Abstract 378: A Systematic Review of Mobility/Immobility in Thromboembolism Risk Assessment Models for Hospitalized Patients

2017 ◽  
Vol 121 (suppl_1) ◽  
Author(s):  
Fan Ye ◽  
Carolyn Stalvey ◽  
Matheen Khuddus ◽  
David Winchester ◽  
Hale Toklu ◽  
...  

Introduction: Venous thromboembolism (VTE) is a potentially fatal disorder. Prophylaxis is often suboptimal in medical inpatients, attributed to the difficulty in identifying at-risk patients. Simple and validated risk-assessment models (RAMs) are available to assist clinicians in identifying and stratifying patients who have a higher likelihood for developing VTE. Despite the well-documented association of immobility with increased risk of thrombosis, immobility is not consistently defined in clinical studies. Methods: We conducted a systematic review of published RAMs, based on objective criteria, to determine how the term immobility is defined in RAMs. Results: We identified seventeen RAMs with six being externally validated. The concept of immobility is vaguely described in different RAMs, impacting the validity of these models in clinical practice. The widespread variability in defining mobility in RAMs precluded its accurate clinical application further limiting generalization of published RAMs. Conclusion: Externally validated RAMs with clearly defined qualitative or quantitative terms of immobility are needed to assess VTE risk in real-time at the point-of-care.

Author(s):  
Noori A.M. Guman ◽  
Matteo Candeloro ◽  
Noémie Kraaijpoel ◽  
Marcello Di Nisio

AbstractCancer patients have a high risk of developing venous thromboembolism and arterial thrombosis, along with an increased risk of anticoagulant-related bleeding with primary and secondary prophylaxis of cancer-associated thrombosis. Decisions on initiation, dosing, and duration of anticoagulant therapy for prevention and treatment of cancer-associated thrombosis are challenging, as clinicians have to balance patients' individual risk of (recurrent) thrombosis against the risk of bleeding complications. For this purpose, several dedicated risk assessment models for venous thromboembolism in cancer patients have been suggested. However, most of these scores perform poorly and have received limited to no validation. For bleeding and arterial thrombosis, no risk scores have been developed specifically for cancer patients, and treatment decisions remain based on clinical gestalt and rough and unstructured estimation of the risks. The aims of this review are to summarize the characteristics and performance of risk assessment scores for (recurrent) venous thromboembolism and discuss available data on risk assessment for bleeding and arterial thrombosis in the cancer population. This summary can help clinicians in daily practice to make a balanced decision when considering the use of risk assessment models for cancer-associated venous thromboembolism. Future research attempts should aim at improving risk assessment for arterial thrombosis and anticoagulant-related bleeding in cancer patients.


2020 ◽  
Vol 18 (6) ◽  
pp. 1398-1407 ◽  
Author(s):  
Thomas Moumneh ◽  
Jérémie Riou ◽  
Delphine Douillet ◽  
Samir Henni ◽  
Dominique Mottier ◽  
...  

2012 ◽  
Vol 108 (12) ◽  
pp. 1072-1076 ◽  
Author(s):  
Thomas McGinn ◽  
Alok Khorana ◽  
Alex Spyropoulos

SummaryFormalised risk assessment models (RAMs) for venous thromboembolism (VTE) using weighted and scored variables have only recently been widely incorporated into international antithrombotic guidelines.Scored and weighted VTE RAMs have advantages over a simplified group-specific VTE risk approach, with the potential to allow more tailored strategies for thromboprophylaxis and an improved estimation of the risk/benefit profile for a particular patient. The derivation of VTE RAMs should be based on variables that are a priori defined or identified in a univariate analysis and the predictive capability of each variable should be rigorously assessed for both clinical and statistical significance and internal consistency and completeness. The assessment of the RAM should include the goodness of fit of the model and construction of a prognostic index score. Any VTE RAM which has been derived must undergo validation of that model before it can be used in clinical practice. Validation of the model should be performed in a “deliberate”prospective fashion across several diverse clinical sites using pre-defined criteria using basic standards for performing model validation. We discuss the basic concepts in the derivation of recent scored and weighted VTE RAMs in hospitalised surgical and medical patients and cancer outpatients, the mechanisms for accurate external validation of the models, and implications for their use in clinical practice.


