6 research outputs found

    Global burden of peripheral artery disease and its risk factors, 1990–2019 : a systematic analysis for the Global Burden of Disease Study 2019

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    peripheral artery disease were modelled using the Global Burden of Disease, Injuries, and Risk Factors Study (GBD) 2019 database. Prevalence, disability-adjusted life years (DALYs), and mortality estimates of peripheral artery disease were extracted from GBD 2019. Total DALYs and age-standardised DALY rate of peripheral artery disease attributed to modifiable risk factors were also assessed. Findings In 2019, the number of people aged 40 years and older with peripheral artery disease was 113 million (95% uncertainty interval [UI] 99·2–128·4), with a global prevalence of 1·52% (95% UI 1·33–1·72), of which 42·6% was in countries with low to middle Socio-demographic Index (SDI). The global prevalence of peripheral artery disease was higher in older people, (14·91% [12·41–17·87] in those aged 80–84 years), and was generally higher in females than in males. Globally, the total number of DALYs attributable to modifiable risk factors in 2019 accounted for 69·4% (64·2–74·3) of total peripheral artery disease DALYs. The prevalence of peripheral artery disease was highest in countries with high SDI and lowest in countries with low SDI, whereas DALY and mortality rates showed U-shaped curves, with the highest burden in the high and low SDI quintiles. Interpretation The total number of people with peripheral artery disease has increased globally from 1990 to 2019. Despite the lower prevalence of peripheral artery disease in males and low-income countries, these groups showed similar DALY rates to females and higher-income countries, highlighting disproportionate burden in these groups. Modifiable risk factors were responsible for around 70% of the global peripheral artery disease burden. Public measures could mitigate the burden of peripheral artery disease by modifying risk factors

    Effect of sodium–glucose cotransporter 2 inhibitors on insulin resistance; a systematic review and meta-analysis

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    Aim Recent studies have indicated that Sodium-GLucose co-Transporter 2 Inhibitors (SGLT2Is) may increase insulin sensitivity (IS); however, these results are heterogeneous and need to be systematically assessed. Method We searched MEDLINE/PubMed, Embase, Web of Science, Scopus, Cochrane Library, Ovid, and ProQuest using a predefined search query. Randomized clinical trials on SGLT2Is with a passive control group or metformin controlled group were included. Risk of bias assessment was performed using the Cochrane risk of bias assessment tool. Meta-analysis was performed separately on studies with type 2 diabetes mellitus (T2DM) population and studies with non-T2DM population and also for passive- and active-controlled studies using standardized mean difference (SMD) as the measure of the effect size. Subgroup analysis was performed according to different types of SGLT2Is. Meta-regression analysis was performed according to the dose and duration of intervention. Results Twenty-two studies (6 on non-T2DM population) with a total of 1421 (243 non-T2DM) patients were included. Six studies (3 on T2DM and 3 on non-T2DM) were controlled by metformin, and others were passively controlled. SGLT2Is could significantly increase IS in T2DM patients (SMD = 0.72 [0.32-1.12]). SGLT2Is could reduce insulin resistance in non-T2DM population, but this was not significant. SGLT2Is were not inferior to metformin in reducing insulin resistance. Subgroup analysis indicated that dapagliflozin could significantly increase IS, but empagliflozin was not associated with significant improvement in IS. Meta-regression analysis indicated no effect for dose but duration of SGLT2I administration on IS. Conclusion SGLT2Is, particularly dapagliflozin, could increase IS. These results need to be consolidated by further studies

    Self-Reported safety of the BBIBP-CorV (Sinopharm) COVID-19 vaccine among Iranian people with multiple sclerosis

