Comparison of baseline characteristics, treatment and celinical outcomes of critically ill COVID-19 patients admitted in the first and second waves in Australia

Objective: To report longitudinal differences in baseline characteristics, treatment, and outcomes in patients with coronavirus disease 2019 (COVID-19) admitted to intensive care units (ICUs) between the first and second waves of COVID-19 in Australia. Design, setting and participants: SPRINT-SARI Australia is a multicentre, inception cohort study enrolling adult patients with COVID-19 admitted to participating ICUs. The first wave of COVID-19 was from 27 February to 30 June 2020, and the second wave was from 1 July to 22 October 2020. Results: A total of 461 patients were recruited in 53 ICUs across Australia; a higher number were admitted to the ICU during the second wave compared with the first: 255 (55.3%) versus 206 (44.7%). Patients admitted to the ICU in the second wave were younger (58.0 v 64.0 years; P = 0.001) and less commonly male (68.9% v 60.0%; P = 0.045), although Acute Physiology and Chronic Health Evaluation (APACHE) II scores were similar (14 v 14; P = 0.998). High flow oxygen use (75.2% v 43.4%; P < 0.001) and non-invasive ventilation (16.5% v 7.1%; P = 0.002) were more common in the second wave, as was steroid use (95.0% v 30.3%; P < 0.001). ICU length of stay was shorter (6.0 v 8.4 days; P = 0.003). In-hospital mortality was similar (12.2% v 14.6%; P = 0.452), but observed mortality decreased over time and patients were more likely to be discharged alive earlier in their ICU admission (hazard ratio, 1.43; 95% CI, 1.13-1.79; P = 0.002). Conclusion: During the second wave of COVID-19 in Australia, ICU length of stay and observed mortality decreased over time. Multiple factors were associated with this, including changes in clinical management, the adoption of new evidence-based treatments, and changes in patient demographic characteristics but not illness severity.

Decision making: the two stages of neuronal judgement

A recent study of how a monkey's frontal cortex responds when decisions are made more difficult has characterised the two distinct stages which turn sensory evidence into a command for action.

The influence of urgency on decision time

A fruitful quantitative approach to understanding how the brain makes decisions has been to look at the time needed to make a decision, and how it is affected by factors such as the supply of information, or an individual's expectations. This approach has led to a model of decision-making, consistent with recent neurophysiological data, that explains the observed variability of reaction times and correctly predicts the effects of altered expectations. Can it also predict what happens when the urgency of making the response changes? We asked subjects to make eye movements to low-visibility targets either as fast or as accurately as possible, and found that the model does indeed predict the timing of their responses: the degree of urgency seems to influence the criterion level at which a decision signal triggers a response.