A prospective study of drug utilization pattern in cardiac intensive care unit at a tertiary care teaching hospital

Background: Cardiovascular diseases remain the most common cause of sudden death. Appropriate drug therapy in cardiac intensive care unit (CICU) is crucial in managing cardiovascular emergencies and to decrease morbidity and mortality. The present study was conducted to observe the emergency cardiac diseases which are most frequently being treated and to study the prescribing prevalence among inpatients in CICU.Methods: A prospective, observational study was carried out among 102 patients admitted in CICU at a tertiary care teaching hospital, Karnataka, for a period of 3 months. Demographic data, clinical history, and complete drug therapy received during their stay in CICU was noted.Results: In our study, males (64.7%) had a higher incidence of cardiovascular emergencies than females (35.3%). Hypertension (32.4%) and Type 2 diabetes mellitus (28.4%) were the frequently associated co-morbid conditions. Antiplatelet drugs 80 (78.4%) was most commonly prescribed, followed by hypolipidemic drugs 75 (73.5%) and anticoagulants 65 (63.7%). The mean duration of stay in the hospital was 4.79±1.9 days. The average number of drugs per prescription was 7.8±2.2. Percentage of drugs prescribed by generic names was 52.9%. The percentage of drugs prescribed from essential drug list was 75.1%.Conclusions: Antiplatelet drugs were the most frequently prescribed drug group. Mean number of drugs per prescription were high. The prescribing pattern could be improved by reducing the number of drugs per prescription and by prescribing generic drugs to reduce the economic burden of the patients

Trafficking and Human Rights in Nepal: Community Perceptions and Policy and Program Responses

This report from the Population Council's Horizons program summarizes the policy analysis, documentation of current intervention models, and community-based study of trafficking in the context of an emerging HIV/AIDS epidemic in Nepal

Weighted Hashing-Based Capture Text Similarity Estimation with the Cross-Media Semantic Level

Web Mining is an emerging trend for the drastic advancement of the different data mining techniques. The web mining process comprises the sequence of operations that are comprises of the different languages those need to be processed effectively. The estimation of the similarity between the ontologies words and the sequences are computed. This paper proposed a Weighted Hashing Similarity Estimation (WHSE). The proposed WHSE model comprises of the weightedvalues for the estimated semantics. The computed semantics are updated in the hashing table for the estimation of the features in the variables. The proposed WHSE computes the similarity score for the extracted sematic word features in the ontology and computes the key words. The proposed WHSE model performance is comparatively examined with the existing technique. The measured recall, precision and accuracy value expressed that proposed WHSE achievesthe 0.98 accuracy value for the semantic ontology. The comparative analysis expressed that proposed WHSE achieves the ~3% -7% improvement than the existing technique for the semantic leve

Healthy lifestyle and life expectancy with and without Alzheimer's dementia: population based cohort study.

OBJECTIVE To determine the impact of lifestyle factors on life expectancy lived with and without Alzheimer's dementia. DESIGN Prospective cohort study. SETTING The Chicago Health and Aging Project, a population based cohort study in the United States. PARTICIPANTS 2449 men and women aged 65 years and older. MAIN EXPOSURE A healthy lifestyle score was developed based on five modifiable lifestyle factors: a diet for brain health (Mediterranean-DASH Diet Intervention for Neurodegenerative Delay-MIND diet score in upper 40% of cohort distribution), late life cognitive activities (composite score in upper 40%), moderate or vigorous physical activity (≥150 min/week), no smoking, and light to moderate alcohol consumption (women 1-15 g/day; men 1-30 g/day). MAIN OUTCOME Life expectancy with and without Alzheimer's dementia in women and men. RESULTS Women aged 65 with four or five healthy factors had a life expectancy of 24.2 years (95% confidence interval 22.8 to 25.5) and lived 3.1 years longer than women aged 65 with zero or one healthy factor (life expectancy 21.1 years, 19.5 to 22.4). Of the total life expectancy at age 65, women with four or five healthy factors spent 10.8% (2.6 years, 2.0 to 3.3) of their remaining years with Alzheimer's dementia, whereas women with zero or one healthy factor spent 19.3% (4.1 years, 3.2 to 5.1) with the disease. Life expectancy for women aged 65 without Alzheimer's dementia and four or five healthy factors was 21.5 years (20.0 to 22.7), and for those with zero or one healthy factor it was 17.0 years (15.5 to 18.3). Men aged 65 with four or five healthy factors had a total life expectancy of 23.1 years (21.4 to 25.6), which is 5.7 years longer than men aged 65 with zero or one healthy factor (life expectancy 17.4 years, 15.8 to 20.1). Of the total life expectancy at age 65, men with four or five healthy factors spent 6.1% (1.4 years, 0.3 to 2.0) of their remaining years with Alzheimer's dementia, and those with zero or one healthy factor spent 12.0% (2.1 years, 0.2 to 3.0) with the disease. Life expectancy for men aged 65 without Alzheimer's dementia and four or five healthy factors was 21.7 years (19.7 to 24.9), and for those with zero or one healthy factor life expectancy was 15.3 years (13.4 to 19.1). CONCLUSION A healthy lifestyle was associated with a longer life expectancy among men and women, and they lived a larger proportion of their remaining years without Alzheimer's dementia. The life expectancy estimates might help health professionals, policy makers, and stakeholders to plan future healthcare services, costs, and needs

Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026

Background The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic; characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic; and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting System (CRS) and the WHO Global Health Expenditure Database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95$7·3 trillion (95% UI 7·2–7·4) in 2019; 293·7 times the $24·8 billion (95$43·1 billion in development assistance was provided to maintain or improve health. The pandemic led to an unprecedented increase in development assistance targeted towards health; in 2020 and 2021, $1·8 billion in DAH contributions was provided towards pandemic preparedness in LMICs, and$37·8 billion was provided for the health-related COVID-19 response. Although the support for pandemic preparedness is 12·2% of the recommended target by the High-Level Independent Panel (HLIP), the support provided for the health-related COVID-19 response is 252·2% of the recommended target. Additionally, projected spending estimates suggest that between 2022 and 2026, governments in 17 (95% UI 11–21) of the 137 LMICs will observe an increase in national government health spending equivalent to an addition of 1% of GDP, as recommended by the HLIP. Interpretation There was an unprecedented scale-up in DAH in 2020 and 2021. We have a unique opportunity at this time to sustain funding for crucial global health functions, including pandemic preparedness. However, historical patterns of underfunding of pandemic preparedness suggest that deliberate effort must be made to ensure funding is maintained

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Typical best vitelliform dystrophy secondary to biallelic variants in BEST1

BACKGROUND: Pathogenic variants in BEST1 can cause autosomal dominant or autosomal recessive dystrophy, typically associated with distinct retinal phenotypes. In heterozygous cases, the disorder is commonly characterized by yellow sub-macular lesions in the early stages, known as Best vitelliform macular dystrophy (BVMD). Biallelic variants usually cause a more severe phenotype including diffuse retinal pigment epithelial irregularity and widespread generalized progressive retinopathy, known as autosomal recessive bestrophinopathy (ARB). This study describes three cases with clinical changes consistent with BVMD, however, unusually associated with autosomal recessive inheritance. MATERIALS AND METHODS: Detailed ophthalmic workup included comprehensive ophthalmologic examination, multimodal retinal imaging, full-field and pattern electroretinography (ERG; PERG), and electrooculogram (EOG). Genetic analysis of probands and segregation testing and fundus examination of proband relatives was performed where possible. RESULTS: Three unrelated cases presented with a clinical phenotype typical for BVMD and were found to have biallelic disease-causing variants in BEST1. PERG P50 and ERG were normal in all cases. The EOG was subnormal (probands 1 and 3) or normal/borderline (proband 2). Probands 1 and 2 were homozygous for the BEST1 missense variant c.139C>T, p.Arg47Cys, while proband 3 was homozygous for a deletion, c.536_538delACA, p.Asn179del. The parents of proband 1 were phenotypically normal. Parents of proband 1 and 2 were heterozygous for the same missense variant. CONCLUSIONS: Individuals with biallelic variants in BEST1 can present with a phenotype indistinguishable from BVMD. The same clinical phenotype may not be evident in those harboring the same variants in the heterozygous state. This has implications for genetic counselling and prognosticationA

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