Should every child with epilepsy undergo screening for psychiatric comorbidities?

Purpose: We aimed to build a classification system that uses resting-state (no visible scalp epileptic activity) EEG-based directed functional connectivity values to assign a patient to one of three classes: left TLE (LTLE), right TLE (RTLE) or healthy control. Methods: Twenty LTLE, 20 RTLE and 35 healthy controls underwent resting-state high-density EEG. For each subject, sixty 1-sec epochs free of artifacts or interictal spikes were selected. The source activity was obtained for 82 regions of interest using an individual head model and distributed linear inverse solution. The summed outflow and whole-brain directed functional connectivity were estimated in the theta, alpha and beta frequency bands using Granger-causal modeling. A Random Forest classifier (an ensemble of decision tree classifiers) was then used to assign the subject to one of three classes. The mean classification accuracy was computed with a leave-one-out procedure. We selected a maximum of six connectivity values for classification, using a greedy forward selection algorithm. Finally, three classifiers were built: ‘Control vs. LTLE’, ‘Control vs. RTLE’ and ‘LTLE vs. RTLE’. In the final classification system, a new subject is assigned to the class that was most voted by these three classifiers. Results: The ‘Control vs. RTLE’ classifier achieved an accuracy of 78.2% (sensitivity: 80.0%, specificity 77.2%), ‘Control vs. LTLE’ an accuracy of 83.6% (sensitivity 85.0%, specificity 82.9%) and ‘LTLE vs. RTLE’ an accuracy of 85.0% (sensitivity 85.0%, specificity 85.0%). Combining these classifiers into one system yielded that 16, 15 and 27 subjects were correctly classified as being, respectively, RTLE, LTLE and control. Conclusion: The high accuracy achieved demonstrates the potential of resting-state EEG-based directed functional connectivity for the diagnosis and lateralization of TLE. This could constitute a new clinical biomarker for surgical candidates and earlier in the course of the disease

Case series, chemotherapy-induced cardiomyopathy: mind the family history!

Background Cardiotoxicity presenting as cardiomyopathy is a common side effect in cancer treatment especially with anthracyclines. The role of genetic predisposition is still being investigated.Case summary Four unrelated patients with a familial burden for cardiac disease, who developed cardiomyopathy after anthracycline treatment are presented. Case 1 received chemotherapy for breast cancer and developed a dilated left ventricle just after treatment. Her father had died unexpectedly while being screened for heart transplant. Case 2 was known with a family history of sudden cardiac death prior to her breast cancer diagnosis. She received anthracycline-containing chemotherapy treatment twice in 5 years due to recurrence of breast cancer. During that period, two brothers developed a cardiomyopathy. Eighteen years later, a genetic predisposition for cardiomyopathy was ascertained and at screening an asymptomatic non-ischaemic cardiomyopathy was established. Case 3 was diagnosed with a dilated cardiomyopathy 1 year after chemotherapy treatment for breast cancer. Her mother had developed a dilated cardiomyopathy several years before. Case 4 received chemotherapy treatment for Non-Hodgkin's lymphoma and developed dilated cardiomyopathy 1 year later. His brother died from congestive heart failure which he developed after chemotherapy for Non-Hodgkin's lymphoma and a grandmother had died suddenly during child delivery. In all four cases, genetic screening showed (likely) pathogenic variants in cardiomyopathy-associated genes.Discussion Current guidelines recommend cardiac evaluation in cancer patients receiving chemotherapy based on the presence of cardiovascular risk factors at the start of treatment. This series emphasizes the importance of including a thorough family history in this process.Experimentele farmacotherapi

SNP association study in PMS2-associated Lynch syndrome

Lynch syndrome (LS) patients are at high risk of developing colorectal cancer (CRC). Phenotypic variability might in part be explained by common susceptibility loci identified in Genome Wide Association Studies (GWAS). Previous studies focused mostly on MLH1, MSH2 and MSH6 carriers, with conflicting results. We aimed to determine the role of GWAS SNPs in PMS2 mutation carriers. A cohort study was performed in 507 PMS2 carriers (124 CRC cases), genotyped for 24 GWAS SNPs, including SNPs at 11q23.1 and 8q23.3. Hazard ratios (HRs) were calculated using a weighted Cox regression analysis to correct for ascertainment bias. Discrimination was assessed with a concordance statistic in a bootstrap cross-validation procedure. Individual SNPs only had non-significant associations with CRC occurrence with HRs lower than 2, although male carriers of allele A at rs1321311 (6p21.31) may have increased risk of CRC (HR = 2.1, 95% CI 1.2–3.0). A polygenic risk score (PRS) based on 24 HRs had an HR of 2.6 (95% CI 1.5–4.6) for the highest compared to the lowest quartile, but had no discriminative ability (c statistic 0.52). Previously suggested SNPs do not modify CRC risk in PMS2 carriers. Future large studies are needed for improved risk stratification among Lynch syndrome patients

