Vineet Chopra, MD, MSc*1;Dr. David Paje, MD, MPH2;Anna Conlon, PhD2;Dr. Paul J Grant, MD3;Scott Kaatz, DO, MSc4;Dr. Steven J Bernstein, MD, MPH1 and Dr. Scott A. Flanders, MD3, (1)VA Ann Arbor Healthcare System, Ann Arbor, MI, (2)University of Michigan Health System, Ann Arbor, MI, (3)University of Michigan, Ann Arbor, MI, (4)Henry Ford Health System, Detroit, MI

Meeting: Hospital Medicine 2017

Categories: Oral Presentations, Research Abstracts

Keywords: , , ,

Background: Peripherally inserted central catheters (PICCs) have been associated with venous thromboembolism (VTE) and are a major cause of upper extremity deep vein thrombosis (DVT).  However, mechanisms to identify patients at greatest risk of PICC-associated VTE are limited.

Methods:  Using data from the Michigan Hospital Medicine Safety consortium, patients with PICCs that experienced symptomatic, image-confirmed upper-extremity DVT were identified. A logistic, mixed effect, two-stage model with hospital-specific random intercepts was used to identify factors associated with PICC-DVT. Points were assigned to each predictor, stratifying patients into four classes for risk of PICC-DVT. Validation was performed by internal bootstrapping with results expressed as odds ratios (OR) and 95% confidence intervals (CI).

Results: Of 22,056 patients that received PICCs, 478 (2.2%) developed symptomatic PICC-DVT were included in the analysis. Risk factors associated with PICC-DVT following two-stage modeling included: history of DVT; use of a multi-lumen PICC; active cancer; presence of another CVC when the PICC was placed; and a white blood cell count greater than 12,000 at the time of PICC insertion (Table 1). Thrombosis rates were 0.8% for class I, 1.7% for class II, 2.9% for class III and 6.9% for class IV. The risk classification rule was significantly associated with VTE risk (p<0.0001), with ORs of PICC-DVT of 1.83 (95 % CI: 1.30, 2.57), 3.30 (95 % CI: 2.43, 4.49) and 8.27 (95 % CI: 5.69, 12.01) for risk classes II, III and IV vs. risk class I, respectively (Table 2). The area under the receiver-operating-characteristics curve was 0.72, with an estimated optimism of 0.02 from the bootstrap internal validation data, suggesting excellent performance.

Conclusions: The Michigan Risk Score offers a novel way to predict and categorize risk of PICC-VTE and advances the field in several ways. First, it can help identify patients at high-risk of thrombosis when considering PICC placement. Second, the tool may help inform surveillance or testing among those at high-risk in the setting of vague symptoms. Finally, the risk score could also help inform duration of anticoagulation in patients with PICC-associated thrombosis, with consideration of extended courses in those at highest risk of this event. External validation of this rule with studies that explore implementation in real-world practice are needed.

To cite this abstract:

Chopra, V; Paje, D; Conlon, A; Grant, PJ; Kaatz, S; Bernstein, SJ; Flanders, SA . MICHIGAN RISK SCORE TO PREDICT PICC-RELATED VENOUS THROMBOEMBOLISM [abstract]. Journal of Hospital Medicine. 2017; 12 (suppl 2). http://www.shmabstracts.com/abstract/michigan-risk-score-to-predict-picc-related-venous-thromboembolism/. Accessed April 26, 2017.

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