Recurrent respiratory tract infections (rRTIs) frequently affect young children and are associated with antibody deficiencies. We investigated the prevalence of and epidemiological risk factors ...associated with antibody deficiencies in young children with rRTIs and their progression over time, and linked these to prospectively measured RTI symptoms.
We included children <7 years with rRTIs in a prospective cohort study. Patient characteristics associated with antibody deficiencies were identified using multivariable logistic regression analysis.
We included 146 children with a median age of 3.1 years. Daily RTI symptoms were monitored in winter in n = 73 children and repeated immunoglobulin level measurements were performed in n = 45 children. Antibody deficiency was diagnosed in 56% and associated with prematurity (OR 3.17 1.15-10.29) and a family history of rRTIs (OR 2.37 1.11-5.15). Respiratory symptoms did not differ between children with and without antibody deficiencies. During follow-up, antibody deficiency diagnosis remained unchanged in 67%, while 18% of children progressed to a more severe phenotype.
Immune maturation and genetic predisposition may lie at the basis of antibody deficiencies commonly observed in early life. Because disease severity did not differ between children with and without antibody deficiency, we suggest symptom management can be similar for all children with rRTIs.
An antibody deficiency was present in 56% of children <7 years with recurrent respiratory tract infections (rRTIs) in a Dutch tertiary hospital setting. Prematurity and a family history of rRTIs were associated with antibody deficiencies, suggesting that immune maturation and genetic predisposition may lie at the basis of antibody deficiencies in early life. RTI symptoms did not differ between children with and without antibody deficiency, suggesting that symptom management can be similar for all children with rRTIs, irrespective of humoral immunological deficiencies. During follow-up, 18% of children progressed to a more severe phenotype, emphasizing that early diagnosis is warranted to prevent long-term morbidity and increase quality of life.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Introduction
The simultaneously increased prevalence of atopic diseases and decreased prevalence of infectious diseases might point to a link between the two entities. Past work mainly focused on ...either atopic diseases or recurrent infections. We aim to investigate whether risk factors for atopic diseases (ie, asthma, allergic rhinitis, atopic dermatitis, and/or food allergy) differ from risk factors for recurrent respiratory tract infections (RRTIs) in children.
Methods
Cross‐sectional data were used from 5517 children aged 1 to 18 years who participated in an Electronic Portal for children between 2011 and 2019. Univariable/multivariable logistic regression analyses were performed to determine risk factors for any atopic disease and RRTIs.
Results
Children aged ≥5 years were more likely to have any atopic disease (adjusted odds ratio OR: 1.50‐2.77) and less likely to have RRTIs (OR: 0.68‐0.84) compared to children aged less than 5 years. Female sex (OR: 0.72; 95% confidence interval CI: 0.63‐0.81), low birth weight (OR: 0.74; 95% CI: 0.57‐0.97) and dog ownership (OR: 0.79; 95% CI: 0.66‐0.95) reduced the odds of any atopic disease, but not of RRTIs. Daycare attendance (OR: 1.22; 95% CI: 1.02‐1.47) was associated with RRTIs, but not with atopic diseases. A family history of asthma, allergic rhinitis, atopic dermatitis, and RRTIs was significantly associated with the same entity in children, with OR varying from 1.58 (95% CI: 1.35‐1.85) in allergic rhinitis to 2.20 (95% CI: 1.85‐2.61) in asthma.
Conclusion
Risk factors for atopic diseases are distinct from risk factors for RRTIs, suggesting that the changing prevalence of both entities is not related to shared risk factors.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Background
Hospitalized pediatric oncology patients are at risk of severe clinical deterioration. Yet Pediatric Early Warning System (PEWS) scores have not been prospectively validated in these ...patients. We aimed to determine the predictive performance of the modified BedsidePEWS score for unplanned pediatric intensive care unit (PICU) admission and cardiopulmonary resuscitation (CPR) in this patient population.
Methods
We performed a prospective cohort study in an 80‐bed pediatric oncology hospital in the Netherlands, where care has been nationally centralized. All hospitalized pediatric oncology patients aged 0–18 years were eligible for inclusion. A Cox proportional hazard model was estimated to study the association between BedsidePEWS score and unplanned PICU admissions or CPR. The predictive performance of the model was internally validated by bootstrapping.
