Thromb Haemost 2018; 118(01): 082-089
DOI: 10.1160/TH17-06-0403
Coagulation and Fibrinolysis
Schattauer GmbH Stuttgart

Comparative Performance of Clinical Risk Assessment Models for Hospital-Acquired Venous Thromboembolism in Medical Patients

Marc Blondon
,
David Spirk
,
Nils Kucher
,
Drahomir Aujesky
,
Daniel Hayoz
,
Jürg H. Beer
,
Marc Husmann
,
Beat Frauchiger
,
Wolfgang Korte
,
Walter A. Wuillemin
,
Henri Bounameaux
,
Marc Righini
,
Mathieu Nendaz
Further Information

Publication History

11 June 2017

05 October 2017

Publication Date:
05 January 2018 (online)

Abstract

Background Improved thromboprophylaxis for acutely ill medical patients relies on valid predictions of thrombotic risks. Our aim was to compare the performance of the Improve and Geneva clinical risk assessment models (RAMs), and to simplify the current Geneva RAM.

Methods Medical inpatients from eight Swiss hospitals were prospectively followed during 90 days, for symptomatic venous thromboembolism (VTE) or VTE-related death. We compared discriminative performance and calibration of the RAMs, using time-to-event methods with competing risk modelling of non-VTE death.

Results In 1,478 patients, the 90-day VTE cumulative incidence was 1.6%. Discrimination of the Improve and Geneva RAM was similar, with a 30-day AUC (areas under the curve) of 0.78 (95% CI [confidence interval]: 0.65–0.92) and 0.81 (0.73–0.89), respectively. According to the Improve RAM, 68% of participants were at low risk (0.8% VTE at 90 days), and 32% were at high risk (4.7% VTE), with a sensitivity of 73%. According to the Geneva RAM, 35% were at low risk (0.6% VTE) and 65% were at high risk (2.8% VTE), with a sensitivity of 90%. Among patients without thromboprophylaxis, the sensitivity was numerically greater in the Geneva RAM (85%) than in the Improve RAM (54%). We derived a simplified Geneva RAM with comparable discrimination and calibration as the original Geneva RAM.

Conclusions We found comparably good discrimination of the Improve and Geneva RAMs. The Improve RAM classified more patients as low risk, but with possibly lower sensitivity and greater VTE risks, suggesting that a lower threshold for low risk (<2) should be used. The simplified Geneva RAM may represent an alternative to the Geneva RAM with enhanced usability.

 
  • References

  • 1 Barbar S, Prandoni P. Scoring systems for estimating risk of venous thromboembolism in hospitalized medical patients. Semin Thromb Hemost 2017; 43 (05) 460-468
  • 2 Office of the Surgeon General; National Heart, Lung, and Blood Institute. The Surgeon General's. Call to Action to Prevent Deep Vein Thrombosis and Pulmonary Embolism. Rockville, MD: Office of the Surgeon General; 2008: 1-49
  • 3 Nendaz M, Spirk D, Kucher N. , et al. Multicentre validation of the Geneva Risk Score for hospitalised medical patients at risk of venous thromboembolism. Explicit ASsessment of Thromboembolic RIsk and Prophylaxis for Medical PATients in SwitzErland (ESTIMATE). Thromb Haemost 2014; 111 (03) 531-538
  • 4 Cohen AT, Tapson VF, Bergmann J-F. , et al; ENDORSE Investigators. Venous thromboembolism risk and prophylaxis in the acute hospital care setting (ENDORSE study): a multinational cross-sectional study. Lancet 2008; 371 (9610): 387-394
  • 5 Agency for Healthcare Research and Quality (AHRQ). Preventing Hospital-Associated Venous Thromboembolism. Rockville, MD: Agency for Healthcare Research and Quality; 2016: 1-92
  • 6 Chopard P, Spirk D, Bounameaux H. Identifying acutely ill medical patients requiring thromboprophylaxis. J Thromb Haemost 2006; 4 (04) 915-916
  • 7 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
  • 8 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
  • 9 Stuck AK, Spirk D, Schaudt J, Kucher N. Risk assessment models for venous thromboembolism in acutely ill medical patients. A systematic review. Thromb Haemost 2017; 117 (04) 801-808
  • 10 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
  • 11 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
  • 12 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-e2
  • 13 Alikhan R, Cohen AT, Combe S. , et al; MEDENOX Study. Risk factors for venous thromboembolism in hospitalized patients with acute medical illness: analysis of the MEDENOX Study. Arch Intern Med 2004; 164 (09) 963-968
  • 14 Mebazaa A, Spiro TE, Büller HR. , et al; Circulation American Heart Association. Predicting the risk of venous thromboembolism in patients hospitalized with heart failure. Circulation 2014; 130 (05) 410-418
  • 15 Parkin L, Sweetland S, Balkwill A, Green J, Reeves G, Beral V. ; Million Women Study Collaborators. Body mass index, surgery, and risk of venous thromboembolism in middle-aged women: a cohort study. Circulation 2012; 125 (15) 1897-1904
  • 16 Austin PC, Lee DS, Fine JP. Introduction to the analysis of survival data in the presence of competing risks. Circulation 2016; 133 (06) 601-609
  • 17 Blanche P, Dartigues J-F, Jacqmin-Gadda H. Estimating and comparing time-dependent areas under receiver operating characteristic curves for censored event times with competing risks. Stat Med 2013; 32: 5381-5397
  • 18 Wolbers M, Blanche P, Koller MT, Witteman JC, Gerds TA. Concordance for prognostic models with competing risks. Biostatistics 2014; 15 (03) 526-539
  • 19 Spirk D, Nendaz M, Aujesky D. , et al. Predictors of thromboprophylaxis in hospitalised medical patients. Explicit ASsessment of Thromboembolic RIsk and Prophylaxis for Medical PATients in SwitzErland (ESTIMATE). Thromb Haemost 2015; 113 (05) 1127-1134
  • 20 Minet C, Potton L, Bonadona A. , et al. Venous thromboembolism in the ICU: main characteristics, diagnosis and thromboprophylaxis. Crit Care 2015; 19: 287
  • 21 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: e195S-226S
  • 22 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
  • 23 Marshall HS, Milikowski C. Comparison of clinical diagnoses and autopsy findings: six-year retrospective study. Arch Pathol Lab Med 2017; 141 (09) 1262-1266