Emergency medicine journal : EMJ
-
The aim of this study was to explore the potential of ambulance call-out data in understanding violence to inform about prevention activity. ⋯ Ambulance call-out data can provide a wealth of information to understand violence and subsequently inform about violence prevention and response activity. Ambulance services and staff could play a key role in preventing violence through sharing data and identifying and supporting victims.
-
The original Manchester Acute Coronary Syndromes model (MACS) 'rules in' and 'rules out' acute coronary syndromes (ACS) using high sensitivity cardiac troponin T (hs-cTnT) and heart-type fatty acid binding protein (H-FABP) measured at admission. The latter is not always available. We aimed to refine and validate MACS as Troponin-only Manchester Acute Coronary Syndromes (T-MACS), cutting down the biomarkers to just hs-cTnT. ⋯ T-MACS could 'rule out' ACS in 40% of patients, while 'ruling in' 5% at highest risk using a single hs-cTnT measurement on arrival. As a clinical decision aid, T-MACS could therefore help to conserve healthcare resources.
-
The paper by Body et al is concerned with the evaluation of decision aids, which can be used to identify potential acute coronary syndromes (ACS) in the ED. The authors previously developed the Manchester Acute Coronary Syndromes model (MACS) decision aid, which uses several clinical variables and two biomarkers to 'rule in' and 'rule out' ACS. ⋯ Decision aids (as well as other types of 'diagnostic tests') are often evaluated in terms of diagnostic testing parameters such as the area under the receiver operating characteristic (ROC) curve, sensitivity and specificity. In this article, we explain how the ROC analysis is conducted and why it is an essential step towards developing a test with the desirable levels of sensitivity and specificity.
-
In Reunion Island, alcohol is the most tried out psychoactive substance. To our knowledge, few indicators measuring the health burden of alcohol use exist on the island. In this context, an exploratory analysis based on syndromic surveillance data was implemented in order to describe the emergency department (ED) visits for alcohol intoxication (AI) and factors associated with their variations. ⋯ There was a significant increase in ED visits for AI during days of benefits payday, weekends and publics holidays. This study demonstrated the interest of syndromic surveillance to monitor non-infectious diseases. Time-series models showed a robust association between ED visits for AI and several factors.