Proceedings, 10th Queensland Weed Symposium : 'Celebrating 20 years : managing weeds in a climate of change', 26-29 July 2009, Capricorn Resort, Yeppoon, Queensland

Proceedings of the 10th Queensland Weed Symposium, 26-29 July 2009, Capricorn Resort, Yeppoon, Queensland

Acknowledgement to reviewers of Informatics in 2018

Rigorous peer-review is the corner-stone of high-quality academic publishing. The editorial team greatly appreciates the reviewers who contributed their knowledge and expertise to the journal’s editorial process over the past 12 months. In 2018, a total of 43 papers were published in the journal, with a median time to first decision of 24 days and a median time to publication of 68 days

Derivation and validation of a universal vital assessment (UVA) score: A tool for predicting mortality in adult hospitalised patients in Sub-Saharan Africa

Background Critical illness is a leading cause of morbidity and mortality in Sub-Saharan Africa (SSA). Identifying patients with the highest risk of death could help with resource allocation and clinical decision making. Accordingly, we derived and validated a universal vital assessment (UVA) score for use in SSA. Methods We pooled data from hospital-based cohort studies conducted in six countries in SSA spanning the years 2009–2015. We derived and internally validated a UVA score using decision trees and linear regression and compared its performance with the modified early warning score (MEWS) and the quick sepsis-related organ failure assessment (qSOFA) score. results Of 5573 patients included in the analysis, 2829 (50.8%) were female, the median (IQR) age was 36 (27–49) years, 2122 (38.1%) were HIV-infected and 996 (17.3%) died in-hospital. The UVA score included points for temperature, heart and respiratory rates, systolic blood pressure, oxygen saturation, Glasgow Coma Scale score and HIV serostatus, and had an area under the receiver operating characteristic curve (AUC) of 0.77 (95% CI 0.75 to 0.79), which outperformed MEWS (AUC 0.70 (95% CI 0.67 to 0.71)) and qSOFA (AUC 0.69 (95% CI 0.67 to 0.72)). conclusion We identified predictors of in-hospital mortality irrespective of the underlying condition(s) in a large population of hospitalised patients in SSA and derived and internally validated a UVA score to assist clinicians in risk-stratifying patients for in-hospital mortality. The UVA score could help improve patient triage in resource-limited environments and serve as a standard for mortality risk in future studies