BackgroundEmergency laparotomies in the UK, USA and Denmark are known to have a high risk of death, with accompanying evidence of suboptimal care. The emergency laparotomy pathway quality improvement care (ELPQuiC) bundle is an evidence-based care bundle for patients undergoing emergency laparotomy, consisting of: initial assessment with early warning scores, early antibiotics, interval between decision and operation less than 6 h, goal-directed fluid therapy and postoperative intensive care.MethodsThe ELPQuiC bundle was implemented in four hospitals, using locally identified strategies to assess the impact on risk-adjusted mortality. Comparison of case mix-adjusted 30-day mortality rates before and after care-bundle implementation was made using risk-adjusted cumulative sum (CUSUM) plots and a logistic regression model.ResultsRisk-adjusted CUSUM plots showed an increase in the numbers of lives saved per 100 patients treated in all hospitals, from 6·47 in the baseline interval (299 patients included) to 12·44 after implementation (427 patients included) (P < 0·001). The overall case mix-adjusted risk of death decreased from 15·6 to 9·6 per cent (risk ratio 0·614, 95 per cent c.i. 0·451 to 0·836; P = 0·002). There was an increase in the uptake of the ELPQuiC processes but no significant difference in the patient case-mix profile as determined by the mean Portsmouth Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity risk (0·197 and 0·223 before and after implementation respectively; P = 0·395).ConclusionUse of the ELPQuiC bundle was associated with a significant reduction in the risk of death following emergency laparotomy.

The Logistic Clinical SXscore substantially enhances the prediction of 1-year mortality after PCI compared with the SXscore, and allows for an accurate personalized assessment of patient risk.

These data provide further evidence that variables derived from preoperative CPET can be used to assess risk before elective colorectal surgery.

No abstract

We observed survival after scheduled repair of abdominal aortic aneurysm in 1096 patients for a median (IQR [range]) of 3.0 (1. 5-5.8 [0-15]) years: 943 patients had complete data, 250 of whom died. We compared discrimination and calibration of an external model with the Kaplan-Meier model generated from the study data. Integrated Brier misclassification scores for both models at 1-5 postoperative years were 0.04, 0.08, 0.11, 0.13 and 0.16, respectively. Harrel's concordance index at 1-5 postoperative years was 0.73, 0.71, 0.68, 0.67 and 0.66, respectively. Groups with median 5-year predicted mortality of 40% (n = 251), 18% (n = 414) and 8% (n = 164) had lower observed mortality than 114 patients with 70% predicted mortality, hazard ratio (95% CI): 0.58 (0.37-0.76), p = 0.0031; 0.30 (0.19-0.48), p = 1.7 9 10 À12 and 0.19 (0.13-0.27), p = 1.3 9 10 À10

This study confirms the consistent ability of the SXscore to identify patients who are at highest risk of adverse events.

Planned postoperative critical care was associated with a lower rate of complications after elective colorectal surgery.

Background: A key first step in optimising COVID-19 patient outcomes during future case-surges is to learn from the experience within individual hospitals during the early stages of the pandemic. The aim of this study was to investigate the extent of variation in COVID-19 outcomes between National Health Service (NHS) hospital trusts and regions in England using data from MarchÀJuly 2020. Methods: This was a retrospective observational study using the Hospital Episode Statistics administrative dataset. Patients aged 18 years who had a diagnosis of COVID-19 during a hospital stay in England that was completed between March 1st and July 31st, 2020 were included. In-hospital mortality was the primary outcome of interest. In secondary analysis, critical care admission, length of stay and mortality within 30 days of discharge were also investigated. Multilevel logistic regression was used to adjust for covariates. Findings: There were 86,356 patients with a confirmed diagnosis of COVID-19 included in the study, of whom 22,944 (26.6%) died in hospital with COVID-19 as the primary cause of death. After adjusting for covariates, the extent of the variation in-hospital mortality rates between hospital trusts and regions was relatively modest. Trusts with the largest baseline number of beds and a greater proportion of patients admitted to critical care had the lowest in-hospital mortality rates. Interpretation: There is little evidence of clustering of deaths within hospital trusts. There may be opportunities to learn from the experience of individual trusts to help prepare hospitals for future case-surges.