Literature DB >> 32542391

Risk models for VTE and bleeding in medical inpatients: systematic identification and expert assessment.

Andrea J Darzi1,2,3, Samer G Karam1,2,3, Frederick A Spencer4, Alex C Spyropoulos5,6, Lawrence Mbuagbaw1,7,8, Scott C Woller9, Neil A Zakai10,11, Michael B Streiff12, Michael K Gould13, Mary Cushman10,11, Rana Charide14, Itziar Etxeandia-Ikobaltzeta1,2,3, Federico Germini1,2,3,4,15, Marta Rigoni16, Arnav Agarwal1,2,3,17, Rami Z Morsi14, Elie A Akl1,2,3,14,18, Alfonso Iorio1,2,3,4, Holger J Schünemann1,2,3,4.   

Abstract

Risk assessment models (RAMs) for venous thromboembolism (VTE) and bleeding in hospitalized medical patients inform appropriate use of thromboprophylaxis. Our aim was to use a novel approach for selecting risk factors for VTE and bleeding to be included in RAMs. First, we used the results of a systematic review of all candidate factors. Second, we used the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach to assess the certainty of the evidence for the identified factors. Third, we using a structured approach to select factors to develop the RAMs, by building on clinical and methodological expertise. The expert panel made judgments on whether to include, potentially include, or exclude risk factors, according to domains of the GRADE approach and the Delphi method. The VTE RAM included age >60 years, previous VTE, acute infections, immobility, acute paresis, active malignancy, critical illness, and known thrombophilia. The bleeding RAM included age ≥65 years, renal failure, thrombocytopenia, active gastroduodenal ulcers, hepatic disease, recent bleeding, and critical illness. We identified acute infection as a factor that was not considered in widely used RAMs. Also, we identified factors that require further research to confirm or refute their importance in a VTE RAM (eg, D-dimer). We excluded autoimmune disease which is included in the IMPROVE (International Medical Prevention Registry on Venous Thromboembolism) bleeding RAM. Our results also suggest that sex, malignancy, and use of central venous catheters (factors in the IMPROVE bleeding RAM) require further research. In conclusion, our study presents a novel approach to systematically identifying and assessing risk factors to be included or further explored during RAM development.
© 2020 by The American Society of Hematology.

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Year:  2020        PMID: 32542391      PMCID: PMC7322970          DOI: 10.1182/bloodadvances.2020001937

Source DB:  PubMed          Journal:  Blood Adv        ISSN: 2473-9529


  36 in total

1.  Definition of clinically relevant non-major bleeding in studies of anticoagulants in atrial fibrillation and venous thromboembolic disease in non-surgical patients: communication from the SSC of the ISTH.

Authors:  S Kaatz; D Ahmad; A C Spyropoulos; S Schulman
Journal:  J Thromb Haemost       Date:  2015-11       Impact factor: 5.824

2.  A risk assessment model for the identification of hospitalized medical patients at risk for venous thromboembolism: the Padua Prediction Score.

Authors:  S Barbar; F Noventa; V Rossetto; A Ferrari; B Brandolin; M Perlati; E De Bon; D Tormene; A Pagnan; P Prandoni
Journal:  J Thromb Haemost       Date:  2010-11       Impact factor: 5.824

3.  The incidence of venous thromboembolism following stroke and its risk factors in eastern China.

Authors:  Xingyang Yi; Jing Lin; Zhao Han; Xudong Zhou; Xiaotong Wang; Jiguang Lin
Journal:  J Thromb Thrombolysis       Date:  2012-08       Impact factor: 2.300

4.  Measurement of D-dimer as aid in risk evaluation of VTE in elderly patients hospitalized for acute illness: a prospective, multicenter study in China.

