RSS-Feed abonnieren
![](/products/assets/desktop/img/oa-logo.png)
DOI: 10.1055/s-0037-1603929
The IMPROVEDD VTE Risk Score: Incorporation of D-Dimer into the IMPROVE Score to Improve Venous Thromboembolism Risk Stratification
Publikationsverlauf
Publikationsdatum:
28. Juni 2017 (online)
![](https://www.thieme-connect.de/media/10.1055-s-00033990/201701/lookinside/thumbnails/10-1055-s-0037-1603929_17006-1.jpg)
Abstract
Background The IMPROVE score is a validated venous thromboembolism (VTE) assessment tool to risk stratify hospitalized, medically ill patients based on clinical variables. It was hypothesized that addition of D-dimer measurement to derive a new IMPROVEDD score would improve identification of at risk of VTE.
Methods The association of the IMPROVE score and D-dimer ≥ 2 × the upper limit of normal (ULN) with the risk of symptomatic deep vein thrombosis, nonfatal pulmonary embolism, or VTE-related death was evaluated in 7,441 hospitalized, medically ill patients randomized in the APEX trial. Based on the Cox regression analysis, the IMPROVEDD score was derived by adding two points to the IMPROVE score if the D-dimer was ≥ 2 × ULN.
Results Baseline D-dimer was independently associated with symptomatic VTE through 77 days (adjusted HR: 2.22 [95% CI: 1.38–1.58], p = 0.001). Incorporation of D-dimer into the IMPROVE score improved VTE risk discrimination (ΔAUC: 0.06 [95% CI: 0.02–0.09], p = 0.0006) and reclassification (continuous NRI: 0.34 [95% CI: 0.17–0.51], p = 0.001; categorical NRI: 0.13 [95% CI: 0.03–0.23], p = 0.0159). Patients with an IMPROVEDD score of ≥2 had a greater VTE risk compared with those with an IMPROVEDD score of 0 to 1 (HR: 2.73 [95% CI: 1.52–4.90], p = 0.0007).
Conclusion Incorporation of D-dimer into the IMPROVE VTE risk assessment model further improves risk stratification in hospitalized, medically ill patients who received thromboprophylaxis. An IMPROVEDD score of ≥2 identifies hospitalized, medically ill patients with a heightened risk for VTE through 77 days.
Funding
The study was funded by Portola Pharmaceuticals, Inc.
-
References
- 1 Jha AK, Larizgoitia I, Audera-Lopez C, Prasopa-Plaizier N, Waters H, Bates DW. The global burden of unsafe medical care: analytic modelling of observational studies. BMJ Qual Saf 2013; 22 (10) 809-815
- 2 Kahn SR, Lim W, Dunn AS. , et al. Prevention of VTE in nonsurgical patients: Antithrombotic Therapy and Prevention of Thrombosis, 9th ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines. Chest 2012; 141 (2, Suppl): e195S-e226S
- 3 Qaseem A, Chou R, Humphrey LL, Starkey M, Shekelle P. ; Clinical Guidelines Committee of the American College of Physicians. Venous thromboembolism prophylaxis in hospitalized patients: a clinical practice guideline from the American College of Physicians. Ann Intern Med 2011; 155 (09) 625-632
- 4 ISTH Steering Committee for World Thrombosis Day. Venous thromboembolism: A Call for risk assessment in all hospitalised patients. Thromb Haemost 2016; 116 (05) 777-779
- 5 Flanders SA, Greene MT, Grant P. , et al. Hospital performance for pharmacologic venous thromboembolism prophylaxis and rate of venous thromboembolism: a cohort study. JAMA Intern Med 2014; 174 (10) 1577-1584
- 6 Greene MT, Spyropoulos AC, Chopra V. , et al. Validation of risk assessment models of venous thromboembolism in hospitalized medical patients. Am J Med 2016; 129 (09) 1001.e9-1001.e18
- 7 Desjardins L, Bara L, Boutitie F. , et al. Correlation of plasma coagulation parameters with thromboprophylaxis, patient characteristics, and outcome in the MEDENOX study. Arch Pathol Lab Med 2004; 128 (05) 519-526
