Best Practice Recommendations for the Diagnosis and Management of Children With Pediatric Inflammatory Multisystem Syndrome Temporally Associated With SARS-CoV-2 (PIMS-TS; Multisystem Inflammatory Syndrome in Children, MIS-C) in Switzerland.

Background: Following the spread of the coronavirus disease 2019 (COVID-19) pandemic a new disease entity emerged, defined as Pediatric Inflammatory Multisystem Syndrome temporally associated with COVID-19 (PIMS-TS), or Multisystem Inflammatory Syndrome in Children (MIS-C). In the absence of trials, evidence for treatment remains scarce. Purpose: To develop best practice recommendations for the diagnosis and treatment of children with PIMS-TS in Switzerland. It is acknowledged that the field is changing rapidly, and regular revisions in the coming months are pre-planned as evidence is increasing. Methods: Consensus guidelines for best practice were established by a multidisciplinary group of Swiss pediatric clinicians with expertise in intensive care, immunology/rheumatology, infectious diseases, hematology, and cardiology. Subsequent to literature review, four working groups established draft recommendations which were subsequently adapted in a modified Delphi process. Recommendations had to reach >80% agreement for acceptance. Results: The group achieved agreement on 26 recommendations, which specify diagnostic approaches and interventions across anti-inflammatory, anti-infectious, and support therapies, and follow-up for children with suspected PIMS-TS. A management algorithm was derived to guide treatment depending on the phenotype of presentation, categorized into PIMS-TS with (a) shock, (b) Kawasaki-disease like, and (c) undifferentiated inflammatory presentation. Conclusion: Available literature on PIMS-TS is limited to retrospective or prospective observational studies. Informed by these cohort studies and indirect evidence from other inflammatory conditions in children and adults, as well as guidelines from international health authorities, the Swiss PIMS-TS recommendations represent best practice guidelines based on currently available knowledge to standardize treatment of children with suspected PIMS-TS. Given the absence of high-grade evidence, regular updates of the recommendations will be warranted, and participation of patients in trials should be encouraged

Detailed stratified GWAS analysis for severe COVID-19 in four European populations

Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended genome-wide association meta-analysis of a well-characterized cohort of 3255 COVID-19 patients with respiratory failure and 12 488 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a ∼0.9-Mb inversion polymorphism that creates two highly differentiated haplotypes and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative including non-Caucasian individuals, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.publishedVersio

Age-dependent impact of the major common genetic risk factor for COVID-19 on severity and mortality

