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Aims International early warning scores (EWS) including the additive National Early Warning Score (NEWS) and logistic EWS currently utilise physiological snapshots to predict clinical deterioration. We hypothesised that a dynamic score including vital sign trajectory would improve discriminatory power. Methods Multicentre retrospective analysis of electronic health record data from postoperative patients admitted to cardiac surgical wards in four UK hospitals. Least absolute shrinkage and selection operator-type regression (LASSO) was used to develop a dynamic model (DyniEWS) to predict a composite adverse event of cardiac arrest, unplanned intensive care re-admission or in-hospital death within 24 h. Results A total of 13,319 postoperative adult cardiac patients contributed 442,461 observations of which 4234 (0.96%) adverse events in 24 h were recorded. The new dynamic model (AUC = 0.80 [95% CI 0.78−0.83], AUPRC = 0.12 [0.10−0.14]) outperforms both an updated snapshot logistic model (AUC = 0.76 [0.73−0.79], AUPRC = 0.08 [0.60−0.10]) and the additive National Early Warning Score (AUC = 0.73 [0.70−0.76], AUPRC = 0.05 [0.02−0.08]). Controlling for the false alarm rates to be at current levels using NEWS cut-offs of 5 and 7, DyniEWS delivers a 7% improvement in balanced accuracy and increased sensitivities from 41% to 54% at NEWS 5 and 18% to –30% at NEWS 7. Conclusions Using an advanced statistical approach, we created a model that can detect dynamic changes in risk of unplanned readmission to intensive care, cardiac arrest or in-hospital mortality and can be used in real time to risk-prioritise clinical workload.

Summary NHS England recently mandated that the National Early Warning Score of vital signs be used in all acute hospital trusts in the UK despite limited validation in the postoperative setting. We undertook a multicentre UK study of 13,631 patients discharged from intensive care after risk-stratified cardiac surgery in four centres, all of which used VitalPAC™ to electronically collect postoperative National Early Warning Score vital signs. We analysed 540,127 sets of vital signs to generate a logistic score, the discrimination of which we compared with the national additive score for the composite outcome of: in-hospital death; cardiac arrest; or unplanned intensive care admission. There were 578 patients (4.2%) with an outcome that followed 4300 sets of observations (0.8%) in the preceding 24 h: 499 out of 578 (86%) patients had unplanned re-admissions to intensive care. Discrimination by the logistic score was significantly better than the additive score. Respective areas (95%CI) under the receiver-operating characteristic curve with 24-h and 6-h vital signs were: 0.779 (0.771–0.786) vs. 0.754 (0.746–0.761), p < 0.001; and 0.841 (0.829–0.853) vs. 0.813 (0.800–0.825), p < 0.001, respectively. Our proposed logistic Early Warning Score was better than the current National Early Warning Score at discriminating patients who had an event after cardiac surgery from those who did not.

Maintaining safe elective surgical activity during the global coronavirus disease 2019 (COVID-19) pandemic is challenging and it is not clear how COVID-19 may impact peri-operative morbidity and mortality in this population. Therefore, adaptations to normal care pathways are required. Here, we establish if implementation of a bespoke peri-operative care bundle for urgent elective surgery during a pandemic surge period can deliver a low COVID-19-associated complication profile. We present a single-centre retrospective cohort study from a tertiary care hospital of patients planned for urgent elective surgery during the initial COVID-19 surge in the UK between 29 March and 12 June 2020. Patients asymptomatic for COVID-19 were screened by oronasal swab and chest imaging (chest X-ray or computed tomography if aged ≥ 18 years), proceeding to surgery if negative. COVID-19 positive patients at screening were delayed. Postoperatively, patients transitioning to COVID-19 positive status by reverse transcriptase polymerase chain reaction testing were identified by an in-house tracking system and monitored for complications and death within 30 days of surgery. Out of 557 patients referred for surgery (230 (41.3%) women; median (IQR [range]) age 61 (48-72 [1-89])), 535 patients (96%) had COVID-19 screening, of which 13 were positive (2.4%, 95%CI 1.4-4.1%). Out of 512 patients subsequently undergoing surgery, 7 (1.4%) developed COVID-19 positive status (1.4%, 95%CI 0.7-2.8%) with one COVID-19-related death (0.2%, 95%CI 0.0-1.1%) within 30 days. Out of these seven patients, four developed pneumonia, of which two required invasive ventilation including one patient with acute respiratory distress syndrome. Low rates of COVID-19 infection and mortality in the elective surgical population can be achieved within a targeted care bundle. This should provide reassurance that elective surgery can continue, where possible, despite high community rates of COVID-19.

Editor – We read with great interest the early Newcastle experience of using National Early Warning Score 2 (NEWS2) to identify hospitalised COVID-19 patients at risk of clinical deterioration.[1][1] The study highlights an average >30 hour lag between triggering the NEWS2 ≥5 threshold and first

The incidence of cardiac arrest following cardiac surgery is low and associated with favourable outcomes if timely interventions are undertaken. Many factors precipitate patient deterioration, all of which necessitate investigation. In situations of cardiac arrest, the use of a universal structured approach improves outcome. Anaesthetists caring for postoperative cardiac surgical patients are strongly advised to familiarise themselves with such protocols or attend a suitable resuscitation course.19, 20

The generic instructor course (GIC) is designed to train potential candidates in how to teach on courses for providers of life support. It is a course overseen by the Resuscitation Council (UK) and the Advanced Life Support Group, and it focuses on the acquisition of practical skills in teaching and assessment as applied to the life support courses offered by the two groups. The course is available for any life support provider who performed exceptionally well in their parent course and was recommended for training as an instructor by their faculty. The criterion for recommendation varies according to provider course. There are many eligible provider courses—for example, the advanced life support course, the newborn life support course, and the advanced paediatric life support course. I completed the GIC as a potential instructor for advanced life support four months after my original provider …