12 research outputs found

    Radon Gas Concentrations in Soil and Radon Exhalation Rates in Thiqar City

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    First part to determination concentrations of Rn-222 in surface samples of soil, the highest average concentration of Rn-222 was found in AL-Refai region was equal to (127.500±2 Bq/m3), while lowest the average was found in AL-Aekeckh region which was equal to (33.750±2.2 Bq/m3), with an average value of (75.875±21.8 Bq/m3) ,while the (RER) was found to be ranged from (36.821 mBq/m2h) (T19 region) to (139.103 mBq/m2h) (T1 region), with average value (82.780±18.6 mBq/m2h), second part to determine of concentration of Rn-222 in samples of soil from depth 10 cm , the highest average concentration of radon in AL-Refai region which was equal to (109.500±7.7 Bq/m3), while the lowest average concentration of Rn-222 gas was found in AL-Aekeckh region equal to (30.250±2.9 Bq/m3), with an average value (66.703±14.8 Bq/m3), while (RER) was found to be ranged from (33.003 mBq/m2h) (T19 region) to (119.465 mBq/m2h) (T1 region) ,with value of average (72.784±16.2 mBq/m2h).The concentration of Rn-222 in surface soil and at depth (10 cm) were less than the recommended value given (ICRP, 1993)

    Structural and Optical Properties of Cd0.4 Se0.6 Thin Films Prepared by CBD

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    Cd0.4 Se0.6 thin films have been prepared on a glass substrate by chemical bath deposition( CBD) technique. AFM and X-ray analysis were utilized to investigate the effect of thickness variation on surface morphology and crystallinty. The optical properties of thin films were also investigated as a function of film thickness, which was noticed to be improved with the increasing of film thickness. This could be attributed to the fact that films thinner than 400 nm are under strain which decreases as the film thickness increases

    Impact of the COVID-19 pandemic on patients with paediatric cancer in low-income, middle-income and high-income countries: a multicentre, international, observational cohort study

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    OBJECTIVES: Paediatric cancer is a leading cause of death for children. Children in low-income and middle-income countries (LMICs) were four times more likely to die than children in high-income countries (HICs). This study aimed to test the hypothesis that the COVID-19 pandemic had affected the delivery of healthcare services worldwide, and exacerbated the disparity in paediatric cancer outcomes between LMICs and HICs. DESIGN: A multicentre, international, collaborative cohort study. SETTING: 91 hospitals and cancer centres in 39 countries providing cancer treatment to paediatric patients between March and December 2020. PARTICIPANTS: Patients were included if they were under the age of 18 years, and newly diagnosed with or undergoing active cancer treatment for Acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, Wilms' tumour, sarcoma, retinoblastoma, gliomas, medulloblastomas or neuroblastomas, in keeping with the WHO Global Initiative for Childhood Cancer. MAIN OUTCOME MEASURE: All-cause mortality at 30 days and 90 days. RESULTS: 1660 patients were recruited. 219 children had changes to their treatment due to the pandemic. Patients in LMICs were primarily affected (n=182/219, 83.1%). Relative to patients with paediatric cancer in HICs, patients with paediatric cancer in LMICs had 12.1 (95% CI 2.93 to 50.3) and 7.9 (95% CI 3.2 to 19.7) times the odds of death at 30 days and 90 days, respectively, after presentation during the COVID-19 pandemic (p<0.001). After adjusting for confounders, patients with paediatric cancer in LMICs had 15.6 (95% CI 3.7 to 65.8) times the odds of death at 30 days (p<0.001). CONCLUSIONS: The COVID-19 pandemic has affected paediatric oncology service provision. It has disproportionately affected patients in LMICs, highlighting and compounding existing disparities in healthcare systems globally that need addressing urgently. However, many patients with paediatric cancer continued to receive their normal standard of care. This speaks to the adaptability and resilience of healthcare systems and healthcare workers globally

    Surgeons’ practice and preferences for the anal fissure treatment: results from an international survey

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    The best nonoperative or operative anal fissure (AF) treatment is not yet established, and several options have been proposed. Aim is to report the surgeons' practice for the AF treatment. Thirty-four multiple-choice questions were developed. Seven questions were about to participants' demographics and, 27 questions about their clinical practice. Based on the specialty (general surgeon and colorectal surgeon), obtained data were divided and compared between two groups. Five-hundred surgeons were included (321 general and 179 colorectal surgeons). For both groups, duration of symptoms for at least 6 weeks is the most important factor for AF diagnosis (30.6%). Type of AF (acute vs chronic) is the most important factor which guide the therapeutic plan (44.4%). The first treatment of choice for acute AF is ointment application for both groups (59.6%). For the treatment of chronic AF, this data is confirmed by colorectal surgeons (57%), but not by the general surgeons who prefer the lateral internal sphincterotomy (LIS) (31.8%) (p = 0.0001). Botulin toxin injection is most performed by colorectal surgeons (58.7%) in comparison to general surgeons (20.9%) (p = 0.0001). Anal flap is mostly performed by colorectal surgeons (37.4%) in comparison to general surgeons (28.3%) (p = 0.0001). Fissurectomy alone is statistically significantly most performed by general surgeons in comparison to colorectal surgeons (57.9% and 43.6%, respectively) (p = 0.0020). This analysis provides useful information about the clinical practice for the management of a debated topic such as AF treatment. Shared guidelines and consensus especially focused on operative management are required to standardize the treatment and to improve postoperative results

    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

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    BackgroundRegular, 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.MethodsThe 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.FindingsThe 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.InterpretationLong-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
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