AG has received support by NordForsk Nordic Trial Alliance (NTA) grant, by Academy of Finland Fellow grant N. 323116 and the Academy of Finland for PREDICT consortium N. 340541. The Richards research group is supported by the Canadian Institutes of Health Research (CIHR) (365825 and 409511), the Lady Davis Institute of the Jewish General Hospital, the Canadian Foundation for Innovation (CFI), the NIH Foundation, Cancer Research UK, Genome Québec, the Public Health Agency of Canada, the McGill Interdisciplinary Initiative in Infection and Immunity and the Fonds de Recherche Québec Santé (FRQS). TN is supported by a research fellowship of the Japan Society for the Promotion of Science for Young Scientists. GBL is supported by a CIHR scholarship and a joint FRQS and Québec Ministry of Health and Social Services scholarship. JBR is supported by an FRQS Clinical Research Scholarship. Support from Calcul Québec and Compute Canada is acknowledged. TwinsUK is funded by the Welcome Trust, the Medical Research Council, the European Union, the National Institute for Health Research-funded BioResource and the Clinical Research Facility and Biomedical Research Centre based at Guy’s and St. Thomas’ NHS Foundation Trust in partnership with King’s College London. The Biobanque Québec COVID19 is funded by FRQS, Genome Québec and the Public Health Agency of Canada, the McGill Interdisciplinary Initiative in Infection and Immunity and the Fonds de Recherche Québec Santé. These funding agencies had no role in the design, implementation or interpretation of this study. The COVID19-Host(a)ge study received infrastructure support from the DFG Cluster of Excellence 2167 “Precision Medicine in Chronic Inflammation (PMI)” (DFG Grant: “EXC2167”). The COVID19-Host(a)ge study was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). Genotyping in COVID19-Host(a)ge was supported by a philantropic donation from Stein Erik Hagen. The COVID GWAs, Premed COVID-19 study (COVID19-Host(a)ge_3) was supported by "Grupo de Trabajo en Medicina Personalizada contra el COVID-19 de Andalucia"and also by the Instituto de Salud Carlos III (CIBERehd and CIBERER). Funding comes from COVID-19-GWAS, COVID-PREMED initiatives. Both of them are supported by "Consejeria de Salud y Familias" of the Andalusian Government. DMM is currently funded by the the Andalussian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018). The Columbia University Biobank was supported by Columbia University and the National Center for Advancing Translational Sciences, NIH, through Grant Number UL1TR001873. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or Columbia University. The SPGRX study was supported by the Consejería de Economía, Conocimiento, Empresas y Universidad #CV20-10150. The GEN-COVID study was funded by: the MIUR grant “Dipartimenti di Eccellenza 2018-2020” to the Department of Medical Biotechnologies University of Siena, Italy; the “Intesa San Paolo 2020 charity fund” dedicated to the project NB/2020/0119; and philanthropic donations to the Department of Medical Biotechnologies, University of Siena for the COVID-19 host genetics research project (D.L n.18 of March 17, 2020). Part of this research project is also funded by Tuscany Region “Bando Ricerca COVID-19 Toscana” grant to the Azienda Ospedaliero Universitaria Senese (CUP I49C20000280002). Authors are grateful to: the CINECA consortium for providing computational resources; the Network for Italian Genomes (NIG) (http://www.nig.cineca.it) for its support; the COVID-19 Host Genetics Initiative (https://www.covid19hg.org/); the Genetic Biobank of Siena, member of BBMRI-IT, Telethon Network of Genetic Biobanks (project no. GTB18001), EuroBioBank, and RD-Connect, for managing specimens. Genetics against coronavirus (GENIUS), Humanitas University (COVID19-Host(a)ge_4) was supported by Ricerca Corrente (Italian Ministry of Health), intramural funding (Fondazione Humanitas per la Ricerca). The generous contribution of Banca Intesa San Paolo and of the Dolce&Gabbana Fashion Firm is gratefully acknowledged. Data acquisition and sample processing was supported by COVID-19 Biobank, Fondazione IRCCS Cà Granda Milano; LV group was supported by MyFirst Grant AIRC n.16888, Ricerca Finalizzata Ministero della Salute RF-2016-02364358, Ricerca corrente Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, the European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- “Liver Investigation: Testing Marker Utility in Steatohepatitis”, Programme “Photonics” under grant agreement “101016726” for the project “REVEAL: Neuronal microscopy for cell behavioural examination and manipulation”, Fondazione Patrimonio Ca’ Granda “Liver Bible” PR-0361. DP was supported by Ricerca corrente Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, CV PREVITAL “Strategie di prevenzione primaria nella popolazione Italiana” Ministero della Salute, and Associazione Italiana per la Prevenzione dell’Epatite Virale (COPEV). Genetic modifiers for COVID-19 related illness (BeLCovid_1) was supported by the "Fonds Erasme". The Host genetics and immune response in SARS-Cov-2 infection (BelCovid_2) study was supported by grants from Fondation Léon Fredericq and from Fonds de la Recherche Scientifique (FNRS). The INMUNGEN-CoV2 study was funded by the Consejo Superior de Investigaciones Científicas. KUL is supported by the German Research Foundation (LU 1944/3-1) SweCovid is funded by the SciLifeLab/KAW national COVID-19 research program project grant to Michael Hultström (KAW 2020.0182) and the Swedish Research Council to Robert Frithiof (2014-02569 and 2014-07606). HZ is supported by Jeansson Stiftelser, Magnus Bergvalls Stiftelse. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. Genotyping for the COMRI cohort was performed and funded by the Genotyping Laboratory of Institute for Molecular Medicine Finland FIMM Technology Centre, University of Helsinki, Helsinki, Finland. These funding agencies had no role in the design, implementation or interpretation of this study.Background: There is considerable variability in COVID-19 outcomes amongst younger adults—and some of this variation may be due to genetic predisposition. We characterized the clinical implications of the major genetic risk factor for COVID-19 severity, and its age-dependent effect, using individual-level data in a large international multi-centre consortium. Method: The major common COVID-19 genetic risk factor is a chromosome 3 locus, tagged by the marker rs10490770. We combined individual level data for 13,424 COVID-19 positive patients (N=6,689 hospitalized) from 17 cohorts in nine countries to assess the association of this genetic marker with mortality, COVID-19-related complications and laboratory values. We next examined if the magnitude of these associations varied by age and were independent from known clinical COVID-19 risk factors. Findings: We found that rs10490770 risk allele carriers experienced an increased risk of all-cause mortality (hazard ratio [HR] 1·4, 95% confidence interval [CI] 1·2–1·6) and COVID-19 related mortality (HR 1·5, 95%CI 1·3–1·8). Risk allele carriers had increased odds of several COVID-19 complications: severe respiratory failure (odds ratio [OR] 2·0, 95%CI 1·6-2·6), venous thromboembolism (OR 1·7, 95%CI 1·2-2·4), and hepatic injury (OR 1·6, 95%CI 1·2-2·0). Risk allele carriers ≤ 60 years had higher odds of death or severe respiratory failure (OR 2·6, 95%CI 1·8-3·9) compared to those > 60 years OR 1·5 (95%CI 1·3-1·9, interaction p-value=0·04). Amongst individuals ≤ 60 years who died or experienced severe respiratory COVID-19 outcome, we found that 31·8% (95%CI 27·6-36·2) were risk variant carriers, compared to 13·9% (95%CI 12·6-15·2%) of those not experiencing these outcomes. Prediction of death or severe respiratory failure among those ≤ 60 years improved when including the risk allele (AUC 0·82 vs 0·84, p=0·016) and the prediction ability of rs10490770 risk allele was similar to, or better than, most established clinical risk factors. Interpretation: The major common COVID-19 risk locus on chromosome 3 is associated with increased risks of morbidity and mortality—and these are more pronounced amongst individuals ≤ 60 years. The effect on COVID-19 severity was similar to, or larger than most established risk factors, suggesting potential implications for clinical risk management.Academy of Finland Fellow grant N. 323116Academy of Finland for PREDICT consortium N. 340541.Canadian Institutes of Health Research (CIHR) (365825 and 409511)Lady Davis Institute of the Jewish General HospitalCanadian Foundation for Innovation (CFI)NIH FoundationCancer Research UKGenome QuébecPublic Health Agency of CanadaMcGill Interdisciplinary Initiative in Infection and Immunity and the Fonds de Recherche Québec Santé (FRQS)Japan Society for the Promotion of Science for Young ScientistsCIHR scholarship and a joint FRQS and Québec Ministry of Health and Social Services scholarshipFRQS Clinical Research ScholarshipCalcul QuébecCompute CanadaWelcome TrustMedical Research CouncEuropean UnionNational Institute for Health Research-funded BioResourceClinical Research Facility and Biomedical Research Centre based at Guy’s and St. Thomas’ NHS Foundation TrustKing’s College LondonGenome QuébecPublic Health Agency of CanadaMcGill Interdisciplinary Initiative in Infection and ImmunityFonds de Recherche Québec Santé(DFG Grant: “EXC2167”)(CompLS grant 031L0165)Stein Erik Hagen"Grupo de Trabajo en Medicina Personalizada contra el COVID-19 de Andalucia"Instituto de Salud Carlos III (CIBERehd and CIBERER)COVID-19-GWASCOVID-PREMED initiatives"Consejeria de Salud y Familias" of the Andalusian GovernmentAndalusian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018)Columbia UniversityNational Center for Advancing Translational SciencesNIH Grant Number UL1TR001873Consejería de Economía, Conocimiento, Empresas y Universidad #CV20-10150MIUR grant “Dipartimenti di Eccellenza 2018-2020”“Intesa San Paolo 2020 charity fund” dedicated to the project NB/2020/0119Tuscany Region “Bando Ricerca COVID-19 Toscana”CINECA consortiumNetwork for Italian Genomes (NIG)COVID-19 Host Genetics InitiativeGenetic Biobank of SienaEuroBioBankRD-ConnectRicerca Corrente (Italian Ministry of Health)Fondazione Humanitas per la RicercaBanca Intesa San PaoloDolce&Gabbana Fashion FirmCOVID-19 BiobankFondazione IRCCS Cà Granda MilanoMyFirst Grant AIRC n.16888Ricerca Finalizzata Ministero della Salute RF-2016-02364358Ricerca corrente Fondazione IRCCS Ca’ Granda Ospedale Maggiore PoliclinicoEuropean Union (EU) Programme Horizon 2020 (under grant agreement No. 777377)“Photonics” “101016726”Fondazione Patrimonio Ca’ Granda “Liver Bible” PR-0361CV PREVITAL “Strategie di prevenzione primaria nella popolazione Italiana” Ministero della Salute, and Associazione Italiana per la Prevenzione dell’Epatite Virale (COPEV)"Fonds Erasme"Fondation Léon FredericqFonds de la Recherche Scientifique (FNRS)Consejo Superior de Investigaciones CientíficasGerman Research Foundation (LU 1944/3-1)SciLifeLab/KAW national COVID-19 research program project (KAW 2020.0182)Swedish Research Council (2014-02569 and 2014-07606)Jeansson Stiftelser, Magnus Bergvalls StiftelseTechnical University of Munich, Munich, GermanyGenotyping Laboratory of Institute for Molecular Medicine Finland FIMM Technology Centre, University of Helsinki, Helsinki, Finlan

