Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Risk factors of positive resection margin in laparoscopic and open liver surgery for colorectal liver metastases : a new perspective in the perioperative assessment : a European multicenter study

Objective: To assess the risk factors associated with R1 resection in patients undergoing OLS and LLS for CRLMs. Background: The clinical impact of R1 resection in liver surgery for CRLMs has been continuously appraised, but R1 risk factors have not been clearly defined yet. Methods: A cohort study of patients who underwent OLS and LLS for CRLMs in 9 European high-volume referral centers was performed. A multivariate analysis and the receiver operating characteristic curves were used to investigate the risk factors for R1 resection. A model predicting the likelihood of R1 resection was developed. Results: Overall, 3387 consecutive liver resections for CRLMs were included. OLS was performed in 1792 cases whereas LLS in 1595; the R1 resection rate was 14% and 14.2%, respectively. The risk factors for R1 resection were: the type of resection (nonanatomic and anatomic/nonanatomic), the number of nodules and the size of tumor. In the LLS group only, blood loss was a risk factor, whereas the Pringle maneuver had a protective effect. The predictive size of tumor for R1 resection was >45 mm in OLS and >30 mm in LLS, > 2 lesions was significative in both groups and blood loss >350 cc in LLS. The model was able to predict R1 resection in OLS (area under curve 0.712; 95% confidence interval 0.665 – 0.739) and in LLS (area under curve 0.724; 95% confidence interval 0.671 – 0.745). Conclusions: The study describes the risk factors for R1 resection after liver surgery for CRLMs, which may be used to plan better the perioperative strategies to reduce the incidence of R1 resection during OLS and LLS

Risk factors of positive resection margin in laparoscopic and open liver surgery for colorectal liver metastases: A new perspective in the perioperative assessment: A European multicenter study

Objective: To assess the risk factors associated with R1 resection in patients undergoing OLS and LLS for CRLMs. Background: The clinical impact of R1 resection in liver surgery for CRLMs has been continuously appraised, but R1 risk factors have not been clearly defined yet. Methods: A cohort study of patients who underwent OLS and LLS for CRLMs in 9 European high-volume referral centers was performed. A multivariate analysis and the receiver operating characteristic curves were used to investigate the risk factors for R1 resection. A model predicting the likelihood of R1 resection was developed. Results: Overall, 3387 consecutive liver resections for CRLMs were included. OLS was performed in 1792 cases whereas LLS in 1595; the R1 resection rate was 14% and 14.2%, respectively. The risk factors for R1 resection were: the type of resection (nonanatomic and anatomic/nonanatomic), the number of nodules and the size of tumor. In the LLS group only, blood loss was a risk factor, whereas the Pringle maneuver had a protective effect. The predictive size of tumor for R1 resection was >45 mm in OLS and >30 mm in LLS, > 2 lesions was significative in both groups and blood loss >350 cc in LLS. The model was able to predict R1 resection in OLS (area under curve 0.712; 95% confidence interval 0.665 – 0.739) and in LLS (area under curve 0.724; 95% confidence interval 0.671 – 0.745). Conclusions: The study describes the risk factors for R1 resection after liver surgery for CRLMs, which may be used to plan better the perioperative strategies to reduce the incidence of R1 resection during OLS and LLS

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population