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JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
Venous thrombosis risk assessment in medical inpatients: the medical inpatients and thrombosis (MITH) study.
Journal of Thrombosis and Haemostasis : JTH 2013 April
BACKGROUND: We sought to define the risk factors present at admission for venous thromboembolism (VTE) in medical inpatients and develop a risk model for clinical use.
METHODS: Between January 2002 and June 2009, 299 cases of hospital-acquired VTE were frequency matched to 601 controls. Records were abstracted using a standard form for characteristics of the thrombosis, medical conditions and other risk factors. Weighted logistic regression and survey methods were used to develop a risk model for hospital-acquired VTE that was validated by bootstrapping.
RESULTS: VTE complicated 4.6 per 1000 admissions. Two risk assessment models were developed, one using laboratory data available at admission (Model 1) and the other excluding laboratory data (Model 2). Model 1 consisted of the following risk factors (points): history of congestive heart failure (5), history of inflammatory disease (4), fracture in the past 3 months (3), history of VTE (2), history of cancer in the past 12 months (1), tachycardia (2), respiratory dysfunction (1), white cell count ≥ 11 × 10(9) /L (1), and platelet count ≥ 350 × 10(9) /L (1). Model 2 was similar, except respiratory dysfunction had 2 points and white cell and platelet counts were removed. The c-statistic for Model 1 was 0.73 (95% CI 0.70, 0.77) and for Model 2 0.71 (95% CI 0.68, 0.75).
CONCLUSIONS: We present a VTE risk assessment model for use in medical inpatients. The score is simple and relies on information known at the time of admission and typically collected in all medical inpatients. External validation is needed.
METHODS: Between January 2002 and June 2009, 299 cases of hospital-acquired VTE were frequency matched to 601 controls. Records were abstracted using a standard form for characteristics of the thrombosis, medical conditions and other risk factors. Weighted logistic regression and survey methods were used to develop a risk model for hospital-acquired VTE that was validated by bootstrapping.
RESULTS: VTE complicated 4.6 per 1000 admissions. Two risk assessment models were developed, one using laboratory data available at admission (Model 1) and the other excluding laboratory data (Model 2). Model 1 consisted of the following risk factors (points): history of congestive heart failure (5), history of inflammatory disease (4), fracture in the past 3 months (3), history of VTE (2), history of cancer in the past 12 months (1), tachycardia (2), respiratory dysfunction (1), white cell count ≥ 11 × 10(9) /L (1), and platelet count ≥ 350 × 10(9) /L (1). Model 2 was similar, except respiratory dysfunction had 2 points and white cell and platelet counts were removed. The c-statistic for Model 1 was 0.73 (95% CI 0.70, 0.77) and for Model 2 0.71 (95% CI 0.68, 0.75).
CONCLUSIONS: We present a VTE risk assessment model for use in medical inpatients. The score is simple and relies on information known at the time of admission and typically collected in all medical inpatients. External validation is needed.
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