Rheumatoid arthritis - treatment: 180. Utility of Body Weight Classified Low-Dose Leflunomide in Japanese Rheumatoid Arthritis

Background: In Japan, more than 20 rheumatoid arthritis (RA) patients died of interstitial pneumonia (IP) caused by leflunomide (LEF) were reported, but many of them were considered as the victims of opportunistic infection currently. In this paper, efficacy and safety of low-dose LEF classified by body weight (BW) were studied. Methods: Fifty-nine RA patients were started to administrate LEF from July 2007 to July 2009. Among them, 25 patients were excluded because of the combination with tacrolimus, and medication modification within 3 months before LEF. Remaining 34 RA patients administered 20 to 50 mg/week of LEF were followed up for 1 year and enrolled in this study. Dose of LEF was classified by BW (50 mg/week for over 50 kg, 40 mg/week for 40 to 50 kg and 20 to 30 mg/week for under 40 kg). The average age and RA duration of enrolled patients were 55.5 years old and 10.2 years. Prednisolone (PSL), methotrexate (MTX) and etanercept were used in 23, 28 and 2 patients, respectively. In case of insufficient response or adverse effect, dosage change or discontinuance of LEF were considered. Failure was defined as dosages up of PSL and MTX, or dosages down or discontinuance of LEF. Last observation carried forward method was used for the evaluation of failed patients at 1 year. Results: At 1 year after LEF start, good/ moderate/ no response assessed by the European League Against Rheumatism (EULAR) response criteria using Disease Activity Score, including a 28-joint count (DAS28)-C reactive protein (CRP) were showed in 14/ 10/ 10 patients, respectively. The dosage changes of LEF at 1 year were dosage up: 10, same dosage: 5, dosage down: 8 and discontinuance: 11 patients. The survival rate of patients in this study was 23.5% (24 patients failed) but actual LEF continuous rate was 67.6% (11 patients discontinued) at 1 year. The major reason of failure was liver dysfunction, and pneumocystis pneumonia was occurred in 1 patient resulted in full recovery. One patient died of sepsis caused by decubitus ulcer infection. DAS28-CRP score was decreased from 3.9 to 2.7 significantly. Although CRP was decreased from 1.50 to 0.93 mg/dl, it wasn't significant. Matrix metalloproteinase (MMP)-3 was decreased from 220.0 to 174.2 ng/ml significantly. Glutamate pyruvate transaminase (GPT) was increased from 19 to 35 U/l and number of leukocyte was decreased from 7832 to 6271 significantly. DAS28-CRP, CRP, and MMP-3 were improved significantly with MTX, although they weren't without MTX. Increase of GPT and leukopenia were seen significantly with MTX, although they weren't without MTX. Conclusions: It was reported that the risks of IP caused by LEF in Japanese RA patients were past IP history, loading dose administration and low BW. Addition of low-dose LEF is a potent safe alternative for the patients showing unsatisfactory response to current medicines, but need to pay attention for liver function and infection caused by leukopenia, especially with MTX. Disclosure statement: The authors have declared no conflicts of interes

