10 research outputs found

    Evaluating the Effectiveness of Lumber Corset Wearing in Low Back Ache: A Rehabilitation Center Based Cross-sectional Study

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    Patients are most commonly advised by medical practitioners even after remaining wide range of controversy regarding wearing of lumber corset in low backache (LBA). Therefore, this study aimed to determine the potential evidence of using lumber orthosis in LBA. The study adopted 50 participants (21 male and 29 female) ages ranging between 20 to 60 years as sample selecting randomly from September to December 2015. Outcome evaluated by calculating and presenting descriptive statistics at 0.05 p-value and x2 test with confidence intervals (95%), Odd Ratio (OR), and Relative Risk (RR). Age and sex were not statistically significant determinants (x2 1.172, p 0.279 and x2 0.593, p 0.441, respectively). Wearing orthosis and reduce pain in a journey found as protective (RR 0.79 and RR 0.94) also poor relationship discovered in considering OR (OR 0.242, 95% CI 0.021-2.780 and OR 0.857, 95% CI 0.164-4.467). Our data were unable to provide adequate proof that wearing lumber corset bring any clinical or therapeutic benefit in managing LBA to the patients

    Scope of Physiotherapy Practice in District Hospitals of the Semi-developed Barisal Division, Barisal, Bangladesh

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    In the developed nations physiotherapist are autonomously participating in the first line and already they are working in the second line treatment alongside with other professionals and the right for the mass population similar to the goal of the public health. The aim of the study was to sort out the real scenario of the development of physiotherapy services as a part of primary health care services including the knowledge and attitude of the general people. A multistage sampling method was selected for conducting the study in districts hospitals of the Barisal division. Result depicted that among the respondents mean age 36.86 ± 4.558 years and most 33.3% (n= 73) of them were younger age range 21-30 years and interestingly highest 41.55% (n= 91) were graduated with highly significant (x2= 1.196, P= 0.000). 65.3% (n= 143) of patients had knowledge about physiotherapy. Majority of case 41.1% (n= 90) orthopedic (x2= 86.175, P= 0.000) and medical condition stroke ware highest 30.1% (n= 66) statically significant (x2= 1.561, P= 0.000). Due to the awareness maximum, 39.70% (n= 87) came from self-reference and 88.4% (n= 176) received exercise therapy including other electrical modalities. Lowest 8.70% (n= 19) of patient expense > 300 BDT. Treatment right time 60.3% (n= 132). Treatment success rate 69.4% (n= 152). Difficulty to come physiotherapy center 43.8% (n= 96). Some limitation that causes insufficiency in treatment provide; 10.6% patient noted poor timing, 30.7% long witting time, 68.3% (n= 136) unpleasant, 78.9% (n= 157) absence of physiotherapist, 9.5% (n= 19) lack of cooperation. Although that 99.5% patient demand physiotherapy center as close as their range and 60.3% (n=132) satisfied with the treatment. Therefore it is strongly suggested to set up a modern physiotherapy department within the primary health care system with the qualified physiotherapist in community-level also District level hospital&nbsp

    Epidemiology of Sports-related Musculoskeletal Injuries Common in Men’s Domestic Cricket: An Analytical Cross-sectional Study Based on Sports Fields

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    Introduction: Despite gaining the popularity of cricket in Bangladesh, raising the competition frequency causes more injury to the athletes. Even after that, they have yet to develop an injury incidence surveillance system. The aim of this study was to determine the incidence of musculoskeletal injuries and related risk factors that elite domestic cricketer sustains during the game. Methods and Materials: A cross-sectional study was conducted in Dhaka, Bangladesh. A total of 198 cricketers with age 15-35 years were purposively adopted for an interview played at least three sessions for the divisional clubs. Participants completed a self-reported questionnaire probing the incidence of injury and risk factors. Binary regression analysis was performed to investigate the correlation of strain injury with other characteristics. Results: Participants had the highest sustained 42.4% strain injury. A rate of 42.9% (P=0.00) was reported for risk factors of strain injury in running but excluding body mass index and ground condition initially. There were no significant differences in strain incidence based on the match, protective equipment, and playing position. Age (odd ration (OR): 0.877, 95% confidence interval(CI): 0.441-1.743), body mass index (OR: 0.268, 95% CI: 0.037-1.960), batsman (OR: 0.376, 95% CI: 0.183-0.770), upper extremity (OR: 6.428, 95% CI: 1.483-27.861) and hard ground (OR: 0.005, 95% CI: 0.001-0.022) were identified as the major risk factors, and the PRICE protocol was proved to be the best physical therapy method to remain in the game. Conclusion: In matches, the batsman is most likely to sustain a strain injury mostly to the upper limb. There is no enough evidence to conclude that the injury monitoring system plays a big role, and therefore more study is much needed in cricket

    Global, regional, and national burden of low back pain, 1990–2020, its attributable risk factors, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021

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    Background: Low back pain is highly prevalent and the main cause of years lived with disability (YLDs). We present the most up-to-date global, regional, and national data on prevalence and YLDs for low back pain from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021. Methods: Population-based studies from 1980 to 2019 identified in a systematic review, international surveys, US medical claims data, and dataset contributions by collaborators were used to estimate the prevalence and YLDs for low back pain from 1990 to 2020, for 204 countries and territories. Low back pain was defined as pain between the 12th ribs and the gluteal folds that lasted a day or more; input data using alternative definitions were adjusted in a network meta-regression analysis. Nested Bayesian meta-regression models were used to estimate prevalence and YLDs by age, sex, year, and location. Prevalence was projected to 2050 by running a regression on prevalence rates using Socio-demographic Index as a predictor, then multiplying them by projected population estimates. Findings: In 2020, low back pain affected 619 million (95% uncertainty interval 554–694) people globally, with a projection of 843 million (759–933) prevalent cases by 2050. In 2020, the global age-standardised rate of YLDs was 832 per 100 000 (578–1070). Between 1990 and 2020, age-standardised rates of prevalence and YLDs decreased by 10·4% (10·9–10·0) and 10·5% (11·1–10·0), respectively. A total of 38·8% (28·7–47·0) of YLDs were attributed to occupational factors, smoking, and high BMI. Interpretation: Low back pain remains the leading cause of YLDs globally, and in 2020, there were more than half a billion prevalent cases of low back pain worldwide. While age-standardised rates have decreased modestly over the past three decades, it is projected that globally in 2050, more than 800 million people will have low back pain. Challenges persist in obtaining primary country-level data on low back pain, and there is an urgent need for more high-quality, primary, country-level data on both prevalence and severity distributions to improve accuracy and monitor change. Funding: Bill and Melinda Gates Foundation

    Global, regional, and national incidence of six major immune-mediated inflammatory diseases: findings from the global burden of disease study 2019Research in context

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    Summary: Background: The causes for immune-mediated inflammatory diseases (IMIDs) are diverse and the incidence trends of IMIDs from specific causes are rarely studied. The study aims to investigate the pattern and trend of IMIDs from 1990 to 2019. Methods: We collected detailed information on six major causes of IMIDs, including asthma, inflammatory bowel disease, multiple sclerosis, rheumatoid arthritis, psoriasis, and atopic dermatitis, between 1990 and 2019, derived from the Global Burden of Disease study in 2019. The average annual percent change (AAPC) in number of incidents and age standardized incidence rate (ASR) on IMIDs, by sex, age, region, and causes, were calculated to quantify the temporal trends. Findings: In 2019, rheumatoid arthritis, atopic dermatitis, asthma, multiple sclerosis, psoriasis, inflammatory bowel disease accounted 1.59%, 36.17%, 54.71%, 0.09%, 6.84%, 0.60% of overall new IMIDs cases, respectively. The ASR of IMIDs showed substantial regional and global variation with the highest in High SDI region, High-income North America, and United States of America. Throughout human lifespan, the age distribution of incident cases from six IMIDs was quite different. Globally, incident cases of IMIDs increased with an AAPC of 0.68 and the ASR decreased with an AAPC of −0.34 from 1990 to 2019. The incident cases increased across six IMIDs, the ASR of rheumatoid arthritis increased (0.21, 95% CI 0.18, 0.25), while the ASR of asthma (AAPC = −0.41), inflammatory bowel disease (AAPC = −0.72), multiple sclerosis (AAPC = −0.26), psoriasis (AAPC = −0.77), and atopic dermatitis (AAPC = −0.15) decreased. The ASR of overall and six individual IMID increased with SDI at regional and global level. Countries with higher ASR in 1990 experienced a more rapid decrease in ASR. Interpretation: The incidence patterns of IMIDs varied considerably across the world. Innovative prevention and integrative management strategy are urgently needed to mitigate the increasing ASR of rheumatoid arthritis and upsurging new cases of other five IMIDs, respectively. Funding: The Global Burden of Disease Study is funded by the Bill and Melinda Gates Foundation. The project funded by Scientific Research Fund of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital (2022QN38)

    Global, regional, and national incidence of six major immune-mediated inflammatory diseases: findings from the global burden of disease study 2019

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    Global Burden of Cardiovascular Diseases and Risks, 1990-2022

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    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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