PRRT2-related phenotypes in patients with a 16p11.2 deletion

We studied the presence of benign infantile epilepsy (BIE), paroxysmal kinesigenic dyskinesia (PKD), and PKD with infantile convulsions (PKD/IC) in patients with a 16p11.2 deletion including PRRT2 or with a PRRT2 loss-of-function sequence variant. Index patients were recruited from seven Dutch university hospitals. The presence of BIE, PKD and PKD/IC was retrospectively evaluated using questionnaires and medical records. We included 33 patients with a 16p11.2 deletion: three (9%) had BIE, none had PKD or PKD/IC. Twelve patients had a PRRT2 sequence variant: BIE was present in four (p = 0.069), PKD in six (p < 0.001) and PKD/IC in two (p = 0.067). Most patients with a deletion had undergone genetic testing because of developmental problems (87%), whereas all patients with a sequence variant were tested because of a movement disorder (55%) or epilepsy (45%). BIE, PKD and PKD/IC clearly showed incomplete penetrance in patients with 16p11.2 deletions, but were found in all and 95% of patients with a PRRT2 sequence variant in our study and a large literature cohort, respectively. Deletions and sequence variants have the same underlying loss-of-function disease mechanism. Thus, differences in ascertainment have led to overestimating the frequency of BIE, PKD and PKD/IC in patients with a PRRT2 sequence variant. This has important implications for counseling if genome-wide sequencing shows such variants in patients not presenting the PRRT2-related phenotypes

Tracking development assistance for health and for COVID-19 : a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached$8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total,$40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this,$13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and$1.4 billion was repurposed from existing health projects. $3.1 billion (22.4$2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7$1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000–17 : analysis for the Global Burden of Disease Study 2017

Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood diarrhoea. Methods We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor estimates. Findings The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1–65·8), 17·4% (7·7–28·4), and 59·5% (34·2–86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy coverage. Interpretation By co-analysing geospatial trends in diarrhoeal burden and its key risk factors, we could assess candidate drivers of subnational death reduction. Further, by doing a counterfactual analysis of the remaining disease burden using key risk factors, we identified potential intervention strategies for vulnerable populations. In view of the demands for limited resources in LMICs, accurately quantifying the burden of diarrhoea and its drivers is important for precision public health

Search for strong gravity in multijet final states produced in pp collisions at √s=13 TeV using the ATLAS detector at the LHC

A search is conducted for new physics in multijet final states using 3.6 inverse femtobarns of data from proton-proton collisions at √s = 13TeV taken at the CERN Large Hadron Collider with the ATLAS detector. Events are selected containing at least three jets with scalar sum of jet transverse momenta (HT) greater than 1TeV. No excess is seen at large HT and limits are presented on new physics: models which produce final states containing at least three jets and having cross sections larger than 1.6 fb with HT > 5.8 TeV are excluded. Limits are also given in terms of new physics models of strong gravity that hypothesize additional space-time dimensions

Operation and performance of the ATLAS semiconductor tracker

The semiconductor tracker is a silicon microstrip detector forming part of the inner tracking system of the ATLAS experiment at the LHC. The operation and performance of the semiconductor tracker during the first years of LHC running are described. More than 99% of the detector modules were operational during this period, with an average intrinsic hit efficiency of (99.74±0.04)%. The evolution of the noise occupancy is discussed, and measurements of the Lorentz angle, δ-ray production and energy loss presented. The alignment of the detector is found to be stable at the few-micron level over long periods of time. Radiation damage measurements, which include the evolution of detector leakage currents, are found to be consistent with predictions and are used in the verification of radiation background simulations

Measurement of the correlation between flow harmonics of different order in lead-lead collisions at √sNN = 2.76 TeV with the ATLAS detector

Correlations between the elliptic or triangular flow coefficients vm (m=2 or 3) and other flow harmonics vn (n=2 to 5) are measured using √sNN=2.76 TeV Pb+Pb collision data collected in 2010 by the ATLAS experiment at the LHC, corresponding to an integrated luminosity of 7 μb−1. The vm−vn correlations are measured in midrapidity as a function of centrality, and, for events within the same centrality interval, as a function of event ellipticity or triangularity defined in a forward rapidity region. For events within the same centrality interval, v3 is found to be anticorrelated with v2 and this anticorrelation is consistent with similar anticorrelations between the corresponding eccentricities, ε2 and ε3. However, it is observed that v4 increases strongly with v2, and v5 increases strongly with both v2 and v3. The trend and strength of the vm−vn correlations for n=4 and 5 are found to disagree with εm−εn correlations predicted by initial-geometry models. Instead, these correlations are found to be consistent with the combined effects of a linear contribution to vn and a nonlinear term that is a function of v22 or of v2v3, as predicted by hydrodynamic models. A simple two-component fit is used to separate these two contributions. The extracted linear and nonlinear contributions to v4 and v5 are found to be consistent with previously measured event-plane correlations