Alarming prevalence of Candida auris among critically ill patients in intensive care units in Dhaka City, Bangladesh

Background: Candida auris is a multidrug-resistant yeast capable of invasive infection with high mortality and healthcare-associated outbreaks globally. Due to limited labratory capacity, the burden of C. auris is unknown in Bangladesh. We estimated the extent of C. auris colonization and infection among patients in Dhaka city intensive care units. Methods: During August 2021–September 2022 at adult intensive care units (ICUs) and neonatal intensive care units (NICUs) of 1 government and 1 private tertiary-care hospital, we collected skin swabs from all patients and blood samples from sepsis patients on admission, mid-way through, and at the end of ICU or NICU stays. Skin swab and blood with growth in blood-culture bottle were inoculated in CHROMagar, and identification of isolates was confirmed by VITEK-2. Patient characteristics and healthcare history were collected. We performed descriptive analyses, stratifying by specimen and ICU type. Results: Of 740 patients enrolled, 59 (8%) were colonized with C. auris, of whom 2 (0.3%) later developed a bloodstream infection (BSI). Among patients colonized with C. auris, 27 (46%) were identified in the ICU and 32 (54%) were identified from the NICU. The median age was 55 years for C. auris–positive ICU patients and 4 days for those in the NICU. Also, 60% of all C. auris patients were male. Among 366 ICU patients, 15 (4%) were positive on admission and 12 (3%) became colonized during their ICU stay. Among 374 NICU patients, 19 (5%) were colonized on admission and 13 (4%) became colonized during their NICU stay. All units identified C. auris patients on admission and those who acquired it during their ICU or NICU stay, but some differences were observed among hospitals and ICUs (Figure). Among patients colonized on admission to the ICU, 11 (73%) were admitted from another ward, 3 (20%) were admitted from another hospital, and 1 (7%) were admitted from home. Of patients colonized on admission to the NICU, 4 (21%) were admitted from the obstetric ward, 9 (47%) were admitted from another hospital, and 6 (32%) were admitted from home. In addition, 18 patients with C. auris died (12 in the ICU and 6 in the NICU); both patients with C. auris BSIs died. Conclusions: In these Bangladesh hospitals, 8% of ICU or NICU patients were positive for C. auris, including on admission and acquired during their ICU or NICU stay. This high C. auris prevalence emphasizes the need to enhance case detection and strengthen infection prevention and control. Factors contributing to C. auris colonization should be investigated to inform and strengthen prevention and control strategies

Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015.

BACKGROUND: Healthy life expectancy (HALE) and disability-adjusted life-years (DALYs) provide summary measures of health across geographies and time that can inform assessments of epidemiological patterns and health system performance, help to prioritise investments in research and development, and monitor progress toward the Sustainable Development Goals (SDGs). We aimed to provide updated HALE and DALYs for geographies worldwide and evaluate how disease burden changes with development. METHODS: We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2015. We calculated DALYs by summing years of life lost (YLLs) and years of life lived with disability (YLDs) for each geography, age group, sex, and year. We estimated HALE using the Sullivan method, which draws from age-specific death rates and YLDs per capita. We then assessed how observed levels of DALYs and HALE differed from expected trends calculated with the Socio-demographic Index (SDI), a composite indicator constructed from measures of income per capita, average years of schooling, and total fertility rate. FINDINGS: Total global DALYs remained largely unchanged from 1990 to 2015, with decreases in communicable, neonatal, maternal, and nutritional (Group 1) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). Much of this epidemiological transition was caused by changes in population growth and ageing, but it was accelerated by widespread improvements in SDI that also correlated strongly with the increasing importance of NCDs. Both total DALYs and age-standardised DALY rates due to most Group 1 causes significantly decreased by 2015, and although total burden climbed for the majority of NCDs, age-standardised DALY rates due to NCDs declined. Nonetheless, age-standardised DALY rates due to several high-burden NCDs (including osteoarthritis, drug use disorders, depression, diabetes, congenital birth defects, and skin, oral, and sense organ diseases) either increased or remained unchanged, leading to increases in their relative ranking in many geographies. From 2005 to 2015, HALE at birth increased by an average of 2·9 years (95% uncertainty interval 2·9-3·0) for men and 3·5 years (3·4-3·7) for women, while HALE at age 65 years improved by 0·85 years (0·78-0·92) and 1·2 years (1·1-1·3), respectively. Rising SDI was associated with consistently higher HALE and a somewhat smaller proportion of life spent with functional health loss; however, rising SDI was related to increases in total disability. Many countries and territories in central America and eastern sub-Saharan Africa had increasingly lower rates of disease burden than expected given their SDI. At the same time, a subset of geographies recorded a growing gap between observed and expected levels of DALYs, a trend driven mainly by rising burden due to war, interpersonal violence, and various NCDs. INTERPRETATION: Health is improving globally, but this means more populations are spending more time with functional health loss, an absolute expansion of morbidity. The proportion of life spent in ill health decreases somewhat with increasing SDI, a relative compression of morbidity, which supports continued efforts to elevate personal income, improve education, and limit fertility. Our analysis of DALYs and HALE and their relationship to SDI represents a robust framework on which to benchmark geography-specific health performance and SDG progress. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform financial and research investments, prevention efforts, health policies, and health system improvement initiatives for all countries along the development continuum. FUNDING: Bill & Melinda Gates Foundation

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

Possible misdiagnosis, inappropriate empiric treatment, and opportunities for increased diagnostic testing for patients with vulvovaginal candidiasis-United States, 2018.

