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

Crisp-dm/smes: A data analytics methodology for non-profit smes

The exponential increase in information due to technological advances and the development of communications has created the need to make decisions based on the data analysis. This trend has opened the doors to new approaches to data understanding and decision-making. On the one hand, companies need to follow data analytic methodologies to manage large volumes of information with big data tools. On the other hand, there are non-profit small and medium-sized enterprises (SMEs) that make efforts to address data analytics according to their different sources and types. They find challenges such as lack of knowledge in methodological and software tools, which allow timely deployment for decision-making. In this paper, we propose a data analytics methodology for non-profit SMEs. The design of this methodology is based on CRISP-DM as a reference framework, is represented by Software Process Engineering Metamodel (SPEM) and is characterized by being simple, flexible, and low implementation costs. © Springer Nature Singapore Pte Ltd. 2020

Three cases of prune belly syndrome at the Lagos State University Teaching Hospital, Ikeja

Prune belly syndrome (PBS) is a rare congenital disorder affecting 2.5 to 3.8/100,000 live births worldwide. Our objective of this report is to describe clinical manifestation, laboratory, and radiological characteristics of PBS in our patients, to highlight the limitations to offering appropriate patient care due to parents demanding discharge against medical advice and the need to increase the awareness regarding this rare disease. We report three cases; all referred after birth with lax abdominal wall, congenital anomalies of kidney, and urinary tract. One of the patients had an absent right foot. They all had cryptorchidism, and in one, there was deranged renal function. The reported cases had both medical and radiological interventions to varying degrees. They all had an abdominal ultrasound which revealed varying degrees of hydronephrosis, hydroureters, and bladder changes. Voiding cystourethrogram showed vesicoureteric reflux in one of the reported cases. Urinary tract infections were appropriately treated with antibiotics based on sensitivity. PBS management in our setting remains a challenge because of strong cultural beliefs, and high rate of discharge against medical advice. Focus should be on parent education, early diagnosis, and multidisciplinary management approach

Investigating the Social, Political, Economic and Cultural Implications of Data Trading

Part 3: Open Data: Social and Technical AspectsInternational audienceData market initiatives have, by assigning monetary value to data, and connecting the various actors responsible for its efficient production and consumption, far reaching consequences for national economies. The Data Market Austria (DMA) project represents a unique opportunity for Austria to leverage the enormous potential socio-economic benefits accruing from increased trade of data. At the same time, however, a number of key challenges to the successful uptake of the project needs to be considered, and new problems emerging from this new form of digital commercial infrastructure need to be anticipated and addressed. This study aims to examine how the benefits accruing to increased participation in a data-driven ecosystem can be applied to tackle the long-standing socio-cultural challenges and the possible societal and cultural impediments to the successful unfolding out of a data market. Theoretical discussions framed from arguments obtained through a systematic review of academic and scholarly literature are juxtaposed with empirical data obtained from data science experts and DMA project personnel to test whether they stand up to real-world practicalities and to narrow the focus onto the Austria-specific context. Our findings reveal that data is a dual-purpose commodity that has both commercial value and social application. To amplify the benefits accruing from increased data trading, it is vital that a country establishes a sound open data strategy and a balanced regulatory framework for data trading