Effective refractive error coverage in adults aged 50 years and older - estimates to monitor progress towards the World Health Organisation's 2030 target

Background In 2021, WHO Member States endorsed a global target of a 40-percentage-point increase in effective refractive error coverage (eREC; with a 6/12 visual acuity threshold) by 2030. This study models global and regional estimates of eREC as a baseline for the WHO initiative. Methods The Vision Loss Expert Group analysed data from 565 448 participants of 169 population-based eye surveys conducted since 2000 to calculate eREC (met need/[met need + undermet need + unmet need]). A binary logistic regression model was used to estimate eREC by Global Burden of Disease (GBD) Study super region among adults aged 50 years and older. Findings In 2021, distance eREC was 79·1% (95% CI 72·4–85·0) in the high-income super region; 62·1% (54·7–68·8) in north Africa and Middle East; 49·5% (45·0–54·0) in central Europe, eastern Europe, and central Asia; 40·0% (31·7–48·2) in southeast Asia, east Asia, and Oceania; 34·5% (29·4–40·0) in Latin America and the Caribbean; 9·0% (6·5–12·0) in south Asia; and 5·7% (3·1–9·0) in sub-Saharan Africa. eREC was higher in men and reduced with increasing age. Global distance eREC increased from 2000 to 2021 by 19·0%. Global near vision eREC for 2021 was 20·5% (95% CI 17·8–24·4). Interpretation Over the past 20 years, distance eREC has increased in each super region yet the WHO target will require substantial improvements in quantity and quality of refractive services in particular for near vision impairment

The global prevalence of sexual dysfunction in obese and overweight women: a systematic review and meta-analysis

Background Obesity is a pressing public health risk issue worldwide. Women, in particular, face a higher risk of obesity. Recent research has highlighted the association between obesity and female sexual dysfunction. Therefore, the objective of this study is to investigate the global prevalence of sexual dysfunction in obese and overweight women through a systematic review and meta-analysis. Methods In this study, a systematic search was conducted across electronic databases, including PubMed, Scopus, Web of Science, Embase, ScienceDirect, and Google Scholar. The search aimed to identify studies published between December 2000 and August 2022 that reported metabolic syndrome's impact on female sexual dysfunction. Results The review included nine studies with a sample size of 1508 obese women. The I2 heterogeneity index indicated high heterogeneity (I2: 97.5). As a result, the random effects method was used to analyze the data. Based on this meta-analysis, the prevalence of sexual dysfunction in women with obesity was reported as 49.7% (95%CI: 35.8–63.5). Furthermore, the review comprised five studies involving 1411 overweight women. The I2 heterogeneity test demonstrated high heterogeneity (I2: 96.6). Consequently, the random effects model was used to analyze the results. According to the meta-analysis, the prevalence of sexual dysfunction in overweight women was 26.9% (95% CI: 13.5–46.5). Conclusion Based on the results of this study, it has been reported that being overweight and particularly obese is an important factor affecting women's sexual dysfunction. Therefore, health policymakers must acknowledge the significance of this issue in order to raise awareness in society about its detrimental effect on the female population.</p

The global prevalence of sexual dysfunction in obese and overweight women: a systematic review and meta-analysis

Background Obesity is a pressing public health risk issue worldwide. Women, in particular, face a higher risk of obesity. Recent research has highlighted the association between obesity and female sexual dysfunction. Therefore, the objective of this study is to investigate the global prevalence of sexual dysfunction in obese and overweight women through a systematic review and meta-analysis. Methods In this study, a systematic search was conducted across electronic databases, including PubMed, Scopus, Web of Science, Embase, ScienceDirect, and Google Scholar. The search aimed to identify studies published between December 2000 and August 2022 that reported metabolic syndrome's impact on female sexual dysfunction. Results The review included nine studies with a sample size of 1508 obese women. The I2 heterogeneity index indicated high heterogeneity (I2: 97.5). As a result, the random effects method was used to analyze the data. Based on this meta-analysis, the prevalence of sexual dysfunction in women with obesity was reported as 49.7% (95%CI: 35.8–63.5). Furthermore, the review comprised five studies involving 1411 overweight women. The I2 heterogeneity test demonstrated high heterogeneity (I2: 96.6). Consequently, the random effects model was used to analyze the results. According to the meta-analysis, the prevalence of sexual dysfunction in overweight women was 26.9% (95% CI: 13.5–46.5). Conclusion Based on the results of this study, it has been reported that being overweight and particularly obese is an important factor affecting women's sexual dysfunction. Therefore, health policymakers must acknowledge the significance of this issue in order to raise awareness in society about its detrimental effect on the female population.</p

Using machine learning algorithms to develop a clinical decision-making tool for COVID-19 inpatients

Background: Within the UK, COVID-19 has contributed towards over 103,000 deaths. Although multiple risk factors for COVID-19 have been identified, using this data to improve clinical care has proven challenging. The main aim of this study is to develop a reliable, multivariable predictive model for COVID-19 in-patient outcomes, thus enabling risk-stratification and earlier clinical decision-making. Methods: Anonymised data consisting of 44 independent predictor variables from 355 adults diagnosed with COVID-19, at a UK hospital, was manually extracted from electronic patient records for retrospective, case–control analysis. Primary outcomes included inpatient mortality, required ventilatory support, and duration of inpatient treatment. Pulmonary embolism sequala was the only secondary outcome. After balancing data, key variables were feature selected for each outcome using random forests. Predictive models were then learned and constructed using Bayesian networks. Results: The proposed probabilistic models were able to predict, using feature selected risk factors, the probability of the mentioned outcomes. Overall, our findings demonstrate reliable, multivariable, quantitative predictive models for four outcomes, which utilise readily available clinical information for COVID-19 adult inpatients. Further research is required to externally validate our models and demonstrate their utility as risk stratification and clinical decision-making tools.</p