An audit and feedback intervention for reducing antibiotic prescribing in general dental practice:the RAPiD Cluster Randomised Controlled Trial

Acknowledgments: We thank the TRiaDS Research Methodology Group, including Irene Black, Debbie Bonetti, Heather Cassie, Martin Eccles, Sandra Eldridge, Jill J. Francis, Jeremy M. Grimshaw, Lorna Macpherson, Lorna McKee, Susan Michie, Nigel Pitts, Derek Richards, Douglas Stirling, Colin Tilley, Carole Torgerson, Shaun Treweek, Luke Vale, and Alan Walker for their guidance and contribution to the design and development of the study. We also thank Maria Prior for overseeing the running of the study, drafting of the published protocol, and her contribution to the design and analysis of the process evaluation. Thanks are also extended to Jill Farnham, Jenny Eades, Sarah Blackburn, and Lorna Barnsley for providing invaluable administrative support for this study. The views expressed in this article are those of the authors and may not reflect those of the funder. Funding: This study was conducted as part of the TRiaDS programme of implementation research which is funded by NHS Education for Scotland (NES). The Health Services Research Unit which is funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates supported the study. The funder had no influence over the design, conduct, analysis and write up of the study. Data Availability: Researchers can request to access the data from the Information Services Division of NHS National Services Scotland http://www.isdscotland.org/. Some restrictions may apply for the protection of privacy and appropriate usage of the data.Peer reviewedPublisher PD

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