictors of brain maturity were found in highly localized sensorimotor and association areas. The results of our study demonstrate that cortical thickness can be used to estimate individuals' brain maturity with high accuracy, and the estimated ages relate to functional and behavioural measures, underscoring the relevance and scope of the study in the understanding of biological maturity.
•An elastic net penalized linear regression model was used for estimating age.•Top predictors of brain maturity were found in sensorimotor and association areas.•Estimated ages were observed to be related to functional and behavioural measures.
OBJECTIVE:To investigate the vascular contribution to longitudinal changes in Alzheimer disease (AD) biomarkers.
METHODS:The Alzheimerʼs Disease Neuroimaging Initiative is a clinic based, ...longitudinal study with CSF, PET, and MRI biomarkers repeatedly measured in participants with normal cognition (NC), mild cognitive impairment (MCI), and mild AD. Participants with severe cerebrovascular risks were excluded. Cardiovascular risk scores and MRI white matter hyperintensities (WMHs) were treated as surrogate markers for vascular burden. Generalized estimating equations were applied, and both vascular burden and its interaction with time (vascular burden × time) or time-varying WMHs were entered into regression models to assess whether biomarker rates of change were modified by vascular burden.
RESULTS:Cardiovascular risk profiles were not predictive of progression in CSF β42-amyloid, Ffluorodeoxyglucose (FDG) PET uptake, and MRI hippocampal atrophy. Greater baseline cardiovascular risks or WMHs were generally associated with cognitive impairment, particularly poor executive function. WMHs increased over time with a faster rate in MCI and AD than in NC. Increased time-varying WMH was associated with faster decline in executive function and lower FDG uptake in NC. Otherwise, WMH was not associated with CSF and MRI biomarkers in the 3 groups. These findings remained unchanged after accounting for APOE4.
CONCLUSION:Increased WMHs are associated with aging, decreased glucose metabolism, and decline in executive function but do not affect AD-specific pathologic progression, suggesting that the vascular contribution to dementia is probably additive although not necessarily independent of the amyloid pathway.
GLOSSARYAββ-amyloidADAlzheimer diseaseADNIAlzheimerʼs Disease Neuroimaging InitiativeASAD-cogAlzheimerʼs Disease Assessment Scale–Cognitive SubscaleFDG18FfluorodeoxyglucoseGEEgeneralized estimating equationMCImild cognitive impairmentMMSEMini-Mental State ExaminationNCnormal cognitionWMHwhite matter hyperintensity
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