Predicting Risk in Patients Hospitalized for Acute Decompensated Heart Failure and Preserved Ejection Fraction: The Atherosclerosis Risk in Communities Study Heart Failure Community Surveillance

Background Risk-prediction models specifically for hospitalized heart failure with preserved ejection fraction are lacking. Methods and Results We analyzed data from the ARIC (Atherosclerosis Risk in Communities) Study Heart Failure Community Surveillance to create and validate a risk score predicting mortality in patients ≥55 years of age admitted with acute decompensated heart failure with preserved ejection fraction (ejection fraction ≥50%). A modified version of the risk-prediction model for acute heart failure developed from patients in the EFFECT (Enhanced Feedback for Effective Cardiac Treatment) study was used as a composite predictor of 28-day and 1-year mortalities and evaluated together with other potential predictors in a stepwise logistic regression. The derivation sample consisted of 1852 hospitalizations from 2005 to 2011 (mean age, 77 years; 65% women; 74% white). Risk scores were created from the identified predictors and validated in hospitalizations from 2012 to 2013 (n=821). Mortality in the derivation and validation sample was 11% and 8% at 28 days and 34% and 31% at 1 year. The modified EFFECT score, including age, systolic blood pressure, blood urea nitrogen, sodium, cerebrovascular disease, chronic obstructive pulmonary disease, and hemoglobin, was a powerful predictor of mortality. Another important predictor for both 28-day and 1-year mortalities was hypoxia. The risk scores were well calibrated and had good discrimination in the derivation sample (area under the curve: 0.76 for 28-day and 0.72 for 1-year mortalities) and validation sample (area under the curve: 0.73 and 0.71, respectively). Conclusions Mortality after acute decompensation in patients with heart failure with preserved ejection fraction is high, with one third of patients dying within a year. A prediction tool may allow for greater discrimination of the highest risk patients. Clinical Trial Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00005131

Burden of Neurological Disorders across the US from 1990-2017: A Global Burden of Disease Study

Importance: Accurate and up-to-date estimates on incidence, prevalence, mortality, and disability-adjusted life-years (burden) of neurological disorders are the backbone of evidence-based health care planning and resource allocation for these disorders. It appears that no such estimates have been reported at the state level for the US. Objective: To present burden estimates of major neurological disorders in the US states by age and sex from 1990 to 2017. Design, Setting, and Participants: This is a systematic analysis of the Global Burden of Disease (GBD) 2017 study. Data on incidence, prevalence, mortality, and disability-adjusted life-years (DALYs) of major neurological disorders were derived from the GBD 2017 study of the 48 contiguous US states, Alaska, and Hawaii. Fourteen major neurological disorders were analyzed: stroke, Alzheimer disease and other dementias, Parkinson disease, epilepsy, multiple sclerosis, motor neuron disease, migraine, tension-type headache, traumatic brain injury, spinal cord injuries, brain and other nervous system cancers, meningitis, encephalitis, and tetanus. Exposures: Any of the 14 listed neurological diseases. Main Outcome and Measure: Absolute numbers in detail by age and sex and age-standardized rates (with 95 uncertainty intervals) were calculated. Results: The 3 most burdensome neurological disorders in the US in terms of absolute number of DALYs were stroke (3.58 95% uncertainty interval UI], 3.25-3.92] million DALYs), Alzheimer disease and other dementias (2.55 95% UI, 2.43-2.68 million DALYs), and migraine (2.40 95% UI, 1.53-3.44 million DALYs). The burden of almost all neurological disorders (in terms of absolute number of incident, prevalent, and fatal cases, as well as DALYs) increased from 1990 to 2017, largely because of the aging of the population. Exceptions for this trend included traumatic brain injury incidence (-29.1% 95% UI, -32.4% to -25.8%); spinal cord injury prevalence (-38.5% 95% UI, -43.1% to -34.0%); meningitis prevalence (-44.8% 95% UI, -47.3% to -42.3%), deaths (-64.4% 95% UI, -67.7% to -50.3%), and DALYs (-66.9% 95% UI, -70.1% to -55.9%); and encephalitis DALYs (-25.8% 95% UI, -30.7% to -5.8%). The different metrics of age-standardized rates varied between the US states from a 1.2-fold difference for tension-type headache to 7.5-fold for tetanus; southeastern states and Arkansas had a relatively higher burden for stroke, while northern states had a relatively higher burden of multiple sclerosis and eastern states had higher rates of Parkinson disease, idiopathic epilepsy, migraine and tension-type headache, and meningitis, encephalitis, and tetanus. Conclusions and Relevance: There is a large and increasing burden of noncommunicable neurological disorders in the US, with up to a 5-fold variation in the burden of and trends in particular neurological disorders across the US states. The information reported in this article can be used by health care professionals and policy makers at the national and state levels to advance their health care planning and resource allocation to prevent and reduce the burden of neurological disorders.. © 2021 American Medical Association. All rights reserved

