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Background: Critically ill patients are more likely to survive intensive care than ever before due to advances in treatment. However, a proportion subsequently experiences post-intensive care syndrome (PICS) incurring substantial personal, social, and economic costs. PICS is a debilitating set of physical, psychological, and cognitive sequelae but the size and characteristics of the affected population have been difficult to describe, impeding progress in intensive care rehabilitation. Aims and objectives: The aim of this protocol is to describe recovery after admission to intensive care unit (ICU) and the predictors, correlates, and patient-reported outcomes for those experiencing PICS. The study will support the development of screening, diagnostic, and outcome measures to improve post-ICU recovery. Design: A prospective, multi-site observational study in three ICUs in Brisbane, Australia. Following consent, data will be collected from clinical records and using validated self-report instruments from 300 patients, followed up at 6 weeks and 6 months post ICU discharge. Methods: TOPIC is a prospective, multi-site observational study using self-report and clinical data on risk factors, including comorbidities, and outcomes. Data will be collected with consent from hospital records and participants 6 weeks and 6months post ICU discharge. Results: The main outcome measures will be self-reported physical, cognitive, and psychological function 6 weeks and 6 months post-ICU discharge. Relevance to Clinical Practice: This protocol provides a methodological framework to measure recovery and understand PICS. Data analysis will describe characteristics associated with recovery and PICS. The subsequent prediction and screening tools developed then aim to improve the effectiveness of post-ICU prevention and rehabilitation through more targeted screening and prediction and found a program of research developing a more tailored approach to PICS.

The purpose of this study is to establish the diagnostic sensitivity of Endothelin-1 for risk stratification and screening of clinical vasospasm after subarachnoid hemorrhage. This is a multicentre, observational study, correlating daily blood Endothelin-1 with clinical variables. Binary logistic regression used to examine if Endothelin-1 levels could be used to predict clinical vasospasm. Bivariate modelling used to explore associations between patient characteristics and vasospasm. A Receiver Operating Curve used to explore cut-off values for Endothelin-1. Sensitivity and specificity was used to validate the cut-point found in the pilot study. A total of 96 patients were enrolled over two years. Median Endothelin-1 was higher for patients who experienced clinical vasospasm except for day-5, where median endothelin for patients without vasospasm was higher (3.6 IQR = 5.3), compared to patients with vasospasm (3.3 IQR = 8.5) although differences were not significant. The Receiver Operating Curve analysis confirmed that day-5 Endothelin-1 was not a good indicator of vasospasm, with an area under the curve of 0.506 (95% CI: 0.350-0.663, p = 0.938). The levels of Endothelin-1 in blood do not discriminate patients who may develop symptomatic vasospasm. The high variability in Endothelin-1 levels, aligns with the pathophysiological variability of most biomarkers, decreasing their ability to predict a clinical event.

Background: While the impact of the intensive care environment on patients’ experiences and outcomes has been extensively studied, relatively little research has examined the impact on clinicians and their provision of care in the intensive care unit (ICU). Understanding staff experience and views about the environment is needed to optimise the ICU environment, patient outcomes and staff wellbeing. Objective: The objective of this study was to inform design of an optimised intensive care bedspace by describing clinicians’ views about the current environment, including experience, impact on performance of clinical duties, and experience and outcomes of patients and family members. Methods: A pragmatic, qualitative descriptive study was conducted, with data collected in focus groups and interviews with 30 intensive care clinicians at a large cardiothoracic specialist hospital and analysed using the framework approach. Results: Participants acknowledged that the busy and noisy ICU provided a suboptimal healing environment for patients, was confronting for visiting families and exposed clinicians to risk of psychological injury. The bedspace, described as small and cluttered, hindered provision of clinical care of various kinds and contributed to an increased risk of staff physical injuries. Participants noted that the bland, sterile environment, devoid of natural light and views of the outside world, negatively affected both staff and patients’ mood and motivation. Aware of the potential benefits of natural light, cognitive stimulation and visually appealing environments for patients and families, clinicians were frustrated by their inability to personalise the bedspace. Some participants, while acknowledging the importance of family contact for patients, were concerned about the impact of visitors on care delivery, particularly within already crowded bedspaces, suggesting restrictions on visiting. Conclusions: Intensive care clinicians perceive that the current int

Introduction: Delirium, a common complication of an intensive care unit (ICU) admission, is inconsistently diagnosed by clinicians. Current screening tools require specialist expertise and/or training. Some are time-consuming to administer, and reliability in routine clinical practice is questionable. An innovative app designed to enable efficient and sensitive screening for delirium without specialist training (eDIS-ICU) has recently been described. This pilot study compared the eDIS-ICU against the reference standard expert assessment using DSM-V (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition) criteria and the Confusion Assessment Method for the ICU (CAM-ICU). Methods: In this prospective, single-centre pilot study, a convenience sample of 29 ICU patients were recruited at a tertiary referral hospital between November 2018 and August 2019. After obtaining written consent, demographic and clinical data were collected, and the patients were screened for delirium using eDIS-ICU and CAM-ICU by two clinician researchers in random order. The patients were also assessed for presence of delirium independently by an expert clinician using a structured interview to diagnose as per DSM-V criteria. The results of screening and diagnosis were tabulated to allow comparison of screening tools against diagnosis; sensitivity and specificity of the tools were calculated. Results: Seven participants were diagnosed with delirium as per DSM-V criteria. The eDIS-ICU tool correctly identified six of these participants compared with two identified by CAM-ICU. The sensitivity of the eDIS-ICU tool was 86% (95% confidence interval [CI] = 81.5–100.0) compared with 29% (95% CI = 5.1–69.7) for CAM-ICU (p < 0.05), and the specificity was 73% (95% CI = 81.5–100.0) versus 96% (95% CI = 75.1–99.8), respectively. Conclusion: The simple and novel eDIS-ICU delirium screening tool was noninferior to the CAM-ICU in detecting delirium as per DSM-V criteria. A definitive validat

Objectives: Early discharge of patients with presentations triggering assessment for possible acute coronary syndrome (ACS) is safe when clinical assessment indicates low risk, biomarkers are negative, and electrocardiograms (ECGs) are nonischemic. We hypothesized that the Emergency Department Assessment of Chest Pain Score (EDACS) combined with a single measurement of high-sensitivity cardiac troponin (hs-cTn) could allow early discharge of a clinically meaningful proportion of patients. Methods: We pooled data from four patient cohorts from New Zealand and Australia presenting to an emergency department with symptoms suggestive of ACS. The primary outcome was major adverse cardiac events (MACE) within 30 days of presentation. In patients with a nonischemic ECG we evaluated the sensitivity for MACE and percentage low risk of every combination of high-sensitivity cardiac troponin T (hs-cTnT) concentration and high-sensitivity cardiac troponin I (hs-cTnI) concentration with EDACS. We used a standard smoothing technique on the probability density function for hs-cTn and EDACS and applied bootstrapping to determine the optimal threshold combinations, namely, the combination that maximized the percentage low risk with ≥98.5% sensitivity for MACE. Results: From 2,536 patients, 2,258 presented without an ischemic ECG of whom 272 (12.1%) had a MACE within 30 days. The optimal threshold for hs-cTnI was 7 ng/L combined with an EDACS threshold of 16 (36.8% patients low risk). The optimal thresholds for hs-cTnT were 8 ng/L combined with an EDACS threshold of 15 (30.2% patients low risk). Conclusion: Single measurements of both hs-cTnI and hs-cTnT at presentation combined with EDACS to identify over 30% of patients as low risk and therefore eligible for safe early discharge after only one blood draw.