Pharmaceutical Care Services, Ministry of National Guard Health Affairs (MNGHA), King Abdullah International Medical Research Center (KAIMRC), King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh, Saudi Arabia.
Research Office, King Abdullah International Medical Research Center (KAIMRC), King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), Ministry of National Guard Health Affairs (MNGHA), Riyadh, Kingdom of Saudi Arabia.
PLoS One. 2021 May 3;16(5):e0250502. doi: 10.1371/journal.pone.0250502. eCollection 2021.
Frequently used models, such as the HAS-BLED, ATRIA, ORBIT, and GARFIELD-AF evaluate the risk of bleeding when using an anticoagulant, for example warfarin, in patients with non-valvular atrial fibrillation. Limited studies are available reporting a model with a good discriminative ability to predict the bleeding risk score when using direct oral anticoagulants.
Patient data were collected from King Abdulaziz Medical City, King Fahad Cardiac Center, and Prince Sultan Cardiac Center in Riyadh, from outpatients, inpatients, or primary care clinics. In total, 1722 patients with a prescription for a new oral anticoagulant, Dabigatran, Rivaroxaban, or Apixaban, were enrolled. A resampling approach for variable selection was used and a five-fold cross-validation to assess the model fit and misclassification probabilities. The analysis used the receiver operating characteristics curve (ROC) and the concordance (c) statistic to assess the validation models' discriminative power. The final penalized likelihood parameters were used for the development of the risk prediction tool. The accuracy of a classification and the prediction are reported with the sensitivity, specificity, and Brier score.
Bleeding occurred in 11.15% of cases, of which 23.08% required a blood transfusion and 51.65% had a reduction in haemoglobin of more than 2 gm. The variable selection model identified 15 predictors associated with major bleeding. The discriminative ability of the model was good (c-statistic 0.75, p = 0.035). The Brier score of the model was 0.095. With a fixed cut-off probability value of 0.12 for the logistic regression equation, the sensitivity was 72.7%, and the specificity 66.3%.
This model demonstrated a good performance in predicting the bleeding risk in Arab patients treated with novel oral anticoagulants. This easy to use bleeding risk score will allow the clinician to quickly classify patients according to their risk category, supporting close monitoring and follow-up for high-risk patients, without laboratory and radiological monitoring.
在使用非瓣膜性心房颤动患者的抗凝药物（例如华法林）时，经常使用 HAS-BLED、ATRIA、ORBIT 和 GARFIELD-AF 等模型来评估出血风险。目前可用的研究有限，这些研究报告了一种具有良好区分能力的模型，可用于预测使用直接口服抗凝剂时的出血风险评分。
从利雅得的阿卜杜勒阿齐兹国王医疗城、法赫德国王心脏中心和苏尔坦亲王心脏中心的门诊、住院或初级保健诊所收集患者数据。共纳入 1722 名新处方达比加群、利伐沙班或阿哌沙班的口服抗凝药物患者。采用变量选择的重采样方法和五折交叉验证来评估模型拟合度和误分类概率。分析采用接受者操作特征曲线（ROC）和一致性（c）统计量评估验证模型的区分能力。最终使用惩罚似然参数开发风险预测工具。报告分类和预测的准确性包括敏感性、特异性和 Brier 评分。
11.15%的患者发生出血，其中 23.08%需要输血，51.65%的血红蛋白降低超过 2 克。变量选择模型确定了 15 个与大出血相关的预测因子。该模型的区分能力良好（c 统计量为 0.75，p=0.035）。模型的 Brier 评分为 0.095。在固定逻辑回归方程的截断概率值为 0.12 时，敏感性为 72.7%，特异性为 66.3%。
该模型在预测阿拉伯患者使用新型口服抗凝剂的出血风险方面表现出良好的性能。这种易于使用的出血风险评分将使临床医生能够根据患者的风险类别快速对患者进行分类，支持对高危患者进行密切监测和随访，无需实验室和影像学监测。
