137 research outputs found

    Determinants for hospitalization in " low-risk" community acquired pneumonia

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    BACKGROUND: A variable decision in managing community acquired pneumonia (CAP) is the initial site of care; in-patient versus outpatient. These variations persist despite comprehensive practice guidelines. Patients with a Pneumonia Severity Index (PSI) score lower than seventy have low risk for complications and outpatient antibiotic management is recommended in this group. These patients are generally below the age of fifty years, non-nursing home residents, HIV negative and have no major cardiac, hepatic, renal or malignant diseases. METHODS: A retrospective analysis of 296 low-risk CAP patients evaluated within a year one period at St. Agnes Hospital, Baltimore, Maryland was undertaken. All patients were assigned a PSI score. 208 (70%) were evaluated and discharged from the emergency department (E.D.) to complete outpatient antibiotic therapy, while 88 (30%) were hospitalized. Patients were sub-stratified into classes I-V according to PSI. A comparison of demographic, clinical, social and financial parameters was made between the E.D. discharged and hospitalized groups. RESULTS: Statistically significant differences in favor of the hospitalized group were noted for female gender (CI: 1.46-5.89, p= 0.0018), African Americans (CI: 0.31-0.73, p= 0.004), insurance coverage (CI: 0.19-0.63, p= 0.0034), temperature (CI: 0.04-0.09, p= 0.0001) and pulse rate (CI: 0.03-0.14, p= 0.0001). No statistically significant differences were observed between the two groups for altered mental status, hypotension, tachypnea, laboratory/radiological parameters and social indicators (p>0.05). The average length of stay for in-patients was 3.5 days at about eight time's higher cost than outpatient management. There was no difference in mortality or treatment failures between the two groups. The documentation rate and justifications for hospitalizing low risk CAP patients by admitting physicians was less than optimal. CONCLUSIONS: High fever, tachycardia, female gender, African- American race and medical insurance coverage are determinants for hospitalization among low risk CAP patients in our study. The average length of stay for in-patients was 3.5 days (3 to 5 days). The cost of in-patient care was about eight times higher than outpatient management. This study supports the recommendation of using the PSI for E.D evaluation of patients in appropriate social settings

    Genetic diversity in Napier grass (Cenchrus purpureus ) collections and progeny plants: Potential duplicates and unique genotypes

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    Napier grass is an important perennial tropical grass grown as a forage and energy crop, however, it has a limited global diversity mainly due to its vegetative propagation. In this study, 345 Napier grass genotypes composed of 199 progeny plants raised from 13 seed-setting accessions, 19 accessions from USDA-ARS, 25 accessions from ICRISAT, 42 accessions from EMBRAPA, and 60 accessions from ILRI were investigated with the aim of enhancing the genetic diversity and increasing the population size of the Napier grass collection in the ILRI forage genebank. The plants were genotyped using the DArTseq genotyping by sequencing (GBS) method. A total of 96,321 SNP and 96,454 SilicoDArT genome-wide markers were generated. Of these, 85,619 (89 %) SNP and 73,573 (76 %) SilicoDArT markers were mapped onto the fourteen chromosomes of the Napier grass genome. Over 46% of the SilicoDArT and 35% of the SNP markers had a polymorphic information content (PIC) value above 0.25. Genetic diversity analysis using a subset of independent and highly polymorphic SNP markers detected moderate genetic variation among the collections, particularly between the progeny and the four collections, and indicated the presence of unique diversity in the progeny plants. The progeny plants clustered separately from the collections in multivariate analysis (UPGMA and PCA) and scattered across the PCA plot showing the high genetic variability within progeny plants. Variance components calculated by analysis of molecular variance (AMOVA) were also significant both among and within populations, however, more variation (90 %) was within than among populations (10 %). Multilocus genotype (MLG) analysis using Nei’s genetic distance identified 33 potential duplicates (0.02 threshold) suggesting the remaining 312 genotypes as distinct. Of these 312, 81 genotypes were selected as unique genotypes (0.26 threshold) by MLG analysis. The unique genotypes were mainly from progeny plants while the ILRI collection had most of the potential duplicates. The results of this study provide a useful information for the Napier grass breeding strategy and enhancement of genetic diversity in the ILRI collection. The results also provide a useful guide for the management and conservation of the collection in the ILRI forage genebank

    International Study of the Epidemiology of Paediatric Trauma : PAPSA Research Study

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    Objectives: Trauma is a significant cause of morbidity and mortality worldwide. The literature on paediatric trauma epidemiology in low- and middle-income countries (LMICs) is limited. This study aims to gather epidemiological data on paediatric trauma. Methods: This is a multicentre prospective cohort study of paediatric trauma admissions, over 1 month, from 15 paediatric surgery centres in 11 countries. Epidemiology, mechanism of injury, injuries sustained, management, morbidity and mortality data were recorded. Statistical analysis compared LMICs and high-income countries (HICs). Results: There were 1377 paediatric trauma admissions over 31 days; 1295 admissions across ten LMIC centres and 84 admissions across five HIC centres. Median number of admissions per centre was 15 in HICs and 43 in LMICs. Mean age was 7 years, and 62% were boys. Common mechanisms included road traffic accidents (41%), falls (41%) and interpersonal violence (11%). Frequent injuries were lacerations, fractures, head injuries and burns. Intra-abdominal and intra-thoracic injuries accounted for 3 and 2% of injuries. The mechanisms and injuries sustained differed significantly between HICs and LMICs. Median length of stay was 1 day and 19% required an operative intervention; this did not differ significantly between HICs and LMICs. No mortality and morbidity was reported from HICs. In LMICs, in-hospital morbidity was 4.0% and mortality was 0.8%. Conclusion: The spectrum of paediatric trauma varies significantly, with different injury mechanisms and patterns in LMICs. Healthcare structure, access to paediatric surgery and trauma prevention strategies may account for these differences. Trauma registries are needed in LMICs for future research and to inform local policy

    Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

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    BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

    Future and potential spending on health 2015-40 : development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

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    Background The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings We estimated that global spending on health will increase from US9.21trillionin2014to9.21 trillion in 2014 to 24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at 154(UI133181)percapitain2030and154 (UI 133-181) per capita in 2030 and 195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential.Peer reviewe

    Future and potential spending on health 2015-40: Development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

    Get PDF
    Background: The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods: We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings: We estimated that global spending on health will increase from US9.21trillionin2014to9.21 trillion in 2014 to 24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at 154(UI133181)percapitain2030and154 (UI 133-181) per capita in 2030 and 195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation: Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential

    Global economic burden of unmet surgical need for appendicitis

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    Background: There is a substantial gap in provision of adequate surgical care in many low-and middle-income countries. This study aimed to identify the economic burden of unmet surgical need for the common condition of appendicitis. Methods: Data on the incidence of appendicitis from 170 countries and two different approaches were used to estimate numbers of patients who do not receive surgery: as a fixed proportion of the total unmet surgical need per country (approach 1); and based on country income status (approach 2). Indirect costs with current levels of access and local quality, and those if quality were at the standards of high-income countries, were estimated. A human capital approach was applied, focusing on the economic burden resulting from premature death and absenteeism. Results: Excess mortality was 4185 per 100 000 cases of appendicitis using approach 1 and 3448 per 100 000 using approach 2. The economic burden of continuing current levels of access and local quality was US 92492millionusingapproach1and92 492 million using approach 1 and 73 141 million using approach 2. The economic burden of not providing surgical care to the standards of high-income countries was 95004millionusingapproach1and95 004 million using approach 1 and 75 666 million using approach 2. The largest share of these costs resulted from premature death (97.7 per cent) and lack of access (97.0 per cent) in contrast to lack of quality. Conclusion: For a comparatively non-complex emergency condition such as appendicitis, increasing access to care should be prioritized. Although improving quality of care should not be neglected, increasing provision of care at current standards could reduce societal costs substantially

    Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

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    Background Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator.Background Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator

    Transport injuries and deaths in the Eastern Mediterranean Region : findings from the Global Burden of Disease 2015 Study

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    Transport injuries (TI) are ranked as one of the leading causes of death, disability, and property loss worldwide. This paper provides an overview of the burden of TI in the Eastern Mediterranean Region (EMR) by age and sex from 1990 to 2015. Transport injuries mortality in the EMR was estimated using the Global Burden of Disease mortality database, with corrections for ill-defined causes of death, using the cause of death ensemble modeling tool. Morbidity estimation was based on inpatient and outpatient datasets, 26 cause-of-injury and 47 nature-of-injury categories. In 2015, 152,855 (95% uncertainty interval: 137,900-168,100) people died from TI in the EMR countries. Between 1990 and 2015, the years of life lost (YLL) rate per 100,000 due to TI decreased by 15.5%, while the years lived with disability (YLD) rate decreased by 10%, and the age-standardized disability-adjusted life years (DALYs) rate decreased by 16%. Although the burden of TI mortality and morbidity decreased over the last two decades, there is still a considerable burden that needs to be addressed by increasing awareness, enforcing laws, and improving road conditions.Peer reviewe
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