The Effect of Mild Gestational Diabetes Mellitus Treatment on Adverse Pregnancy Outcomes: A Systemic Review and Meta-Analysis

publishedVersio

A Systematic Review and Meta-Analysis of Male Infertility and the Subsequent Risk of Cancer

Objectives: The primary objective of this systemic review and meta-analysis was to investigate the risk of developing composite outcome of all cancers, regardless of the type of cancer among men with infertility diagnosis compared to fertile counterparts. The secondary objective was to compare the pooled risk of developing individual specific cancers between two groups.Methods: A systematic literature search was performed on the databases of PubMed (including Medline), Scopus, and Web of Science to retrieve observational studies published in English language from 01.01.1990 to 28. 02. 2021. They assessed cancer events in males with an infertility diagnosis compared to controls without infertility. The outcomes of interest were a composite outcome of cancers including all known cancer types, and also specific individual cancers. The fixed/random effects model was used to analyze heterogeneous and non-heterogeneous results. Publication bias was assessed using the Harbord test, Egger test, Begg test, and funnel plot. The pooled odds ratio of cancers was calculated using the DerSimonian and Laird, and inverse variance methods. Studies’ quality and risk of bias were assessed using structured standard tools.Results: We included eight cohort studies involving 168,327 men with the diagnosis of infertility and 2,252,806 men without it. The total number of composite outcome of cancers as well as individual cancers including prostate, testicular and melanoma were 1551, 324, 183 and 121 in the infertile men and 12164, 3875, 849, and 450 in the fertile men, respectively. The pooled OR of the composite outcome of cancers, regardless of the type of cancer, in men with infertility was 1.4 folds higher than those without infertility (pooled OR = 1.43, 95% confidence interval [CI]: 1.25-1.64). Meta-analysis of individual cancers including prostate, testicular and melanoma between two groups was carried out. The pooled ORs of testicular and prostate cancers in men with the diagnosis of infertility were significantly higher than controls without infertility (pooled OR = 1.91, 95% CI: 1.52-2.42 and pooled OR = 1.48, 95% CI: 1.05-2.08, respectively). Additionally, the pooled OR of melanoma in men with infertility was 1.3 folds higher than those without infertility (pooled OR = 1.31, 95% CI: 1.06-1.62).Conclusion: A greater risk of cancers in men with male infertility was found suggesting that the history of male infertility might be an important risk factor for developing cancers in later life. Further well-designed long-term population-based prospective studies, considering all known cancers and their accompanying risk factors should be conducted to support our findings

Perinatal and Neonatal Outcomes in Immigrants From Conflict-Zone Countries : A Systematic Review and Meta-Analysis of Observational Studies

publishedVersio

Importance of IL-1β in SARS-CoV-2 infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) provokes the host immune responses and induces severe respiratory syndrome by overreaction of immune cells. IL-1β is a pro-inflammatory cytokine highly associated with the related inflammation and cytokine storm, and several IL-1β antagonists are being used to treat cytokine release syndrome (CRS). Accordingly, some studies and clinical trials are investigating the effects of IL-1β antagonists for controlling Coronavirus disease 2019 (COVID-19) associated CRS. Here, we will review any interaction and association between IL-1β and SARS-CoV-2 infection

Prevalence of preterm birth in Scandinavian countries : a systematic review and meta-analysis

publishedVersio

Adverse Pregnancy Outcomes and International Immigration Status: A Systematic Review and Meta-analysis

publishedVersio

A Systematic Review and Meta-Analysis of the Risk of Stillbirth, Perinatal and Neonatal Mortality in Immigrant Women

publishedVersio

Association of glutathione S-transferase polymorphisms with the severity of mustard lung

Introduction: Glutathione S-transferase (GST) is one of the major detoxifiers in alveoli. Polymorphism in GST genes can influence the ability of individuals to suppress oxidative stress and inflammation. The present study was aimed to explore the hypothesis that the genetic polymorphisms of GST T1, M1 and P1 are associated with the severity of the mustard lung in the sulfur mustard-exposed individuals. Methods: Blood samples were taken from 185 sulfur mustard-exposed and 57 unexposed subjects. According to the stage of the mustard lung, sulfur mustard-exposed patients were categorized in the mild/moderate and severe/very severe groups. A multiplex PCR method was conducted to identify GSTM1 and GSTT1 null genotypes. To determine the polymorphisms of GSTP1 in exon 5 (Ile105Val) and exon 6 (Ala114Val), RFLP-PCR method was performed. Results: The frequency of GSTM1 homozygous deletion was significantly higher in the severe/very severe patients compared with the mild/moderate subjects (66.3% vs. 48%, P = 0.013). The GSTM1 null genotype was associated with the severity of mustard lung (adjusted odds ratio [OR], 2.257; 95% CI, 1.219-4.180). There was no significant association between GSTT1 and GSTP1 polymorphisms with the severity of the mustard lung. Conclusion: The different distribution of GSTM1 null genotype in severe/very severe and mild/moderate groups indicated that the severity of the mustard lung might be associated with the genetic polymorphism(s)

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

BACKGROUND Regular, 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. METHODS The 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. FINDINGS The 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. INTERPRETATION Long-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. FUNDING Bill & Melinda Gates Foundation