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

The effect of organically derived fertilisers on early growth of Pinot noir cuttings under glasshouse conditions

This study examined the effects of organically-derived plant growth promoters (PGPs) on vegetative growth of Pinot noir cuttings under glasshouse conditions for 8 weeks. Solutions of 10 products were applied four times, 2 weeks apart, as a soil drench. In standard potting mix, none of the products caused significant increases in vegetative growth. In low-nutrient potting mix, three products (Synerlogic, Actavize, Just Fish) increased aspects of growth, such as leaf number, shoot length and shoot and root dry weight. These products were relatively high in NPK, and therefore cutting growth was positively correlated to concentrations of NPK in the added solutions. The results imply that addition of PGPs does not by default enhance growth of grape cuttings, and that the mechanism of growth enhancement appears to be simple nutrient provision, rather than by a more complex physiological route involving plant hormones or hormone mimics

Automatic drought stress detection in grapevines without using conventional threshold values

Aims : Because the water status of grapevines strongly affects the quality of the grapes and resulting wine, automated and early drought stress detection is important. Plant measurements are very promising for detecting drought stress, but strongly depend on microclimatic changes. Therefore, conventional stress detection methods require threshold values which define when plants start sensing drought stress. There is however no unique method to define these values. In this study, we propose two techniques that overcome this limitation. Methods : Two statistical methods were used to automatically distinguish between drought and microclimate effects, based on a short preceding full-irrigated period to extract plant behaviour under normal conditions: Unfold Principal Component Analysis (UPCA) and Functional Unfold Principal Component Analysis (FUPCA). Both techniques aimed at detecting when measured sap flow rate or stem diameter variations in grapevine deviated from their normal behaviour due to drought stress. Results : The models based on sap flow rate had some difficulties to detect stress on days with low atmospheric demands, while those based on stem diameter variations did not show this limitation, but ceased detecting stress when the stem diameter levelled off after a period of severe shrinkage. Nevertheless, stress was successfully detected with both approaches days before visible symptoms appeared. Conclusions : UPCA and FUPCA based on plant indicators are therefore very promising for early stress detection