Neonatal, infant, and under-5 mortality and morbidity burden in the Eastern Mediterranean region: findings from the Global Burden of Disease 2015 study

Objectives Although substantial reductions in under-5 mortality have been observed during the past 35 years, progress in the Eastern Mediterranean Region (EMR) has been uneven. This paper provides an overview of child mortality and morbidity in the EMR based on the Global Burden of Disease (GBD) study. Methods We used GBD 2015 study results to explore under-5 mortality and morbidity in EMR countries. Results In 2015, 755,844 (95% uncertainty interval (UI) 712,064–801,565) children under 5 died in the EMR. In the early neonatal category, deaths in the EMR decreased by 22.4%, compared to 42.4% globally. The rate of years of life lost per 100,000 population under 5 decreased 54.38% from 177,537 (173,812–181,463) in 1990 to 80,985 (76,308–85,876) in 2015; the rate of years lived with disability decreased by 0.57% in the EMR compared to 9.97% globally. Conclusions Our findings call for accelerated action to decrease child morbidity and mortality in the EMR. Governments and organizations should coordinate efforts to address this burden. Political commitment is needed to ensure that child health receives the resources needed to end preventable deaths

Mutations in the histone methyltransferase gene KMT2B cause complex early-onset dystonia.

Histone lysine methylation, mediated by mixed-lineage leukemia (MLL) proteins, is now known to be critical in the regulation of gene expression, genomic stability, cell cycle and nuclear architecture. Despite MLL proteins being postulated as essential for normal development, little is known about the specific functions of the different MLL lysine methyltransferases. Here we report heterozygous variants in the gene KMT2B (also known as MLL4) in 27 unrelated individuals with a complex progressive childhood-onset dystonia, often associated with a typical facial appearance and characteristic brain magnetic resonance imaging findings. Over time, the majority of affected individuals developed prominent cervical, cranial and laryngeal dystonia. Marked clinical benefit, including the restoration of independent ambulation in some cases, was observed following deep brain stimulation (DBS). These findings highlight a clinically recognizable and potentially treatable form of genetic dystonia, demonstrating the crucial role of KMT2B in the physiological control of voluntary movement.Funding for the project was provided by the Wellcome Trust for UK10K (WT091310) and DDD Study. The DDD study presents independent research commissioned by the Health Innovation Challenge Fund [grant number HICF-1009-003] - see www.ddduk.org/access.html for full acknowledgement. This work was supported in part by the Intramural Research Program of the National Human Genome Research Institute and the Common Fund, NIH Office of the Director. This work was supported in part by the German Ministry of Research and Education (grant nos. 01GS08160 and 01GS08167; German Mental Retardation Network) as part of the National Genome Research Network to A.R. and D.W. and by the Deutsche Forschungsgemeinschaft (AB393/2-2) to A.R. Brain expression data was provided by the UK Human Brain Expression Consortium (UKBEC), which comprises John A. Hardy, Mina Ryten, Michael Weale, Daniah Trabzuni, Adaikalavan Ramasamy, Colin Smith and Robert Walker, affiliated with UCL Institute of Neurology (J.H., M.R., D.T.), King’s College London (M.R., M.W., A.R.) and the University of Edinburgh (C.S., R.W.)