Results
A total of 1137 patients were included. During the study, 103 patients experienced 127 unplanned PICU admissions and three CPRs. The hazard ratio for unplanned PICU admission or CPR was 1.65 (95% confidence interval CI: 1.59–1.72) for each point increase in the modified BedsidePEWS score. The discriminative ability was moderate (D‐index close to 0 and a C‐index of 0.83 95% CI: 0.79–0.90). Positive and negative predictive values of modified BedsidePEWS score at the widely used cutoff of 8, at which escalation of care is required, were 1.4% and 99.9%, respectively.
Conclusion
The modified BedsidePEWS score is significantly associated with requirement of PICU transfer or CPR. In pediatric oncology patients, this PEWS score may aid in clinical decision‐making for timing of PICU transfer.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
IntroductionHospitalised paediatric oncology patients are at risk to develop acute complications. Early identification of clinical deterioration enabling adequate escalation of care remains ...challenging. Various Paediatric Early Warning Systems (PEWSs) have been evaluated, also in paediatric oncology patients but mostly in retrospective or case–control study designs. This study protocol encompasses the first prospective cohort with the aim of evaluating the predictive performance of a modified Bedside PEWS score for non-elective paediatric intensive care unit (PICU) admission or cardiopulmonary resuscitation in hospitalised paediatric oncology patients.Methods and analysisA prospective cohort study will be conducted at the 80-bed Dutch paediatric oncology hospital, where all national paediatric oncology care has been centralised, directly connected to a shared 22-bed PICU. All patients between 1 February 2019 and 1 February 2021 admitted to the inpatient nursing wards, aged 0–18 years, with an International Classification of Diseases for Oncology (ICD-O) diagnosis of paediatric malignancy will be eligible. A Cox proportional hazard regression model will be used to estimate the association between the modified Bedside PEWS and time to non-elective PICU transfer or cardiopulmonary arrest. Predictive performance (discrimination and calibration) will be assessed internally using resampling validation. To account for multiple occurrences of the event of interest within each patient, the unit of study is a single uninterrupted ward admission (a clinical episode).Ethics and disseminationThe study protocol has been approved by the institutional ethical review board of our hospital (MEC protocol number 16-572/C). We adapted our enrolment procedure to General Data Protection Regulation compliance. Results will be disseminated at scientific conferences, regional educational sessions and publication in peer-reviewed journals.Trial registration numberNetherlands Trial Registry (NL8957).
Language deficits are a major characteristic of neurobehavioral dysfunction in pediatric HIV disease. An object decision task, which assessed reaction time facilitation following a semantic or ...identical prime in comparison to an unrelated prime, was used to investigate whether semantic processing abnormalities could be responsible, in part, for these deficits. Thirty children with vertically acquired HIV infection (M age 9.0 years; range 6-13) participated. Either a picture of the same object (repetition prime), a semantically related object (semantic prime), a semantically unrelated object, or a nonsense object preceded a target picture, which in 50% of the cases was a real object. Brain scans of children were rated and used together with neurobehavioral functioning to classify children as having HIV-related CNS abnormalities (n = 13) or not (n = 17). Increased semantic priming but not repetition priming was associated with a greater degree of cortical atrophy. Furthermore, CNS compromised children had significantly faster reaction times following a semantic prime compared to an unrelated prime than non-compromised patients. This facilitation following semantic priming for the CNS compromised patients (13.3%) almost equaled the facilitation following repetition priming (15.3%) while for the non-compromised patients facilitation following semantic priming (7.9%) was clearly smaller than following repetition priming (14.6%). These data suggest that HIV infection in children may result in a reduced neural network leading to impoverished semantic representations characterized by poor differentiation between closely related objects.
Objective: Severe fatigue is highly prevalent in various chronic diseases. Disease-specific fatigue models have been developed, but it is possible that fatigue-related factors in these models are ...similar across diseases. The purpose of the current study was to determine the amount of variance in fatigue severity explained by: (a) the specific disease, (b) factors associated with fatigue across different chronic diseases (transdiagnostic factors), and (c) the interactions between these factors and specific diseases. Method: Data from 15 studies that included 1696 patients with common chronic diseases and disorders that cause long-term disabilities were analyzed. Linear regression analysis with the generalized least-squares technique was used to determine fatigue-related factors associated with fatigue severity, that is, demographic variables, health-related symptoms and psychosocial variables. Results: Type of chronic disease explained 11% of the variance noted in fatigue severity. The explained variance increased to 55% when the transdiagnostic factors were added to the model. These factors were female sex, age, motivational and concentration problems, pain, sleep disturbances, physical functioning, reduced activity and lower self-efficacy concerning fatigue. The predicted variance increased to 61% when interaction terms were added. Analysis of the interactions revealed that the relationship between fatigue severity and relevant predictors mainly differed in strength, not in direction. Conclusions: Fatigue severity can largely be explained by transdiagnostic factors; the associations vary between chronic diseases in strength and significance. This suggests that severely fatigued patients with different chronic diseases can probably benefit from a transdiagnostic fatigue-approach which focuses on individual patient needs rather than a specific disease.