2016 ◽  
Vol 69 (6) ◽  
Author(s):  
Reza Rafizadeh ◽  
Ricky D Turgeon ◽  
Josh Batterink ◽  
Victoria Su ◽  
Anthony Lau

<p><strong>ABSTRACT</strong></p><p><strong>Background:</strong> Symptomatic venous thromboembolism (VTE) occurs in about 1% of patients within 3 months after admission to a medical unit. Recent evidence for thromboprophylaxis in an unselected medical inpatient population has suggested only a modest net benefit. Consequently, guidelines recommend careful risk stratification to guide thromboprophylaxis.</p><p><strong>Objectives:</strong> To compare candidacy for thromboprophylaxis according to 4 risk stratification models: a regional preprinted order (PPO) set used in the study institution, the Padua Prediction Score, and the IMPROVE predictive and associative risk assessment models.</p><p><strong>Methods:</strong> A retrospective review of health records was undertaken for patients with no contraindication to pharmacologic thromboprophylaxis who were admitted to the internal medicine service of a teaching hospital between April and July 2013.</p><p><strong>Results:</strong> Of the 298 patients in the study cohort, 238 (80.0%) received pharmacologic thromboprophylaxis on admission, ordered according to the regional PPO. However, according to the Padua and the IMPROVE predictive risk assessment models, only 64 (21.5%) and 21 (7.0%) of the patients, respectively, were eligible for thromboprophylaxis at the time of admission. On the basis of risk factors identified during the subsequent hospital stay, 54 (18.1%) of the patients were eligible for thromboprophylaxis according to the IMPROVE associative model. Chance-corrected agreement between the PPO and the published risk assessment models was generally poor, with kappa coefficients of 0.109 for the PPO compared with the Padua Prediction Score and 0.013 for the PPO compared with the IMPROVE predictive model.</p><p><strong>Conclusions:</strong> These data suggest that quantitative models such as the Padua Prediction Score and the IMPROVE models identify more patients at low risk of venous thromboembolism than do in-hospital qualitative risk assessment models. Adoption of these guideline-based risk assessment models for predicting thromboembolic risk in medical inpatients could reduce the use of pharmacologic thromboprophylaxis from 80% to as low as 7%. Further external prognostic validation of risk assessment models and impact analysis studies may show improvements in safety and resource utilization.</p><p><strong>RÉSUMÉ</strong></p><p><strong>Contexte :</strong> La thromboembolie veineuse symptomatique se produit chez environ 1 % des patients dans les trois mois suivant leur admission à un service médical. Des données récentes portant sur la thromboprophylaxie chez une population non sélectionnée de patients hospitalisés ne suggéraient qu’un modeste avantage. Par conséquent, les lignes directrices recommandent une stratification du risque rigoureuse pour guider l’emploi d’une thromboprophylaxie.</p><p><strong>Objectifs :</strong> Comparer l’admissibilité à la thromboprophylaxie en fonction de quatre modèles de stratification du risque : un ensemble d’ordonnances préimprimées adopté dans une région et utilisé dans l’établissement à l’étude, le score prédictif de Padua et les modèles prédictifs et associatifs d’évaluation du risque issus de l’étude IMPROVE.</p><p><strong>Méthodes :</strong> Une analyse rétrospective des dossiers médicaux a été menée auprès des patients ne présentant pas de contre-indication à la thromboprophylaxie médicamenteuse qui ont été admis au service de médecine interne d’un hôpital universitaire entre avril et juillet 2013.</p><p><strong>Résultats :</strong> Parmi les 298 patients de l’étude de cohorte, 238 (80,0 %) ont reçu une thromboprophylaxie médicamenteuse au moment de l’admission, prescrite conformément à l’ensemble d’ordonnances préimprimées en usage dans la région. Or, respectivement selon les modèles prédictifs d’évaluation du risque Padua et IMPROVE, seuls 64 (21,5 %) et 21 (7,0 %) des patients étaient admissibles à la thromboprophylaxie au moment de l’admission. En fonction de facteurs de risques identifiés pendant le séjour subséquent à l’hôpital, 54 (18,1 %) des patients étaient admissibles à la thromboprophylaxie selon le modèle associatif IMPROVE. L’accord corrigé pour le hasard entre l’ensemble d’ordonnances préimprimées et les modèles d’évaluation du risque publiés était généralement faible, les coefficients de kappa étant de 0,109 pour l’ensemble d’ordonnances préimprimées comparé au score prédictif de Padua et de 0,013 pour l’ensemble d’ordonnances préimprimées comparé au modèle prédictif IMPROVE.</p><p><strong>Conclusions :</strong> Ces données suggèrent que les modèles quantitatifs comme le score prédictif de Padua et les modèles IMPROVE permettent de dépister plus de patients qui sont à faible risque de thromboembolie veineuse que ne le permettent les modèles qualitatifs d’évaluation du risque propres aux hôpitaux. L’adoption de ces modèles d’évaluation du risque mis de l’avant dans des lignes directrices pour prédire les risques d’événements thromboemboliques chez les patients médicaux hospitalisés pourrait réduire l’utilisation de la thromboprophylaxie médicamenteuse, qui pourrait passer de 80 % à aussi peu que 7 %. De plus amples validations externes quant à la valeur prédictive des modèles d’évaluation du risque et des études d’analyse d’impact pourraient montrer des améliorations à la sécurité et une réduction de l’utilisation des ressources.</p>


2012 ◽  
Vol 35 (1) ◽  
pp. 67-80 ◽  
Author(s):  
Wei Huang ◽  
Frederick A. Anderson ◽  
Frederick A. Spencer ◽  
Alexander Gallus ◽  
Robert J. Goldberg

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