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: a systematic analysis for the Global Burden of Disease Study 2016

BACKGROUND: Detailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016. METHODS: We have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15-60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to estimate age-specific and sex-specific death rates for each location-year. Using various international databases, we identified fatal discontinuities, which we defined as increases in the death rate of more than one death per million, resulting from conflict and terrorism, natural disasters, major transport or technological accidents, and a subset of epidemic infectious diseases; these were added to estimates in the relevant years. In 47 countries with an identified peak adult prevalence for HIV/AIDS of more than 0·5% and where VR systems were less than 65% complete, we informed our estimates of age-sex-specific mortality using the Estimation and Projection Package (EPP)-Spectrum model fitted to national HIV/AIDS prevalence surveys and antenatal clinic serosurveillance systems. We estimated stillbirths, early neonatal, late neonatal, and childhood mortality using both survey and VR data in spatiotemporal Gaussian process regression models. We estimated abridged life tables for all location-years using age-specific death rates. We grouped locations into development quintiles based on the Socio-demographic Index (SDI) and analysed mortality trends by quintile. Using spline regression, we estimated the expected mortality rate for each age-sex group as a function of SDI. We identified countries with higher life expectancy than expected by comparing observed life expectancy to anticipated life expectancy on the basis of development status alone. FINDINGS: Completeness in the registration of deaths increased from 28% in 1970 to a peak of 45% in 2013; completeness was lower after 2013 because of lags in reporting. Total deaths in children younger than 5 years decreased from 1970 to 2016, and slower decreases occurred at ages 5-24 years. By contrast, numbers of adult deaths increased in each 5-year age bracket above the age of 25 years. The distribution of annualised rates of change in age-specific mortality rate differed over the period 2000 to 2016 compared with earlier decades: increasing annualised rates of change were less frequent, although rising annualised rates of change still occurred in some locations, particularly for adolescent and younger adult age groups. Rates of stillbirths and under-5 mortality both decreased globally from 1970. Evidence for global convergence of death rates was mixed; although the absolute difference between age-standardised death rates narrowed between countries at the lowest and highest levels of SDI, the ratio of these death rates-a measure of relative inequality-increased slightly. There was a strong shift between 1970 and 2016 toward higher life expectancy, most noticeably at higher levels of SDI. Among countries with populations greater than 1 million in 2016, life expectancy at birth was highest for women in Japan, at 86·9 years (95% UI 86·7-87·2), and for men in Singapore, at 81·3 years (78·8-83·7) in 2016. Male life expectancy was generally lower than female life expectancy between 1970 and 2016, an

Measuring the health-related Sustainable Development Goals in 188 countries : a baseline analysis from the Global Burden of Disease Study 2015

Background In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015). Methods We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices. Findings In 2015, the median health-related SDG index was 59.3 (95% uncertainty interval 56.8-61.8) and varied widely by country, ranging from 85.5 (84.2-86.5) in Iceland to 20.4 (15.4-24.9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r(2) = 0.88) and the MDG index (r(2) = 0.2), whereas the non-MDG index had a weaker relation with SDI (r(2) = 0.79). Between 2000 and 2015, the health-related SDG index improved by a median of 7.9 (IQR 5.0-10.4), and gains on the MDG index (a median change of 10.0 [6.7-13.1]) exceeded that of the non-MDG index (a median change of 5.5 [2.1-8.9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened. Interpretation GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient. Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs.Peer reviewe

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015 : a systematic analysis for the Global Burden of Disease Study 2015

Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61.7 years (95% uncertainty interval 61.4-61.9) in 1980 to 71.8 years (71.5-72.2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11.3 years (3.7-17.4), to 62.6 years (56.5-70.2). Total deaths increased by 4.1% (2.6-5.6) from 2005 to 2015, rising to 55.8 million (54.9 million to 56.6 million) in 2015, but age-standardised death rates fell by 17.0% (15.8-18.1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14.1% (12.6-16.0) to 39.8 million (39.2 million to 40.5 million) in 2015, whereas age-standardised rates decreased by 13.1% (11.9-14.3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42.1%, 39.1-44.6), malaria (43.1%, 34.7-51.8), neonatal preterm birth complications (29.8%, 24.8-34.9), and maternal disorders (29.1%, 19.3-37.1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Copyright (C) The Author(s). Published by Elsevier Ltd.Peer reviewe