A new method to analyse the pace of child development: Cox regression validated by a bootstrap resampling procedure

<p>Abstract</p> <p>Background</p> <p>Various perinatal factors influencing neuromotor development are known from cross sectional studies. Factors influencing the age at which distinct abilities are acquired are uncertain. We hypothesized that the Cox regression model might identify these factors.</p> <p>Methods</p> <p>Neonates treated at Aachen University Hospital in 2000/2001 were identified retrospectively (n = 796). Outcome data, based on a structured interview, were available from 466 children, as were perinatal data. Factors possibly related to outcome were identified by bootstrap selection and then included into a multivariate Cox regression model. To evaluate if the parental assessment might change with the time elapsed since birth we studied five age cohorts of 163 normally developed children.</p> <p>Results</p> <p>Birth weight, gestational age, congenital cardiac disease and periventricular leukomalacia were related to outcome in the multivariate analysis (p < 0.05). Analysis of the control cohorts revealed that the parents' assessment of the ability of bladder control is modified by the time elapsed since birth.</p> <p>Conclusions</p> <p>Combined application of the bootstrap resampling procedure and multivariate Cox regression analysis effectively identifies perinatal factors influencing the age at which distinct abilities are acquired. These were similar as known from previous cross sectional studies. Retrospective data acquistion may lead to a bias because the parental memories change with time. This recommends applying this statistical approach in larger prospective trials.</p

Special Care and School Difficulties in 8-Year-Old Very Preterm Children: The Epipage Cohort Study

OBJECTIVES: To investigate school difficulties, special care and behavioral problems in 8 year-old very preterm (VPT) children. PATIENT AND METHODS: Longitudinal population-based cohort in nine regions of France of VPT children and a reference group born at 39-40 weeks of gestation (WG). The main outcome measures were information about school, special care and behavioral problems using Strengths and Difficulties Questionnaire from a questionnaire to parents. RESULTS: Among the 1439 VPT children, 5% (75/1439) were in a specialised school or class, 18% (259/1439) had repeated a grade in a mainstream class and 77% (1105/1439) were in the appropriate grade-level in mainstream class; these figures were 1% (3/327) , 5% (16/327) and 94% (308/327) , respectively, for the reference group. Also, 15% (221/1435) of VPT children in a mainstream class received support at school versus 5% (16/326) of reference group. More VPT children between the ages of five and eight years received special care (55% (794/1436)) than children born at term (38% (124/325)); more VPT children (21% (292/1387)) had behavioral difficulties than the reference group (11% (35/319)). School difficulties, support at school, special care and behavioral difficulties in VPT children without neuromotor or sensory deficits varied with gestational age, socioeconomic status, and cognitive score at the age of five. CONCLUSIONS: Most 8-year-old VPT children are in mainstream schools. However, they have a high risk of difficulty in school, with more than half requiring additional support at school and/or special care. Referral to special services has increased between the ages of 5 and 8 years, but remained insufficient for those with borderline cognitive scores

Acute kidney injury in children

Acute kidney injury (AKI) (previously called acute renal failure) is characterized by a reversible increase in the blood concentration of creatinine and nitrogenous waste products and by the inability of the kidney to regulate fluid and electrolyte homeostasis appropriately. The incidence of AKI in children appears to be increasing, and the etiology of AKI over the past decades has shifted from primary renal disease to multifactorial causes, particularly in hospitalized children. Genetic factors may predispose some children to AKI. Renal injury can be divided into pre-renal failure, intrinsic renal disease including vascular insults, and obstructive uropathies. The pathophysiology of hypoxia/ischemia-induced AKI is not well understood, but significant progress in elucidating the cellular, biochemical and molecular events has been made over the past several years. The history, physical examination, and laboratory studies, including urinalysis and radiographic studies, can establish the likely cause(s) of AKI. Many interventions such as ‘renal-dose dopamine’ and diuretic therapy have been shown not to alter the course of AKI. The prognosis of AKI is highly dependent on the underlying etiology of the AKI. Children who have suffered AKI from any cause are at risk for late development of kidney disease several years after the initial insult. Therapeutic interventions in AKI have been largely disappointing, likely due to the complex nature of the pathophysiology of AKI, the fact that the serum creatinine concentration is an insensitive measure of kidney function, and because of co-morbid factors in treated patients. Improved understanding of the pathophysiology of AKI, early biomarkers of AKI, and better classification of AKI are needed for the development of successful therapeutic strategies for the treatment of AKI