- 8 Fan J, Li X, Cheng Y, Yao C, Zhong N. ; Investigators Group. Measurement of D-dimer as aid in risk evaluation of VTE in elderly patients hospitalized for acute illness: a prospective, multicenter study in China. Clin Invest Med 2011; 34 (02) E96-E104
- 9 Cohen AT, Harrington R, Goldhaber SZ. , et al. The design and rationale for the Acute Medically Ill Venous Thromboembolism Prevention with Extended Duration Betrixaban (APEX) study. Am Heart J 2014; 167 (03) 335-341
- 10 Mahan CE, Liu Y, Turpie AG. , et al. External validation of a risk assessment model for venous thromboembolism in the hospitalised acutely-ill medical patient (VTE-VALOURR). Thromb Haemost 2014; 112 (04) 692-699
- 11 Rosenberg D, Eichorn A, Alarcon M, McCullagh L, McGinn T, Spyropoulos AC. External validation of the risk assessment model of the International Medical Prevention Registry on Venous Thromboembolism (IMPROVE) for medical patients in a tertiary health system. J Am Heart Assoc 2014; 3 (06) e001152
- 12 Spyropoulos AC, Anderson Jr FA, FitzGerald G. , et al; IMPROVE Investigators. Predictive and associative models to identify hospitalized medical patients at risk for VTE. Chest 2011; 140 (03) 706-714
- 13 Cohen AT, Harrington RA, Goldhaber SZ. , et al; APEX Investigators. Extended thromboprophylaxis with betrixaban in acutely ill medical patients. N Engl J Med 2016; 375 (06) 534-544
- 14 Pencina MJ, D'Agostino Sr RB, D'Agostino Jr RB, Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 2008; 27 (02) 157-172 , discussion 207–212
- 15 Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making 2006; 26 (06) 565-574
- 16 Lester W, Freemantle N, Begaj I, Ray D, Wood J, Pagano D. Fatal venous thromboembolism associated with hospital admission: a cohort study to assess the impact of a national risk assessment target. Heart 2013; 99 (23) 1734-1739
- 17 Roberts LN, Porter G, Barker RD. , et al. Comprehensive VTE prevention program incorporating mandatory risk assessment reduces the incidence of hospital-associated thrombosis. Chest 2013; 144 (04) 1276-1281
- 18 Catterick D, Hunt BJ. Impact of the national venous thromboembolism risk assessment tool in secondary care in England: retrospective population-based database study. Blood Coagul Fibrinolysis 2014; 25 (06) 571-576
- 19 Barbar S, Noventa F, Rossetto V. , et al. A risk assessment model for the identification of hospitalized medical patients at risk for venous thromboembolism: the Padua Prediction Score. J Thromb Haemost 2010; 8 (11) 2450-2457
- 20 Kucher N, Koo S, Quiroz R. , et al. Electronic alerts to prevent venous thromboembolism among hospitalized patients. N Engl J Med 2005; 352 (10) 969-977
- 21 Woller SC, Stevens SM, Jones JP. , et al. Derivation and validation of a simple model to identify venous thromboembolism risk in medical patients. Am J Med 2011; 124 (10) 947-954.e2
- 22 Pabinger I, Thaler J, Ay C. Biomarkers for prediction of venous thromboembolism in cancer. Blood 2013; 122 (12) 2011-2018
- 23 Eichinger S, Heinze G, Jandeck LM, Kyrle PA. Risk assessment of recurrence in patients with unprovoked deep vein thrombosis or pulmonary embolism: the Vienna prediction model. Circulation 2010; 121 (14) 1630-1636
- 24 Raskob GE, Spyropoulos AC, Zrubek J. , et al. The MARINER trial of rivaroxaban after hospital discharge for medical patients at high risk of VTE. Design, rationale, and clinical implications. Thromb Haemost 2016; 115 (06) 1240-1248
- 25 Lippi G, Tripodi A, Simundic AM, Favaloro EJ. International survey on D-dimer test reporting: a call for standardization. Semin Thromb Hemost 2015; 41 (03) 287-293