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2•72 (95% uncertainty interval [UI] 2•66–2•79) in 2000 to 2•31 (2•17–2•46) in 2019. Global annual livebirths increased from 134•5 million (131•5–137•8) in 2000 to a peak of 139•6 million (133•0–146•9) in 2016. Global livebirths then declined to 135•3 million (127•2–144•1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2•1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27•1% (95% UI 26•4–27•8) of global livebirths. Global life expectancy at birth increased from 67•2 years (95% UI 66•8–67•6) in 2000 to 73•5 years (72•8–74•3) in 2019. The total number of deaths increased from 50•7 million (49•5–51•9) in 2000 to 56•5 million (53•7–59•2) in 2019. Under-5 deaths declined from 9•6 million (9•1–10•3) in 2000 to 5•0 million (4•3–6•0) in 2019. Global population increased by 25•7%, from 6•2 billion (6•0–6•3) in 2000 to 7•7 billion (7•5–8•0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58•6 years (56•1–60•8) in 2000 to 63•5 years (60•8–66•1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. Interpretation: Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Global burden of 87 risk factors in 204 countries and territories, 1990�2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods: GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk�outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk�outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk�outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings: The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95 uncertainty interval UI 9·51�12·1) deaths (19·2% 16·9�21·3 of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12�9·31) deaths (15·4% 14·6�16·2 of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253�350) DALYs (11·6% 10·3�13·1 of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0�9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10�24 years, alcohol use for those aged 25�49 years, and high systolic blood pressure for those aged 50�74 years and 75 years and older. Interpretation: Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Exploitation of hybrid vigour in ridge gourd (Luffa acutangula Roxb L.)

A study was conducted for accessing hybrid vigour of 28 crosses of ridge gourd over standard parent during late Kharif 2008 at N.A.U., Navsari. These hybrids were generated by half diallel mating design of eight diverse ridge gourd genotypes. Highly significant difference existed between genotypes for all studied traits. None of the hybrid showed consistent heterosis for all studied traits. In crosses, maximum heterosis was observed for fruit yield per vine followed by primary branches per vine. The highest economic heterosis was observed for fruit yield in ARGS 98-06 x ARGS 00-03 (63.81%) which was followed by ARGS 02-14 x ARGS 03-18 (37.38%), ARGS 04-23 x ARGS 00-03 (34.76%), ARGS 00-03 x ARGS 03-18 (31.67%), ARGS 02-14 x ARGS 98-06 (28.33%), ARGS 04-23 x ARGS 98-06 (26.67%) and SKNRG 21 x ARGS 03-18 (25.00%). These cross combination also showed heterosis for one or more yield contributing traits. Therefore, three hybrids viz., ARGS 98-06 x ARGS 00-03, ARGS 02-14 x ARGS 03-18 and ARGS 04-23 x ARGS 00-03 were identified for evaluation at multi-location and for commercial exploitation