A comprehensive standardised data definitions set for acute coronary syndrome research in emergency departments in Australasia

Patients with chest discomfort or other symptoms suggestive of acute coronary syndrome are one of the most common categories seen in many Emergency Departments (EDs). Although the recognition of patients at high risk of acute coronary syndrome has improved steadily, identifying the majority of chest pain presentations who fall into the low-risk group remains a challenge. Research in this area needs to be transparent, robust, applicable to all hospitals from large tertiary centres to rural and remote sites, and to allow direct comparison between different studies with minimum patient spectrum bias. A standardized approach to the research framework using a common language for data definitions must be adopted to achieve this. The aim was to create a common framework for a standardized data definitions set that would allow maximum value when extrapolating research findings both within Australasian ED practice, and across similar populations worldwide. Therefore a comprehensive data definitions set for the investigation of non-traumatic chest pain patients with possible acute coronary syndrome was developed, specifically for use in the ED setting. This standardized data definitions set will facilitate‘knowledge translation’ by allowing extrapolation of useful findings into the real-life practice of emergency medicine

2-Hour Accelerated Diagnostic Protocol to Assess Patients With Chest Pain Symptoms Using Contemporary Troponins as the Only Biomarker

Objectives The purpose of this study was to determine whether a new accelerated diagnostic protocol (ADP) for possible cardiac chest pain could identify low-risk patients suitable for early discharge (with follow-up shortly after discharge). Background Patients presenting with possible acute coronary syndrome (ACS), who have a low short-term risk of adverse cardiac events may be suitable for early discharge and shorter hospital stays. Methods This prospective observational study tested an ADP that included pre-test probability scoring by the Thrombolysis In Myocardial Infarction (TIMI) score, electrocardiography, and 0 + 2 h values of laboratory troponin I as the sole biomarker. Patients presenting with chest pain due to suspected ACS were included. The primary endpoint was major adverse cardiac event (MACE) within 30 days. Results Of 1,975 patients, 302 (15.3%) had a MACE. The ADP classified 392 patients (20%) as low risk. One (0.25%) of these patients had a MACE, giving the ADP a sensitivity of 99.7% (95% confidence interval [CI]: 98.1% to 99.9%), negative predictive value of 99.7% (95% CI: 98.6% to 100.0%), specificity of 23.4% (95% CI: 21.4% to 25.4%), and positive predictive value of 19.0% (95% CI: 17.2% to 21.0%). Many ADP negative patients had further investigations (74.1%), and therapeutic (18.3%) or procedural (2.0%) interventions during the initial hospital attendance and/or 30-day follow-up. Conclusions Using the ADP, a large group of patients was successfully identified as at low short-term risk of a MACE and therefore suitable for rapid discharge from the emergency department with early follow-up. This approach could decrease the observation period required for some patients with chest pain. (An observational study of the diagnostic utility of an accelerated diagnostic protocol using contemporary central laboratory cardiac troponin in the assessment of patients presenting to two Australasian hospitals with chest pain of possible cardiac origin; ACTRN12611001069943

Validation of the shared decision-making model in the context of a patient presenting to the emergency department with chest pain of possible cardiac origin

The intention of this thesis was to investigate the feasibility of clinical shared decision-making. If physicians are to contribute to a shared decision process, they will need to be able to communicate unbiased information to their patients clearly. Thus, physicians need to provide some form of quantitative risk estimate. Physicians estimated the probability that a patient presenting with chest pain had Acute Coronary Syndrome. The patients details were then entered into a structured clinical risk calculator and the results were compared. It was found that although both methods held comparable predictive power, the physician’s estimate did not correlate well with the structured estimate. This suggests that physicians do not utilise a quantitative risk estimate. It then found that the correlation between risk estimates increased as further investigations were performed. However, neither estimation method could predict these test results. It was hypothesised that physicians utilise a dichotomous decision process. Thus, as positive and negative test results erode the intermediate risk group and populate the high and low risk groups, the correlation between methods increases. It was concluded that a dichotomous decision process would provide a considerable hurdle to the shared decision-making process, as it would limit the communicability of the physicians thought process. However, the potential benefits of shared decision-making encourage future researchers to find a way to overcome this hurdle

Validation of the shared decision-making model in the context of a patient presenting to the emergency department with chest pain of possible cardiac origin.

The intention of this thesis was to investigate the feasibility of clinical shared decision-making. If physicians are to contribute to a shared decision process, they will need to be able to communicate unbiased information to their patients clearly. Thus, physicians need to provide some form of quantitative risk estimate. Physicians estimated the probability that a patient presenting with chest pain had Acute Coronary Syndrome. The patients details were then entered into a structured clinical risk calculator and the results were compared. It was found that although both methods held comparable predictive power, the physician’s estimate did not correlate well with the structured estimate. This suggests that physicians do not utilise a quantitative risk estimate. It then found that the correlation between risk estimates increased as further investigations were performed. However, neither estimation method could predict these test results. It was hypothesised that physicians utilise a dichotomous decision process. Thus, as positive and negative test results erode the intermediate risk group and populate the high and low risk groups, the correlation between methods increases. It was concluded that a dichotomous decision process would provide a considerable hurdle to the shared decision-making process, as it would limit the communicability of the physicians thought process. However, the potential benefits of shared decision-making encourage future researchers to find a way to overcome this hurdle

Delirium risk in non-surgical patients: systematic review of predictive tools

Delirium is a common, serious condition associated with poor hospital outcomes. Guidelines recommend screening for delirium risk to target diagnostic and/or prevention strategies. This study critically reviews multicomponent delirium risk prediction tools in adult non-surgical inpatients.Systematic review of studies incorporating at least two clinical factors in a multicomponent tool predicting risk of delirium during hospital admission. Derivation and validation studies were included. Study design, risk factors and tool performance were extracted and tabulated, and study quality was assessed by CHARMS criteria.PubMed, Embase, PsycINFO, and Cumulative Index to Nursing Health Literature (CINAHL) to 11 March 2018.22 derivation studies enrolling 38,874 participants (9 with a validation component) and 4 additional validation studies were identified, from a range of ward types. All studies had at least moderate risk of bias. Older age and cognitive, functional and sensory impairment were important predisposing factors. Precipitating risk factors included infection, illness severity, renal and electrolyte disturbances. Tools mostly did not differentiate between predisposing and precipitating risk factors mathematically or conceptually Most tools showed fair to good discrimination, and identified more than half of older inpatients at risk.Several validated delirium risk prediction tools can identify patients at increased risk of delirium, but do not provide clear advice for clinical application. Most recommended cut-points are sensitive but have low specificity. Implementation studies demonstrating how risk screening can better direct clinical interventions in specific clinical settings are needed to define the potential value of these tools