Short-term outcomes of patients with neovascular exudative AMD: the effect of COVID-19 pandemic

Graefe's Archive for Clinical and Experimental Ophthalmology - To estimate the impact of delayed care during the coronavirus disease 2019 (COVID-19) pandemic on the outcomes of patients with...     

Endoscopic ultrasonography and small‐bowel endoscopy: Present and future

Over the last decade, impressive technological advances have occurred in ultrasonography and small‐bowel endoscopy. Nowadays, endoscopic ultrasonography is an essential diagnostic tool and a therapeutic weapon for pancreatobiliary disorders. Capsule endoscopy and device‐assisted enteroscopy have quickly become the reference standard for the diagnosis of small‐bowel luminal diseases, thereby leading to radical changes in diagnostic and therapeutic pathways. We herein provide an up‐to‐date overview of the latest advances in endoscopic ultrasonography and small‐bowel endoscopy, focusing on the emerging paradigms and technological innovations that might improve clinical practice in the near future.     

Anthropometric and reproductive factors and risk of esophageal and gastric cancer by subtype and subsite: Results from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort

Obesity has been associated with upper gastrointestinal cancers; however, there are limited prospective data on associations by subtype/subsite. Obesity can impact hormonal factors, which have been hypothesized to play a role in these cancers. We investigated anthropometric and reproductive factors in relation to esophageal and gastric cancer by subtype and subsite for 476,160 participants from the European Prospective Investigation into Cancer and Nutrition cohort. Multivariable hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox models. During a mean follow-up of 14 years, 220 esophageal adenocarcinomas (EA), 195 esophageal squamous cell carcinomas, 243 gastric cardia (GC) and 373 gastric noncardia (GNC) cancers were diagnosed. Body mass index (BMI) was associated with EA in men (BMI ≥30 vs. 18.5–25 kg/m²: HR = 1.94, 95% CI: 1.25–3.03) and women (HR = 2.66, 95% CI: 1.15–6.19); however, adjustment for waist-to-hip ratio (WHR) attenuated these associations. After mutual adjustment for BMI and HC, respectively, WHR and waist circumference (WC) were associated with EA in men (HR = 3.47, 95% CI: 1.99–6.06 for WHR >0.96 vs. <0.91; HR = 2.67, 95% CI: 1.52–4.72 for WC >98 vs. <90 cm) and women (HR = 4.40, 95% CI: 1.35–14.33 for WHR >0.82 vs. <0.76; HR = 5.67, 95% CI: 1.76–18.26 for WC >84 vs. <74 cm). WHR was also positively associated with GC in women, and WC was positively associated with GC in men. Inverse associations were observed between parity and EA (HR = 0.38, 95% CI: 0.14–0.99; >2 vs. 0) and age at first pregnancy and GNC (HR = 0.54, 95% CI: 0.32–0.91; >26 vs. <22 years); whereas bilateral ovariectomy was positively associated with GNC (HR = 1.87, 95% CI: 1.04–3.36). These findings support a role for hormonal pathways in upper gastrointestinal cancers.     

Impact of new technologies on diabetes care

Technologies for diabetes management, such as continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) systems, have improved remarkably over the last decades. These developments are impacting the capacity to achieve recommended hemoglobin A1c levels and assisting in preventing the development and progression of micro- and macro vascular complications. While improvements in metabolic control and decreases in risk of severe and moderate hypoglycemia have been described with use of these technologies, large epidemiological international studies show that many patients are still unable to meet their glycemic goals, even when these technologies are used. This editorial will review the impact of technology on glycemic control, hypoglycemia and quality of life in children and youth with type 1 diabetes. Technologies reviewed include CSII, CGM systems and sensor-augmented insulin pumps. In addition, the usefulness of advanced functions such as bolus profiles, bolus calculators and threshold-suspend features will be also discussed. Moreover, the current editorial will explore the challenges of using these technologies. Indeed, despite the evidence currently available of the potential benefits of using advanced technologies in diabetes management, many patients still report barriers to using them. Finally this article will highlight the importance of future studies tailored toward overcome these barriers to optimizing glycemic control and avoiding severe hypoglycemia.     

Patterns in metabolite profile are associated with risk of more aggressive prostate cancer: A prospective study of 3,057 matched case–control sets from EPIC

Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case–control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR_1SD) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR_1SD = 0.77, 95% confidence interval 0.66–0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR_1SD = 0.72, 0.57–0.90), or lysophosphatidylcholines (OR_1SD = 0.81, 0.69–0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR_1SD = 0.77, 0.61–0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer.