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Extended Venous Thromboembolism Prophylaxis After Elective Surgery for IBD Patients: Nomogram-Based Risk Assessment
Cigdem Benlice1, Stefan D Holubar, Emre Gorgun
1Department of Colorectal Surgery, Digestive Disease and Surgery Institute, Cleveland Clinic, Cleveland, Ohio.
Patients with inflammatory bowel disease (IBD) undergoing abdominal surgery face a significant risk of venous thromboembolism (VTE). A new nomogram helps predict VTE risk, guiding extended thromboprophylaxis decisions.
Area of Science:
- Surgical outcomes research
- Gastroenterology
- Vascular medicine
Background:
- Postoperative venous thromboembolism (VTE) is a serious complication for patients with inflammatory bowel disease (IBD) undergoing surgery.
- Identifying risk factors is crucial for preventing VTE and reducing associated morbidity.
Purpose of the Study:
- To identify risk factors for 30-day VTE after abdominal surgery in IBD patients.
- To determine potential indications for extended thromboprophylaxis.
- To develop a predictive nomogram for VTE risk.
Main Methods:
- Retrospective cohort study using data from the American College of Surgeons National Surgical Quality Improvement Program (2005-2016).
- Included patients with IBD undergoing elective abdominopelvic bowel surgery.
- Analyzed in-hospital and postdischarge VTE incidence within 30 days.
Main Results:
- 24,182 patients were analyzed; 30-day VTE rate was 2.5% (614/24,182), with 41% occurring postdischarge.
- Risk factors for VTE included older age, steroid use, bleeding disorders, open surgery, hypertension, longer operative time, and preoperative hospitalization.
- Factors associated with postdischarge VTE included postoperative transfusion, steroid use, specific fistula surgeries, and longer operative time.
Conclusions:
- A nomogram was developed to predict VTE risk before and after discharge.
- This tool can aid in individualized extended thromboprophylaxis decisions for IBD patients undergoing elective abdominopelvic surgery.
- The study highlights the elevated VTE risk in IBD patients and the utility of predictive models.
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