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

Predicting serious complications in patients with cancer and pulmonary embolism using decision tree modelling: the EPIPHANY Index

Our objective was to develop a prognostic stratification tool that enables patients with cancer and pulmonary embolism (PE), whether incidental or symptomatic, to be classified according to the risk of serious complications within 15 days. The sample comprised cases from a national registry of pulmonary thromboembolism in patients with cancer (1075 patients from 14 Spanish centres). Diagnosis was incidental in 53.5% of the events in this registry. The Exhaustive CHAID analysis was applied with 10-fold cross-validation to predict development of serious complications following PE diagnosis. About 208 patients (19.3%, 95% confidence interval (CI), 17.1-21.8%) developed a serious complication after PE diagnosis. The 15-day mortality rate was 10.1%, (95% CI, 8.4-12.1%). The decision tree detected six explanatory covariates: Hestia-like clinical decision rule (any risk criterion present vs none), Eastern Cooperative Group performance scale (ECOG-PS; We have developed and internally validated a prognostic index to predict serious complications with the potential to impact decision-making in patients with cancer and PE

Neurological Adverse Effects Attributable to β-Lactam Antibiotics: A Literature Review

International audienc