The COVID-19 [SARS-COV-2] pandemic has had a devastating global impact, with both the human and socio economic costs being severe. One result of the COVID-19 pandemic is the emergence of an urgent requirement for effective techniques and technologies for screening individuals showing symptoms of infection in a non-invasive and non-contact way. Systems that exploit thermal imaging technology to screen individuals show promise to satisfy the desired criteria, including offering a non-contact, non-invasive method of temperature measurement. Furthermore, the potential for mass and passive screening makes thermal imaging systems an attractive technology where current ′standard of care′ methods are not practical. Critically, any fever screening solution must be capable of accurate temperature measurement and subsequent prediction of core temperature. This is essential to ensure a high sensitivity in identifying fever while maintaining a low rate of false positives. This paper discusses the results and analysis of a clinical trial undertaken by Thales UK Ltd and the Queen Elizabeth University Teaching Hospital in Glasgow to assess the accuracy and operation of the High Temperature Detection (HTD) system developed by Thales UK Ltd when used in a clinical setting. Results of this single centre prospective observational cohort study show that the measured laboratory accuracy of the Thales HTD system (RMSE=0.1°C) is comparable to the accuracy when used in a clinical setting (RMSE=0.15°C) when measuring a calibrated blackbody source at typical skin temperature. For measurement of forehead skin temperature, the system produced results commensurate with close contact measurement methods (R=0.86, Mean error = 0.05°C). Compared to measured tympanic temperatures, measurement of the forehead skin temperature by the HTD system showed a moderate correlation (R=0.43), which is stronger than close contact IR forehead thermometers (R=0.20, 0.35). An improved correlation was observed between the maximum facial temperature measured by the HTD system and measured tympanic temperatures (R=0.53), which is significantly stronger than the close contact methods. A linear predictive model for tympanic temperature based on the measured maximum facial temperatures resulted in a root mean square error (RMSE=0.50°C) that is marginally larger than what is expected as a compound of errors in the measuring devices (RMSE=0.45°C). The study demonstrates that the HTD could be applied in the clinical and non-clinical setting as a screening mechanism to detect citizens with raised temperature. This approach would enable high volume surveillance and identification of individuals that contribute to further spread of COVID-19. Deployment of the HTD system could be implemented as part of a screening tool to support measures to enhance public safety and confidence in areas of high throughput, such as airports, shopping centres or places of work.

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Aim Emergency laparotomies carry significant risk of morbidity and mortality. Risk calculation tools are essential to identify high-risk patients and inform clinicians in decision making. As part of a multi-centre research initiative, a retrospective study of all emergency laparotomies in a major trauma centre was conducted to determine the most accurate predictor of thirty-day mortality by comparing four, internationally recognised, risk assessment tools. Method Patients who underwent emergency laparotomy were identified using hospital databases. National Emergency Laparotomy Audit (NELA) was used to record pre- and post-operative mortality scores. The Portsmouth Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity (P-POSSUM); American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) and Surgical Outcome Risk Tool (SORT) were used to calculate risk of mortality for each patient. The Receiver Operating Curve (ROC) statistical method was chosen to compare the results of each in order to establish the tool most pertinent to prediction of local mortality. Results 274 patients underwent emergency laparotomies at the Trust between December 2017 to December 2019. Of these, 96.7% (n=265) survived the 30-day post -operative period and 3.3% (n= 9) died. The ROC comparator demonstrated 100% sensitivity for the calculation of NELA, P-POSSUM and ACS-NSQIP and specificity of 77%, 76% and 63% for NELA, ACS-NSQIP and P-POSSUM respectively. SORT was found to be the poorest indicator of post-operative mortality. Conclusions NELA is the most accurate predictor of 30-day mortality in patients who undergo emergency laparotomy. Comparison with the outcomes of other centres will help confirm our results.