Concomitant Deep Vein Thrombosis in Cancer Patients with Unsuspected Pulmonary Embolism

Incidental venous thromboembolism (VTE) is common in cancer patients and identifying factors associated with these events can improve the management plan. We studied the characteristics of concomitant deep vein thrombosis (C-DVT) in cancer patients presenting with unsuspected pulmonary embolism (PE) and the association of C-DVT with VTE recurrence and survival outcomes. Patients presenting to our emergency department with confirmed unsuspected/incidental PE between 1 January 2006 and 1 January 2016, were identified. Radiologic reports were reviewed to confirm the presence or absence of C-DVT. Logistic regression analyses and cox regression modeling were used to determine the effect of C-DVT on VTE recurrence and survival outcomes. Of 904 eligible patients, 189 (20.9%) had C-DVT. Patients with C-DVT had twice the odds of developing VTE recurrence (odds ratio 2.07, 95% confidence interval 1.21–3.48, p = 0.007). The mortality rates among C-DVT were significantly higher than in patients without. C-DVT was associated with reduced overall survival in patients with unsuspected PE (hazard ratio 1.33, 95% confidence interval 1.09–1.63, p = 0.005). In conclusion, C-DVT in cancer patients who present with unsuspected PE is common and is associated with an increased risk of VTE recurrence and poor short- and long-term survival. Identifying other venous thrombi in cancer patients presenting with unsuspected PE is recommended and can guide the management plan. For patients with isolated incidental subsegmental pulmonary embolism and concomitant deep vein thrombosis, initiating anticoagulants if no contraindications exist is recommended

Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

Background Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P < 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)