1Department of Medicine, McMaster University, Hamilton, ON, Canada. 2Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada. 3Research Center of the CHU de Québec, Population Health and Optimal Health Practices Research Unit, Québec, QC, Canada. 4Division of Critical Care, Department of Medicine, Québec, QC, Canada. 5Section of Critical Care, Department of Internal Medicine, University of Manitoba, Winnipeg, MB, Canada. 6Section of Hematology/Medical Oncology, Department of Internal Medicine, University of Manitoba, Winnipeg, MB, Canada. 7Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada. 8Division of Critical Care, Department of Medicine, Centre de Recherche Clinique Étiene-Le Bel, Université de Sherbrooke, Sherbrooke, QC, Canada. 9Division of Critical Care Medicine and Center for Health Evaluation and Outcome Sciences, St. Paul's Hospital and University of British Columbia, Vancouver, BC, Canada. 10Department of Critical Care, University of Ottawa, Ottawa, ON, Canada. 11Department of Anesthesia, Queen Elizabeth II Health Sciences Centre, 12Department of Critical Care, Queen Elizabeth II Health Sciences Centre, Halifax, NS, Canada. 13Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada. 14Department of Medicine, Queen's University, Kingston, ON, Canada. 15Department of Anesthesiology, Québec, QC, Canada. 16Department of Medicine, University of Toronto, Toronto, ON, Canada. 17Malcolm Fisher Department of Intensive Care Medicine, Royal North Shore Hospital, Sydney, Australia. 18The George Institute for Global Health, University of Sydney, Sydney, Australia. 19Department of Critical Care, University of Alberta, Edmonton, AB, Canada. 20Department of Anesthesia, University of Alberta, Edmonton, AB, Canada. 21Department of Medicine, Research Institute-HCor, Hospital do Coracao, Sao Paolo, Brazil. 22Department of Intensive Care Medicine, Guys
Crit Care Med. 2015 Feb;43(2):401-10. doi: 10.1097/CCM.0000000000000713.
To identify risk factors for failure of anticoagulant thromboprophylaxis in critically ill patients in the ICU.
Multivariable regression analysis of thrombosis predictors from a randomized thromboprophylaxis trial.
Sixty-seven medical-surgical ICUs in six countries.
Three thousand seven hundred forty-six medical-surgical critically ill patients.
All patients received anticoagulant thromboprophylaxis with low-molecular-weight heparin or unfractionated heparin at standard doses.
Independent predictors for venous thromboembolism, proximal leg deep vein thrombosis, and pulmonary embolism developing during critical illness were assessed. A total of 289 patients (7.7%) developed venous thromboembolism. Predictors of thromboprophylaxis failure as measured by development of venous thromboembolism included a personal or family history of venous thromboembolism (hazard ratio, 1.64; 95% CI, 1.03-2.59; p = 0.04) and body mass index (hazard ratio, 1.18 per 10-point increase; 95% CI, 1.04-1.35; p = 0.01). Increasing body mass index was also a predictor for developing proximal leg deep vein thrombosis (hazard ratio, 1.25; 95% CI, 1.06-1.46; p = 0.007), which occurred in 182 patients (4.9%). Pulmonary embolism occurred in 47 patients (1.3%) and was associated with body mass index (hazard ratio, 1.37; 95% CI, 1.02-1.83; p = 0.035) and vasopressor use (hazard ratio, 1.84; 95% CI, 1.01-3.35; p = 0.046). Low-molecular-weight heparin (in comparison to unfractionated heparin) thromboprophylaxis lowered pulmonary embolism risk (hazard ratio, 0.51; 95% CI, 0.27-0.95; p = 0.034) while statin use in the preceding week lowered the risk of proximal leg deep vein thrombosis (hazard ratio, 0.46; 95% CI, 0.27-0.77; p = 0.004).
Failure of standard thromboprophylaxis using low-molecular-weight heparin or unfractionated heparin is more likely in ICU patients with elevated body mass index, those with a personal or family history of venous thromboembolism, and those receiving vasopressors. Alternate management or incremental risk reduction strategies may be needed in such patients.
确定 ICU 危重病患者抗凝血栓预防失败的危险因素。
血栓形成预测因子的多变量回归分析来自一项随机血栓预防试验。
六个国家的 67 个内科-外科 ICU。
3746 例内科-外科危重病患者。
所有患者均接受低分子量肝素或未分级肝素的抗凝血栓预防治疗，标准剂量。
评估了在危重病期间发生静脉血栓栓塞、近端腿部深静脉血栓形成和肺栓塞的独立预测因素。共有 289 名患者（7.7%）发生静脉血栓栓塞。血栓预防失败的预测因素，如静脉血栓栓塞的发展，包括个人或家族静脉血栓栓塞史（风险比，1.64；95%可信区间，1.03-2.59；p=0.04）和体重指数（风险比，每增加 10 点 1.18；95%可信区间，1.04-1.35；p=0.01）。体重指数的增加也是近端腿部深静脉血栓形成的预测因素（风险比，1.25；95%可信区间，1.06-1.46；p=0.007），182 名患者（4.9%）发生近端腿部深静脉血栓形成。47 名患者（1.3%）发生肺栓塞，与体重指数相关（风险比，1.37；95%可信区间，1.02-1.83；p=0.035）和血管加压素的使用（风险比，1.84；95%可信区间，1.01-3.35；p=0.046）。低分子量肝素（与未分级肝素相比）降低肺栓塞风险（风险比，0.51；95%可信区间，0.27-0.95；p=0.034），而他汀类药物在先前一周的使用降低了近端腿部深静脉血栓形成的风险（风险比，0.46；95%可信区间，0.27-0.77；p=0.004）。
在体重指数升高、有静脉血栓栓塞个人或家族史或接受血管加压素的 ICU 患者中，使用低分子量肝素或未分级肝素进行标准血栓预防治疗更有可能失败。可能需要在这些患者中采用替代管理或增量风险降低策略。