Authors:  Jin Fan; Xiaoying Li; Youqin Cheng; Chen Yao; Nanshan Zhong
Journal:  Clin Invest Med       Date:  2011-04-01       Impact factor: 0.825

5.  Predictive and associative models to identify hospitalized medical patients at risk for VTE.

Authors:  Alex C Spyropoulos; Frederick A Anderson; Gordon FitzGerald; Herve Decousus; Mario Pini; Beng H Chong; Rainer B Zotz; Jean-François Bergmann; Victor Tapson; James B Froehlich; Manuel Monreal; Geno J Merli; Ricardo Pavanello; Alexander G G Turpie; Mashio Nakamura; Franco Piovella; Ajay K Kakkar; Frederick A Spencer
Journal:  Chest       Date:  2011-03-24       Impact factor: 9.410

6.  Thromboprophylaxis patterns, risk factors, and outcomes of care in the medically ill patient population.

Authors:  Charles E Mahan; Maxine D Fisher; Roger M Mills; Larry E Fields; Judith J Stephenson; An-Chen Fu; Alex C Spyropoulos
Journal:  Thromb Res       Date:  2013-08-28       Impact factor: 3.944

7.  Clinical conundrums in antithrombotic therapy management: A Delphi Consensus panel.

Authors:  Paolo Colonna; Felicita Andreotti; Walter Ageno; Vittorio Pengo; Niccolò Marchionni
Journal:  Int J Cardiol       Date:  2017-09-19       Impact factor: 4.164

8.  Assessing the Caprini Score for Risk Assessment of Venous Thromboembolism in Hospitalized Medical Patients.

Authors:  Paul J Grant; M Todd Greene; Vineet Chopra; Steven J Bernstein; Timothy P Hofer; Scott A Flanders
Journal:  Am J Med       Date:  2015-11-06       Impact factor: 4.965

9.  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.

Authors:  David Rosenberg; Ann Eichorn; Mauricio Alarcon; Lauren McCullagh; Thomas McGinn; Alex C Spyropoulos
Journal:  J Am Heart Assoc       Date:  2014-11-17       Impact factor: 5.501

Review 10.  Prognosis Research Strategy (PROGRESS) 3: prognostic model research.

Authors:  Ewout W Steyerberg; Karel G M Moons; Danielle A van der Windt; Jill A Hayden; Pablo Perel; Sara Schroter; Richard D Riley; Harry Hemingway; Douglas G Altman
Journal:  PLoS Med       Date:  2013-02-05       Impact factor: 11.069

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  5 in total

1.  Risk-assessment models for VTE and bleeding in hospitalized medical patients: an overview of systematic reviews.

Authors:  Andrea J Darzi; Allen B Repp; Frederick A Spencer; Rami Z Morsi; Rana Charide; Itziar Etxeandia-Ikobaltzeta; Kenneth A Bauer; Allison E Burnett; Mary Cushman; Francesco Dentali; Susan R Kahn; Suely M Rezende; Neil A Zakai; Arnav Agarwal; Samer G Karam; Tamara Lotfi; Wojtek Wiercioch; Reem Waziry; Alfonso Iorio; Elie A Akl; Holger J Schünemann
Journal:  Blood Adv       Date:  2020-10-13

Review 2.  Epidemiology and prevention of venous thromboembolism.

Authors:  Pamela L Lutsey; Neil A Zakai
Journal:  Nat Rev Cardiol       Date:  2022-10-18       Impact factor: 49.421

3.  Factors predicting successful vaginal birth after caesarean section: protocol for evidence-based consensus recommendations using a Delphi survey.

Authors:  Ling Ai; Zubing Mei; Weiying Zhu; Ying Feng; Haiyan Yuan; Yu Wang; Meitang Wang
Journal:  BMJ Open       Date:  2021-05-05       Impact factor: 2.692

4.  Thrombotic and Hemorrhagic Incidences in Patients After Discharge from COVID-19 Infection: A Systematic Review and Meta-Analysis.

Authors:  Tarinee Rungjirajittranon; Weerapat Owattanapanich; Nattawut Leelakanok; Natthaporn Sasijareonrat; Bundarika Suwanawiboon; Yingyong Chinthammitr; Theera Ruchutrakool
Journal:  Clin Appl Thromb Hemost       Date:  2021 Jan-Dec       Impact factor: 2.389

5.  Biomarker derived risk scores predict venous thromboembolism and major bleeding among patients with COVID-19.

Authors:  Scott C Woller; Scott M Stevens; Joseph R Bledsoe; Masarret Fazili; James F Lloyd; Greg L Snow; Benjamin D Horne
Journal:  Res Pract Thromb Haemost       Date:  2022-07-21
  5 in total

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