Venous Thrombosis Risk after Cast Immobilization of the Lower Extremity: Derivation and Validation of a Clinical Prediction Score, L-TRiP(cast), in Three Population-Based Case–Control Studies

Abstract

BackgroundGuidelines and clinical practice vary considerably with respect to thrombosis prophylaxis during plaster cast immobilization of the lower extremity. Identifying patients at high risk for the development of venous thromboembolism (VTE) would provide a basis for considering individual thromboprophylaxis use and planning treatment studies.The aims of this study were (1) to investigate the predictive value of genetic and environmental risk factors, levels of coagulation factors, and other biomarkers for the occurrence of VTE after cast immobilization of the lower extremity and (2) to develop a clinical prediction tool for the prediction of VTE in plaster cast patients.Methods and FindingsWe used data from a large population-based case–control study (MEGA study, 4,446 cases with VTE, 6,118 controls without) designed to identify risk factors for a first VTE. Cases were recruited from six anticoagulation clinics in the Netherlands between 1999 and 2004; controls were their partners or individuals identified via random digit dialing. Identification of predictor variables to be included in the model was based on reported associations in the literature or on a relative risk (odds ratio) > 1.2 and p ≤ 0.25 in the univariate analysis of all participants. Using multivariate logistic regression, a full prediction model was created. In addition to the full model (all variables), a restricted model (minimum number of predictors with a maximum predictive value) and a clinical model (environmental risk factors only, no blood draw or assays required) were created. To determine the discriminatory power in patients with cast immobilization (n = 230), the area under the curve (AUC) was calculated by means of a receiver operating characteristic. Validation was performed in two other case–control studies of the etiology of VTE: (1) the THE-VTE study, a two-center, population-based case–control study (conducted in Leiden, the Netherlands, and Cambridge, United Kingdom) with 784 cases and 523 controls included between March 2003 and December 2008 and (2) the Milan study, a population-based case–control study with 2,117 cases and 2,088 controls selected between December 1993 and December 2010 at the Thrombosis Center, Fondazione IRCCS Ca’ Granda–Ospedale Maggiore Policlinico, Milan, Italy.The full model consisted of 32 predictors, including three genetic factors and six biomarkers. For this model, an AUC of 0.85 (95% CI 0.77–0.92) was found in individuals with plaster cast immobilization of the lower extremity. The AUC for the restricted model (containing 11 predictors, including two genetic factors and one biomarker) was 0.84 (95% CI 0.77–0.92). The clinical model (consisting of 14 environmental predictors) resulted in an AUC of 0.77 (95% CI 0.66–0.87). The clinical model was converted into a risk score, the L-TRiP(cast) score (Leiden–Thrombosis Risk Prediction for patients with cast immobilization score), which showed an AUC of 0.76 (95% CI 0.66–0.86). Validation in the THE-VTE study data resulted in an AUC of 0.77 (95% CI 0.58...

Current and future burden of venous thrombosis: Not simply predictable

“…These models ideally allow identification of individuals at high or low venous thrombosis risk during a specific risk situation. 61 In recent years, several models have been developed for different patient populations such as patients with cancer 62 on which a novel model was also presented at the ISTH 2017 congress by Pabinger and colleagues, 63 major trauma, 64 lower extremity cast-immobilization, 65 medical inpatients, 66 or postpartum women, 67 among others. In order to optimize the safe utilization of these models, they first need to be externally validated (ie, tested in a dataset different from the set in which the models were built).…”

Validation of risk assessment models for venous thrombosis in hospitalized medical patients

“…To use sex and age as predictors, we weighted the age and sex distribution from controls to that of the general population of the Netherlands using direct standardization (Table S4 shows stratum-specific weights). 22 Multiple imputation of missing values was applied for all predictors for which missing data were present (10 imputations). Predictors that were not available (thus not measured at all) were set to no/nonpresent and can be found in Table S3.…”

“…The control group was frequency matched for sex and age, and as a result, their sex and age distribution is not equal to that of the general population. To use sex and age as predictors, we weighted the age and sex distribution from controls to that of the general population of the Netherlands using direct standardization (Table S4 shows stratum‐specific weights) …”

Risks of development of thrombotic complications in surgery

“…Например, влияние гендерного фактора на риск тромбозов учитывается в нескольких схемах прогнозирования. Однако одни авторы [27] к факторам риска тромбоза отнесли мужской пол, а другие [22] -женский. Так, шкала CHA2DS2VASC для определения риска тромбоэмболических событий у пациентов с фибрилляцией предсердий предусматривает выявление таких факторов риска, как сердечная недостаточность, дисфункция левого желудочка, артериальная гипертензия, сахарный диабет, возраст старше 65 лет, транзиторная ишемическая атака, инсульт, тромбоэмболия в анамнезе, сосудистые заболевания и женский пол [22].…”

“…B. Nemeth и соавт. [27] предложили для малоподвижных пациентов с иммобилизованными гипсовыми повязками нижними конечностями клиническую модель, сопряженную с высокой тромботической опасностью. В данной модели в качестве значимых факторов риска являлись: мужской пол, возраст старше 35 лет, злокачественные новообразования в течение последних 5 лет, индекс массы тела 25 и более, семейный анамнез венозных тромбозов [27].…”