Introduction Stress-induced hyperglycaemia is prevalent in critical care. Control of blood glucose levels to within a 4.4 to 6.1 mmol/L range or below 7.75 mmol/L can reduce mortality and improve clinical outcomes. The Specialised Relative Insulin Nutrition Tables (SPRINT) protocol is a simple wheel-based system that modulates insulin and nutritional inputs for tight glycaemic control.

Peri-operative SARS-CoV-2 infection increases postoperative mortality. The aim of this study was to determine the optimal duration of planned delay before surgery in patients who have had SARS-CoV-2 infection. This international, multicentre, prospective cohort study included patients undergoing elective or emergency surgery during October 2020. Surgical patients with pre-operative SARS-CoV-2 infection were compared with those without previous SARS-CoV-2 infection. The primary outcome measure was 30-day postoperative mortality. Logistic regression models were used to calculate adjusted 30-day mortality rates stratified by time from diagnosis of SARS-CoV-2 infection to surgery. Among 140,231 patients (116 countries), 3127 patients (2.2%) had a pre-operative SARS-CoV-2 diagnosis. Adjusted 30-day mortality in patients without SARS-CoV-2 infection was 1.5% (95%CI 1.4-1.5). In patients with a pre-operative SARS-CoV-2 diagnosis, mortality was increased in patients having surgery within 0-2 weeks, 3-4 weeks and 5-6 weeks of the diagnosis (odds ratio (95%CI) 4.1 (3.3-4.8), 3.9 (2.6-5.1) and 3.6 (2.0-5.2), respectively). Surgery performed ≥ 7 weeks after SARS-CoV-2 diagnosis was associated with a similar mortality risk to baseline (odds ratio (95%CI) 1.5 (0.9-2.1)). After a ≥ 7 week delay in undertaking surgery following SARS-CoV-2 infection, patients with ongoing symptoms had a higher mortality than patients whose symptoms had resolved or who had been asymptomatic (6.0% (95%CI 3.2-8.7) vs. 2.4% (95%CI 1.4-3.4) vs. 1.3% (95%CI 0.6-2.0), respectively). Where possible, surgery should be delayed for at least 7 weeks following SARS-CoV-2 infection. Patients with ongoing symptoms ≥ 7 weeks from diagnosis may benefit from further delay.

This study compares public stigma towards three types of infectious diseases- human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS), severe acute respiratory syndrome (SARS), and tuberculosis (TB)-tests an attribution model of stigma, and explores the relationships between stigma and public attitudes towards government policies in Hong Kong. Using a population-based telephone survey, 3011 Hong Kong Chinese adults were randomly assigned to one of the three disease conditions and were interviewed about their attitudes and beliefs towards the assigned disease. Findings showed that public stigma was the highest towards HIV/AIDS, followed by TB and SARS. Using multi-sample model structural equation modeling, we found that the attributions of controllability, personal responsibility, and blame were applicable in explaining stigma across three disease types. Knowledge about the disease had no significant effect on stigma. Participants with less stigmatizing views had significantly more favorable attitudes towards government policies related to the diseases. The study is an important attempt in understanding the attributional mechanisms of stigma towards infectious diseases. Implications for stigma reduction and promotion of public awareness and disease prevention are discussed.

Targeted, tight model-based glycemic control in critical care patients that can reduce mortality 18 -45% is enabled by prediction of insulin sensitivity, S I . However, this parameter can vary significantly over a given hour in the critically ill as their condition evolves. A stochastic model of S I variability is constructed using data from 165 critical care patients. Given S I for an hour, the stochastic model returns the probability density function of S I for the next hour. Consequently, the glycemic distribution following a known intervention can be derived, enabling pre-determined likelihoods of the result and more accurate control.Cross validation of the S I variability model shows that 86.6% of the blood glucose measurements are within the 0.90 probability interval, and 54.0% are within the interquartile interval. "Virtual Patients" with S I behaving to the overall S I variability model achieved similar predictive performance in simulated trials (86.8% and 45.7%).Finally, adaptive control method incorporating S I variability is shown to produce improved glycemic control in simulated trials compared to current clinical results. The validated stochastic model and methods provide a platform for developing advanced glycemic control methods addressing critical care variability.

This study has revealed insights into how women experienced postnatal depression in Hong Kong, and what they perceived as contributing to their depression. These insights may be used to guide interventions for women and their families to raise awareness regarding the support childbearing women need.