Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Digital Periphery? A Community Case Study of Digitalization Efforts in Swiss Mountain Regions

Rural economies have undergone major changes in recent years as traditional rural economic sectors declined and shifted. At the same time, digital technologies emerged and rural communities experience profound transformations. In this chapter, we analyze how technological change leads to changing rural economies in a Swiss mountain community. Although Switzerland has one of the highest national coverage of broadband in the world, there is a lack of knowledge regarding the transformation of its rural economy due to digitalization. The community case study’s 46 qualitative interviews show that digital connectivity in peripheral mountain communities is experienced differently by various actors. On the one hand, digitalization offers new economic opportunities to larger businesses, larger hotels, schools and health service providers. On the other hand, particularly smaller businesses struggle with the high cost of becoming digital and their owners tend to become more cautious and stressed as competition and price transparencies in the digital economy become intensified. In terms of spatial aspects, we argue that digitalization reduces cognitive distance between core and periphery while physical distance between the urban and the rural still exist