Vulvovaginal candidiasis (VVC) is a common cause of vaginitis, but the national burden is unknown, and clinical diagnosis without diagnostic testing is often inaccurate. We aimed to calculate rates and evaluate diagnosis and treatment practices of VVC and recurrent vulvovaginal candidiasis (RVVC) in the United States. We used the 2018 IBM® MarketScan® Research Databases, which include health insurance claims data on outpatient visits and prescriptions for >28 million people. We used diagnosis and procedure codes to examine underlying conditions, vaginitis-related symptoms and conditions, diagnostic testing, and antibacterial and antifungal treatment among female patients with VVC. Among 12.3 million female patients in MarketScan, 149,934 (1.2%) had a diagnosis code for VVC; of those, 3.4% had RVVC. The VVC rate was highest in the South census region (14.3 per 1,000 female patients) and lowest in the West (9.9 per 1000). Over 60% of patients with VVC did not have codes for any diagnostic testing, and microscopy was the most common test type performed in 29.5%. Higher rates of diagnostic testing occurred among patients who visited an OB/GYN (53.4%) compared with a family practice or internal medicine provider (24.2%) or other healthcare provider types (31.9%); diagnostic testing rates were lowest in the South (34.0%) and highest in the Midwest (41.0%). Treatments on or in the 7 days after diagnosis included systemic fluconazole (70.0%), topical antifungal medications (19.4%), and systemic antibacterial medications (17.2%). The low frequencies of diagnostic testing for VVC and high rates of antifungal and antibacterial use suggest substantial empiric treatment, including likely overprescribing of antifungal medications and potentially unnecessary antibacterial medications. These findings support a need for improved clinical care for VVC to improve both patient outcomes and antimicrobial stewardship, particularly in the South and among non-OB/GYN providers

Creation LRB (Light-Response BTB) /PIF (Phytochrome-Interacting Factor) Mutant Lines in Arabidopsis thaliana

Color poster with text, charts, and graphs.Light is vital to plant survival and thus plants have developed sophisticated pathways to respond properly to their light environments. Plants sense specific wavelengths of light via photoreceptors, one family of which are the red (R)/far-red (FR)-absorbing phytochromes (phys). Absorption of red light activates the phys, which causes their translocation from the cytosol to the nucleus where they modulate gene expression. They do so by regulating the activity and levels of a family of transcription factors called Phytochrome-Interacting Factors (PIFs). In response to red light the active phys cause PIFs to be ubiquitylated and degraded, which activates expression of PIF-repressed genes. There is feedback regulation of this pathway as, in response to red light, the PIFs also induce ubiquitylation and degradation of the phys. The genes Light-Response BTB 1 and 2 [LRB1 and LRB2]) are critical regulators of the phy/PIF light-response pathway. LRB1 and LRB2 encode BTB (Bric-a-Brac, Tramtrack, Broad Complex) domain-containing proteins that act as target adapters in E3 ubiquitin-ligase complexes. Plants with disruptions of the LRB genes have reduced light-dependent degradation of phys and, like plants with disruptions of PIF genes, exhibit hypersensitivity to red light. The mechanism by which the LRBs modulate phy levels is not entirely clear, however it has been shown that the LRBs can bind to a complex of a PIF protein (PIF3) and a phy (phyB), leading to ubiquitylation and degradation of both. In order to better understand how the LRB and PIF genes interact we are taking a genetic approach, creating plants with T (transfer)-DNA disruptions of both LRB and PIF genes. Study of the phenotypes of these plants may shed light on how these two families of genes work together to regulate light responses or plant growth and development in general.National Science Foundation-Research in Undergraduate Institutions (RUI) grants (#1354438); University of Wisconsin--Eau Claire Office of Research and Sponsored Program

Creation and Characterization of LRB (Light-Response BTB) IPIF (Phytochrome-Interacting Factor) Mutant Lines in Arabidopsis thaliana

Color poster with text, graphs, charts, and images.In order to better understand how the LRB and PIF genes interact we are taking a genetic approach, creating plants with T (transfer)-DNA disruptions of both LRB and PIF genes. Study of the phenotypes of these plants may shed light on how these two families of genes work together to regulate light responses or plant growth and development in general.National Science Foundation-Research in Undergraduate Institutions (RUI Grants #1354438); Unversity of Wisconsin--Eau Claire Differential Tuition; University of Wisconsin--Eau Claire Office of Research and Sponsored Programs

Candida auris‒Associated Hospitalizations, United States, 2017–2022

Using a large US hospital database, we describe 192 Candida auris‒associated hospitalizations during 2017–2022, including 38 (20%) C. auris bloodstream infections. Hospitalizations involved extensive concurrent conditions and healthcare use; estimated crude mortality rate was 34%. These findings underscore the continued need for public health surveillance and C. auris containment efforts