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    To affirm the short-term safety of the BBIBP-CorV (Sinopharm) COVID-19 vaccine among people with multiple sclerosis (pwMS), 517 vaccinated and 174 unvaccinated pwMS were interviewed. 16.2% of the vaccinated pwMS reported at least one neurological symptom in their respective vaccine-related at-risk periods (ARP) – a period from the first dose until two weeks after the second dose of the vaccine. In a multivariable logistic regression model, the presence of comorbidities (P = 0.01), use of natalizumab (P = 0.03), and experiencing post-vaccination myalgia (P < 0.01) predicted the development of post-vaccination neurological symptoms. One MS relapse, one COVID-19 contraction, and one ulcerative colitis flare after the first dose, and four MS relapses after the second dose of the vaccine were the only reported serious adverse events during the ARPs. To show if the vaccine provoked MS relapses, we compared the relapse rate of vaccinated pwMS in the vaccine-related ARP with the annualized relapse rate of unvaccinated pwMS in the prior year—a measure of baseline MS relapsing activity in the respective time—using a multivariable Poisson regression model accounting for possible confounders, which failed to show any statistically significant increase (P = 0.78). Hence, subject to replication—as the vaccinated and unvaccinated pwMS differed in baseline characteristics—the BBIBP-CorV vaccine does not seem to affect short-term MS activity. Furthermore, as 83.33% of the unvaccinated pwMS reported fear of possible adverse events to be the reason of their vaccination hesitancy, provision of evidence-based consultations to pwMS is encouraged. Limitations of our study briefly included lack of data for self-controlled analysis of relapse rates, possible presence of recall bias, and lack of on-site validations regarding the clinical outcomes due to the remote nature

    Global mortality associated with 33 bacterial pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019

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    Background: Reducing the burden of death due to infection is an urgent global public health priority. Previous studies have estimated the number of deaths associated with drug-resistant infections and sepsis and found that infections remain a leading cause of death globally. Understanding the global burden of common bacterial pathogens (both susceptible and resistant to antimicrobials) is essential to identify the greatest threats to public health. To our knowledge, this is the first study to present global comprehensive estimates of deaths associated with 33 bacterial pathogens across 11 major infectious syndromes. Methods: We estimated deaths associated with 33 bacterial genera or species across 11 infectious syndromes in 2019 using methods from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, in addition to a subset of the input data described in the Global Burden of Antimicrobial Resistance 2019 study. This study included 343 million individual records or isolates covering 11 361 study-location-years. We used three modelling steps to estimate the number of deaths associated with each pathogen: deaths in which infection had a role, the fraction of deaths due to infection that are attributable to a given infectious syndrome, and the fraction of deaths due to an infectious syndrome that are attributable to a given pathogen. Estimates were produced for all ages and for males and females across 204 countries and territories in 2019. 95% uncertainty intervals (UIs) were calculated for final estimates of deaths and infections associated with the 33 bacterial pathogens following standard GBD methods by taking the 2·5th and 97·5th percentiles across 1000 posterior draws for each quantity of interest. Findings: From an estimated 13·7 million (95% UI 10·9–17·1) infection-related deaths in 2019, there were 7·7 million deaths (5·7–10·2) associated with the 33 bacterial pathogens (both resistant and susceptible to antimicrobials) across the 11 infectious syndromes estimated in this study. We estimated deaths associated with the 33 bacterial pathogens to comprise 13·6% (10·2–18·1) of all global deaths and 56·2% (52·1–60·1) of all sepsis-related deaths in 2019. Five leading pathogens—Staphylococcus aureus, Escherichia coli, Streptococcus pneumoniae, Klebsiella pneumoniae, and Pseudomonas aeruginosa—were responsible for 54·9% (52·9–56·9) of deaths among the investigated bacteria. The deadliest infectious syndromes and pathogens varied by location and age. The age-standardised mortality rate associated with these bacterial pathogens was highest in the sub-Saharan Africa super-region, with 230 deaths (185–285) per 100 000 population, and lowest in the high-income super-region, with 52·2 deaths (37·4–71·5) per 100 000 population. S aureus was the leading bacterial cause of death in 135 countries and was also associated with the most deaths in individuals older than 15 years, globally. Among children younger than 5 years, S pneumoniae was the pathogen associated with the most deaths. In 2019, more than 6 million deaths occurred as a result of three bacterial infectious syndromes, with lower respiratory infections and bloodstream infections each causing more than 2 million deaths and peritoneal and intra-abdominal infections causing more than 1 million deaths. Interpretation: The 33 bacterial pathogens that we investigated in this study are a substantial source of health loss globally, with considerable variation in their distribution across infectious syndromes and locations. Compared with GBD Level 3 underlying causes of death, deaths associated with these bacteria would rank as the second leading cause of death globally in 2019; hence, they should be considered an urgent priority for intervention within the global health community. Strategies to address the burden of bacterial infections include infection prevention, optimised use of antibiotics, improved capacity for microbiological analysis, vaccine development, and improved and more pervasive use of available vaccines. These estimates can be used to help set priorities for vaccine need, demand, and development. Funding: Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care, using UK aid funding managed by the Fleming Fund
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