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      How paediatrician researchers are advancing child health

      Nature
      Springer Science and Business Media LLC

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          Global, regional, and national trends in under-5 mortality between 1990 and 2019 with scenario-based projections until 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation

          Background The Sustainable Development Goals (SDGs), set in 2015 by the UN General Assembly, call for all countries to reach an under-5 mortality rate (U5MR) of at least as low as 25 deaths per 1000 livebirths and a neonatal mortality rate (NMR) of at least as low as 12 deaths per 1000 livebirths by 2030. We estimated levels and trends in under-5 mortality for 195 countries from 1990 to 2019, and conducted scenario-based projections of the U5MR and NMR from 2020 to 2030 to assess country progress in, and potential for, reaching SDG targets on child survival and the potential under-5 and neonatal deaths over the next decade. Methods Levels and trends in under-5 mortality are based on the UN Inter-agency Group for Child Mortality Estimation (UN IGME) database on under-5 mortality, which contains around 18 000 country-year datapoints for 195 countries—nearly 10 000 of those datapoints since 1990. The database includes nationally representative mortality data from vital registration systems, sample registration systems, population censuses, and household surveys. As with previous sets of national UN IGME estimates, a Bayesian B-spline bias-reduction model (B3) that considers the systematic biases associated with the different data source types was fitted to these data to generate estimates of under-5 (age 0–4 years) mortality with uncertainty intervals for 1990–2019 for all countries. Levels and trends in the neonatal mortality rate (0–27 days) are modelled separately as the log ratio of the neonatal mortality rate to the under-5 mortality rate using a Bayesian model. Estimated mortality rates are combined with livebirths data to calculate the number of under-5 and neonatal deaths. To assess the regional and global burden of under-5 deaths in the present decade and progress towards SDG targets, we constructed several scenario-based projections of under-5 mortality from 2020 to 2030 and estimated national, regional, and global under-5 mortality trends up to 2030 for each scenario. Findings The global U5MR decreased by 59% (90% uncertainty interval [UI] 56–61) from 93·0 (91·7–94·5) deaths per 1000 livebirths in 1990 to 37·7 (36·1–40·8) in 2019, while the annual number of global under-5 deaths declined from 12·5 (12·3–12·7) million in 1990 to 5·2 (5·0–5·6) million in 2019—a 58% (55–60) reduction. The global NMR decreased by 52% (90% UI 48–55) from 36·6 (35·6–37·8) deaths per 1000 livebirths in 1990, to 17·5 (16·6–19·0) in 2019, and the annual number of global neonatal deaths declined from 5·0 (4·9–5·2) million in 1990, to 2·4 (2·3–2·7) million in 2019, a 51% (47–54) reduction. As of 2019, 122 of 195 countries have achieved the SDG U5MR target, and 20 countries are on track to achieve the target by 2030, while 53 will need to accelerate progress to meet the target by 2030. 116 countries have reached the SDG NMR target with 16 on track, leaving 63 at risk of missing the target. If current trends continue, 48·1 million under-5 deaths are projected to occur between 2020 and 2030, almost half of them projected to occur during the neonatal period. If all countries met the SDG target on under-5 mortality, 11 million under-5 deaths could be averted between 2020 and 2030. Interpretation As a result of effective global health initiatives, millions of child deaths have been prevented since 1990. However, the task of ending all preventable child deaths is not done and millions more deaths could be averted by meeting international targets. Geographical and economic variation demonstrate the possibility of even lower mortality rates for children under age 5 years and point to the regions and countries with highest mortality rates and in greatest need of resources and action. Funding Bill & Melinda Gates Foundation, US Agency for International Development.
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            Clinical research for rare disease: opportunities, challenges, and solutions.

            Over 7000 rare diseases, each <200,000 US residents, affect nearly 30 million people in the United States. Furthermore, for the 10% of people with a rare disease and for their families, these disorders no longer seem rare. Molecular genetics have characterized the cause of many rare diseases and provide unprecedented opportunities for identifying patients, determining phenotypes, and devising treatments to prevent, stabilize, or improve each disease. Rare disease research poses challenges to investigators requiring specific approaches to: (1) the design of clinical studies; (2) the funding of research programs; (3) the discovery, testing, and approval of new treatments, and (4) the training of clinical scientists. Rigorous, statistically-valid, natural history-controlled, cross-over, and n-of-1 trials can establish efficacy and support regulatory approval of new treatments for rare diseases. The U.S. Orphan Drug Act of the U.S. FDA has stimulated industry investment in clinical trials to develop treatments for rare diseases. For trainees interested in finding a treatment for a rare disease, a commitment to longitudinal care of patients provides a base for the characterization of phenotype and natural history, a stimulus for innovation, a target population for research and helps fund training and research. The scientific methodology, financial resources, and logistics of clinical research for rare diseases have changed dramatically in the past two decades resulting in increased understanding of the pathophysiology of these disorders and direct benefit to patients.
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              Reductions In Hospitalizations Among Children Referred To A Primary Care–Based Medical-Legal Partnership: Study examines hospitalizations among children who are referred to a primary care-based medical-legal partnership.

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                Author and article information

                Journal
                Nature
                Nature
                Springer Science and Business Media LLC
                0028-0836
                1476-4687
                October 19 2023
                October 18 2023
                October 19 2023
                : 622
                : 7983
                : S5-S9
                Article
                10.1038/d41586-023-03234-9
                f6200646-6a28-4c44-a7c1-07a846e4c982
                © 2023

                https://www.springernature.com/gp/researchers/text-and-data-mining

                https://www.springernature.com/gp/researchers/text-and-data-mining

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