Admission prevalence of deep vein thrombosis in elderly Chinese patients with hip fracture and a new predictor based on risk factors for thrombosis screening

中国老年髋部骨折患者入院时深静脉血栓形成患病率及基于血栓筛查危险因素的新预测因子

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Abstract

BACKGROUND: Elderly hip fracture (HF) patients are at very high risk of developing deep vein thrombosis (DVT), which increases their perioperative mortality. However, data focusing on the admission prevalence of DVT in elderly Chinese patients with hip fracture are limited. Venography and ultrasonography are not suitable for most elderly HF patients; there is also controversy about the prognostic value of D-dimer in elderly patients. Thus, our primary goal was to clarify the prevalence of and risk factors for DVT in elderly Chinese HF patients at admission. Our secondary goal was to evaluate the diagnostic value of a new predictor of DVT based on the risk factors for elderly HF patients. METHODS: This retrospective study was conducted in the West China Hospital, Sichuan University. Between January 2015 and January 2017, 248 elderly Chinese HF patients (> 60 years) were enrolled in this study. The subjects were diagnosed with DVT using ultrasonography or venography. All the patients' clinical data were obtained, including demographic variables, medical history, comorbidities, and laboratory results. A stepwise multiple logistic regression analysis was used to identify the risk factors contributing to the occurrence of DVT. The value of the new DVT predictor was calculated using a formula based on the coefficient regression and independent variables. A receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic value of different factors. RESULTS: Of the study patients, 74 (29.8%) were diagnosed with DVT, including sixty-five (87.8%) with distal peripheral, five (6.8%) with proximal central and four (5.4%) with mixed DVT. A multivariate logistic regression analysis showed that five risk factors increased the occurrence of DVT at admission, including gender, age, time from injury to admission, fibrinogen, and D-dimer. The new DVT predictor was calculated using the following formula: 1.131× (female = 1, male = 0) + 0.071 × age (years) + 0.571 × time from injury to admission (days) + 1.028 × fibrinogen(g/L) + 0.123 × D-dimer(g/L). The diagnostic value of the new predictor was highest among those risk predictors whose AUC (area under the ROC curves) value was 0.852. CONCLUSIONS: The results of this study revealed a high prevalence of DVT in elderly Chinese HF patients at admission. Moreover, the new predictor, based on risk factors, was a good method to improve the diagnosis of DVT.

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