Memory in Microbes: Quantifying History-Dependent Behavior in a Bacterium

Memory is usually associated with higher organisms rather than bacteria. However, evidence is mounting that many regulatory networks within bacteria are capable of complex dynamics and multi-stable behaviors that have been linked to memory in other systems. Moreover, it is recognized that bacteria that have experienced different environmental histories may respond differently to current conditions. These “memory” effects may be more than incidental to the regulatory mechanisms controlling acclimation or to the status of the metabolic stores. Rather, they may be regulated by the cell and confer fitness to the organism in the evolutionary game it participates in. Here, we propose that history-dependent behavior is a potentially important manifestation of memory, worth classifying and quantifying. To this end, we develop an information-theory based conceptual framework for measuring both the persistence of memory in microbes and the amount of information about the past encoded in history-dependent dynamics. This method produces a phenomenological measure of cellular memory without regard to the specific cellular mechanisms encoding it. We then apply this framework to a strain of Bacillus subtilis engineered to report on commitment to sporulation and degradative enzyme (AprE) synthesis and estimate the capacity of these systems and growth dynamics to ‘remember’ 10 distinct cell histories prior to application of a common stressor. The analysis suggests that B. subtilis remembers, both in short and long term, aspects of its cell history, and that this memory is distributed differently among the observables. While this study does not examine the mechanistic bases for memory, it presents a framework for quantifying memory in cellular behaviors and is thus a starting point for studying new questions about cellular regulation and evolutionary strategy

Distinct cytokine patterns may regulate the severity of neonatal asphyxia

Abstract Background Neuroinflammation and a systemic inflammatory reaction are important features of perinatal asphyxia. Neuroinflammation may have dual aspects being a hindrance, but also a significant help in the recovery of the CNS. We aimed to assess intracellular cytokine levels of T-lymphocytes and plasma cytokine levels in moderate and severe asphyxia in order to identify players of the inflammatory response that may influence patient outcome. Methods We analyzed the data of 28 term neonates requiring moderate systemic hypothermia in a single-center observational study. Blood samples were collected between 3 and 6 h of life, at 24 h, 72 h, 1 week, and 1 month of life. Neonates were divided into a moderate (n = 17) and a severe (n = 11) group based on neuroradiological and amplitude-integrated EEG characteristics. Peripheral blood mononuclear cells were assessed with flow cytometry. Cytokine plasma levels were measured using Bioplex immunoassays. Components of the kynurenine pathway were assessed by high-performance liquid chromatography. Results The prevalence and extravasation of IL-1b + CD4 cells were higher in severe than in moderate asphyxia at 6 h. Based on Receiver operator curve analysis, the assessment of the prevalence of CD4+ IL-1β+ and CD4+ IL-1β+ CD49d+ cells at 6 h appears to be able to predict the severity of the insult at an early stage in asphyxia. Intracellular levels of TNF-α in CD4 cells were increased at all time points compared to 6 h in both groups. At 1 month, intracellular levels of TNF-α were higher in the severe group. Plasma IL-6 levels were higher at 1 week in the severe group and decreased by 1 month in the moderate group. Intracellular levels of IL-6 peaked at 24 h in both groups. Intracellular TGF-β levels were increased from 24 h onwards in the moderate group. Conclusions IL-1β and IL-6 appear to play a key role in the early events of the inflammatory response, while TNF-α seems to be responsible for prolonged neuroinflammation, potentially contributing to a worse outcome. The assessment of the prevalence of CD4+ IL-1β+ and CD4+ IL-1β+ CD49d+ cells at 6 h appears to be able to predict the severity of the insult at an early stage in asphyxia

Sequencing of the IL6 gene in a case–control study of cerebral palsy in children

BACKGROUND: Cerebral palsy (CP) is a group of nonprogressive disorders of movement and posture caused by abnormal development of, or damage to, motor control centers of the brain. A single nucleotide polymorphism (SNP), rs1800795, in the promoter region of the interleukin-6 (IL6) gene has been implicated in the pathogenesis of CP by mediating IL-6 protein levels in amniotic fluid and cord plasma and within brain lesions. This SNP has been associated with other neurological, vascular, and malignant processes as well, often as part of a haplotype block. METHODS: To refine the regional genetic association with CP, we sequenced (Sanger) the IL6 gene and part of the promoter region in 250 infants with CP and 305 controls. RESULTS: We identified a haplotype of 7 SNPs that includes rs1800795. In a recessive model of inheritance, the variant haplotype conferred greater risk (OR = 4.3, CI = [2.0-10.1], p = 0.00007) than did the lone variant at rs1800795 (OR = 2.5, CI = [1.4-4.6], p = 0.002). The risk haplotype contains one SNP (rs2069845, CI = [1.2-4.3], OR = 2.3, p = 0.009) that disrupts a methylation site. CONCLUSIONS: The risk haplotype identified in this study overlaps with previously identified haplotypes that include additional promoter SNPs. A risk haplotype at the IL6 gene likely confers risk to CP, and perhaps other diseases, via a multi-factorial mechanism

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages