Models Predicting Postpartum Glucose Intolerance Among Women with a History of Gestational Diabetes Mellitus: a Systematic Review.

PURPOSE OF REVIEW: Despite the crucial role that prediction models play in guiding early risk stratification and timely intervention to prevent type 2 diabetes after gestational diabetes mellitus (GDM), their use is not widespread in clinical practice. The purpose of this review is to examine the methodological characteristics and quality of existing prognostic models predicting postpartum glucose intolerance following GDM. RECENT FINDINGS: A systematic review was conducted on relevant risk prediction models, resulting in 15 eligible publications from research groups in various countries. Our review found that traditional statistical models were more common than machine learning models, and only two were assessed to have a low risk of bias. Seven were internally validated, but none were externally validated. Model discrimination and calibration were done in 13 and four studies, respectively. Various predictors were identified, including body mass index, fasting glucose concentration during pregnancy, maternal age, family history of diabetes, biochemical variables, oral glucose tolerance test, use of insulin in pregnancy, postnatal fasting glucose level, genetic risk factors, hemoglobin A1c, and weight. The existing prognostic models for glucose intolerance following GDM have various methodological shortcomings, with only a few models being assessed to have low risk of bias and validated internally. Future research should prioritize the development of robust, high-quality risk prediction models that follow appropriate guidelines, in order to advance this area and improve early risk stratification and intervention for glucose intolerance and type 2 diabetes among women who have had GDM.

Global trends of hand and wrist trauma: a systematic analysis of fracture and digit amputation using the Global Burden of Disease 2017 Study.

BACKGROUND: As global rates of mortality decrease, rates of non-fatal injury have increased, particularly in low Socio-demographic Index (SDI) nations. We hypothesised this global pattern of non-fatal injury would be demonstrated in regard to bony hand and wrist trauma over the 27-year study period. METHODS: The Global Burden of Diseases, Injuries, and Risk Factors Study 2017 was used to estimate prevalence, age-standardised incidence and years lived with disability for hand trauma in 195 countries from 1990 to 2017. Individual injuries included hand and wrist fractures, thumb amputations and non-thumb digit amputations. RESULTS: The global incidence of hand trauma has only modestly decreased since 1990. In 2017, the age-standardised incidence of hand and wrist fractures was 179 per 100 000 (95% uncertainty interval (UI) 146 to 217), whereas the less common injuries of thumb and non-thumb digit amputation were 24 (95% UI 17 to 34) and 56 (95% UI 43 to 74) per 100 000, respectively. Rates of injury vary greatly by region, and improvements have not been equally distributed. The highest burden of hand trauma is currently reported in high SDI countries. However, low-middle and middle SDI countries have increasing rates of hand trauma by as much at 25%. CONCLUSIONS: Certain regions are noted to have high rates of hand trauma over the study period. Low-middle and middle SDI countries, however, have demonstrated increasing rates of fracture and amputation over the last 27 years. This trend is concerning as access to quality and subspecialised surgical hand care is often limiting in these resource-limited regions.

Trends and determinants of mental illness in humanitarian migrants resettled in Australia: Analysis of longitudinal data.

Given the frequent exposure of humanitarian migrants to traumatic or stressful circumstances, there exists a potential predisposition to mental illness. Our objective was to pinpoint the trends and determinants of mental illness among humanitarian migrants resettled in Australia. This study considered five waves of longitudinal data involving humanitarian migrants resettled in Australia. Post-traumatic stress disorder (PTSD) and psychological distress were assessed using PTSD-8 and Kessler-6 screening tools. Through a Generalised Linear Mixed model (GLMM), variables displaying a 95% CI that excluded the value of 1.0 for the odds ratio were identified as associated factors for both PTSD and elevated psychological distress. The selection of multivariable covariates was guided by causal loop diagrams and least absolute shrinkage and selection operators methods. At baseline, there were 2399 humanitarian migrants with 1881 retained and at the fifth yearly wave; the response rate was 78.4%. PTSD prevalence decreased from 33.3% (95% CI: 31.4-35.3) at baseline to 28.3% (95% CI: 26.2-30.5) at year 5. Elevated psychological distress persisted across all waves: 17.1% (95% CI: 15.5-18.6) at baseline and 17.1% (95% CI: 15.3-18.9) at year 5. Across the five waves, 34.0% of humanitarian migrants met screening criteria for mental illness, either PTSD or elevated psychological distress. In the multivariate model, factors associated with PTSD were loneliness (AOR 1.5, 95% CI: 1.3-1.8), discrimination (AOR 1.6: 1.2-2.1), temporary housing contract (AOR 3.7: 2.1-6.7), financial hardship (AOR 2.2:1.4-3.6) and chronic health conditions (AOR 1.3: 1.1-1.5), whereas the associated factors for elevated psychological distress were loneliness (AOR 1.8: 1.5-2.2), discrimination (AOR 1.7: 1.3-2.2) and short-term lease housing (AOR 1.6: 1.0-1.7). The prevalence, persistence and consequential burden of mental illness within this demographic underscore the urgent need for targeted social and healthcare policies. These policies should aim to mitigate modifiable risk factors, thereby alleviating the significant impact of mental health challenges on this population.

Influence of Social Media Use on Practice of COVID-19 Preventive Measures Among Ethiopian Residents: An Online Cross-Sectional Study.

BACKGROUND: Infection with coronavirus disease 2019 (COVID-19) has become a severe public health issue worldwide. A broad amount of information related to the novel coronavirus (COVID-19) pandemic was disseminated by social media in Ethiopia. To date, there is limited evidence on the influence of social media use for COVID-19-related information on COVID-19 preventive practice. Therefore, this study aimed to assess the influence of social media use on the practice of COVID-19 preventive measures in Ethiopia. METHODS: This study used an anonymous Internet-based online cross-sectional survey using Google Forms to collect the data from the respondents from May 15 to June 17, 2020, in Ethiopia. Multivariable logistic regression was used to assess the relationship between social media use as a predictor and COVID-19 preventive practice, after adjusting for socio-demographic and risk perception of COVID-19 variables. The data were analyzed using SPSS version 21. RESULTS: A total of 372 respondents have participated in the study. From 372, a total of 208 (55.9%) respondents in this study were male. Study participants who had good use of social media to get COVID-19-related information were 9.5 times more engaged in COVID-19 preventive practices compared with study participants who had poor use of social media to get COVID-19-related information (adjusted odds ratio [AOR] = 9.59; 95% confidence interval [CI]: 5.70-16.13). Also, study participants who had a high-risk perception of COVID-19 were 2.6 times more engaged in COVID-19 practices compared with study participants who had a low-risk perception of COVID-19 (AOR = 2.63; 95% CI: 1.58-4.38). Study participants who were students at the time of this study were 4 times more likely to show an adequate COVID-19 preventive practice score compared with those who had another occupational status (AOR = 4.07; 95% CI: 1.66-9.98). CONCLUSIONS: Our results show that the use of social media networks can have a positive effect on the practice of preventive measures and public safety against COVID-19; high-risk perception contributed to preventive activities against COVID-19. Social networking platforms can be used by public health agencies as an important method to raise public health understanding by disseminating concise messages to targeted audiences.