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.

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Hypothesis: Intraoperative and postoperative variables contribute to the development of abdominal compartment syndrome (ACS) in general surgical patients. Design: Case-control cohort study of 44 patients admitted to the surgical intensive care unit from March 1, 1995, to January 1, 2001. Groups were matched with respect to age, sex, diagnosis, and procedure. Prospectively collected data included demographics, ventilatory parameters, fluid requirements, hemodynamic and oxygenderived variables, length of stay, and mortality rates. Statistical analysis was done with the Fisher exact test and/or 2 analysis. Continuous variables were analyzed with multivariate and univariate analysis. Data are presented as mean±SD. Statistical significance is defined as PϽ.05. Setting: Long Island Jewish Medical Center (New Hyde Park, NY) is a large tertiary teaching hospital. Patients: Twenty-two patients admitted to the surgical intensive care unit who developed ACS, and 22 casecontrol patients without ACS. Main Outcome Measures: Identification of variables that predict the development of ACS. Results: Twenty-two patients with episodes of ACS (group 1) were examined and contrasted with 22 matched patients without ACS (group 2). Using univariate analysis, the groups differed with respect to 24-hour fluid administration and balance, number of emergency procedures, peak airway pressure, central venous pressure, pulmonary artery occlusion pressure, lengths of stay in the hospital and intensive care unit, and mortality rates. With multivariate analysis, only 24-hour fluid balance and peak airway pressure (group 1 vs group 2: mean±SD, 15.9 ± 10.3 L vs 7.0 ± 3.5 L, and 57.9 ± 11.9 mm Hg vs 32.2 ± 7.1 mm Hg, respectively; PϽ.05) remained significantly different. The groups did not differ with regard to age, cardiac index, operative blood loss, duration of surgery, intraoperative fluid input, or balance. A predictive equation for ACS development was created: P=1/(1 + e −z), where z=−18.6763+0.1671 (peak airway pressure) + 0.0009 (fluid balance).