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CEKLJ, FFLJ, NUK, ODKLJ, PEFLJ, UPUK
ABSTRACT
Upcoming advances in galaxy surveys and cosmic microwave background data will enable measurements of the anisotropic distribution of diffuse gas in filaments and superclusters at redshift ...z = 1 and beyond, observed through the thermal Sunyaev–Zel’dovich (tSZ) effect. These measurements will help distinguish between different astrophysical feedback models, account for baryons that appear to be ‘missing’ from the cosmic census, and present opportunities for using locally anisotropic tSZ statistics as cosmological probes. This study seeks to guide such future measurements by analysing whether diffuse intergalactic gas is a major contributor to anisotropic tSZ signal in The Three Hundred Gizmo-Simba hydrodynamic simulations. We apply multiple different halo boundary and temperature criteria to divide concentrated from diffuse gas at z = 1, then create mock Compton- y maps for the separated components. The maps from 98 simulation snapshots are centred on massive galaxy clusters, oriented by the most prominent filament axis in the galaxy distribution, and stacked. Results vary significantly depending on the definition used for diffuse gas, indicating that assumptions should be clearly defined when claiming observations of the warm-hot intergalactic medium. In all cases, the diffuse gas is important, contributing 25–60 per cent of the tSZ signal in the far field (>4 h−1 comoving Mpc) from the stacked clusters. The gas 1–2 virial radii from halo centres is especially key. Oriented stacking and environmental selections help to amplify the signal from the warm-hot intergalactic medium, which is aligned but less concentrated along the filament axis than the hot halo gas.
This article describes the IFS-AER aerosol module used operationally in the Integrated Forecasting System (IFS) cycle 45R1, operated by the European Centre for Medium-Range Weather Forecasts (ECMWF) ...in the framework of the Copernicus Atmospheric Monitoring Services (CAMS). We describe the different parameterizations for aerosol sources, sinks, and its chemical production in IFS-AER, as well as how the aerosols are integrated in the larger atmospheric composition forecasting system. The focus is on the entire 45R1 code base, including some components that are not used operationally, in which case this will be clearly specified. This paper is an update to the Morcrette et al. (2009) article that described aerosol forecasts at the ECMWF using cycle 32R2 of the IFS. Between cycles 32R2 and 45R1, a number of source and sink processes have been reviewed and/or added, notably increasing the complexity of IFS-AER. A greater integration with the tropospheric chemistry scheme of the IFS has been achieved for the sulfur cycle and for nitrate production. Two new species, nitrate and ammonium, have also been included in the forecasting system. Global budgets and aerosol optical depth (AOD) fields are shown, as is an evaluation of the simulated particulate matter (PM) and AOD against observations, showing an increase in skill from cycle 40R2, used in the CAMS interim ReAnalysis (CAMSiRA), to cycle 45R1.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Current practice of chemical risk assessment for consumer product ingredients still rarely exercises the aggregation of multi-source exposure. However, focusing on a single dominant source/pathway ...combination may lead to a significant underestimation of the risk for substances present in numerous consumer products, which often are used simultaneously. Moreover, in most cases complex multi-route exposure scenarios also need to be accounted for. This paper introduces and evaluates the performance of the Probabilistic Aggregate Consumer Exposure Model (PACEM) applied in the context of a tiered approach to exposure assessment for ingredients in cosmetics and personal care products (C&PCPs) using decamethylcyclopentasiloxane (D5) as a worked example. It is demonstrated that PACEM predicts a more realistic, but still conservative aggregate exposure within the Dutch adult population when compared to a deterministic point estimate obtained in a lower tier screening assessment. An overall validation of PACEM is performed by quantitatively relating and comparing its estimates to currently available human biomonitoring and environmental sampling data. Moderate (by maximum one order of magnitude) overestimation of exposure is observed due to a justified conservatism built into the model structure, resulting in the tool being suitable for risk assessment.
•A higher tier aggregate consumer exposure model is validated for a cosmetic ingredient.•Person-oriented approach to exposure aggregation yields more realistic values.•The model is reasonably conservative and is thus recommended for risk assessment.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
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