Transfusion Medicine Department, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Key Lab of High Confidence Software Technologies (Peking University), Ministry of Education School of Computer Science, Peking University, Beijing, China.
Transfus Apher Sci. 2023 Dec;62(6):103791. doi: 10.1016/j.transci.2023.103791. Epub 2023 Aug 22.
Vasovagal response (VVR) is the most common adverse reaction during blood donation and it is the main element for the safety of the patients with preoperative autologous blood donation (PABD). Accurate identification high-risk group is of great significance for PABD. Our study aimed to establish a scoring system based on the nomogram to screen the high-risk population and provide evidence for preventing the occurrence of VVRs.
A number of 4829 patients underwent PABD between July 2017 and June 2020 in the first medical center of Chinese PLA Hospital were recruited, 3387 of whom were included in the training group (70 %; 108 VVRs patients vs 3279 Non-VVRs patients), 1442 were included in the validation group (30 %; 46 VVRs patients vs 1396 Non-VVRs patients). The data were analyzed by univariate and multivariate logistic regression. The nomogram of the scoring system was created by using the RMS tool in R software.
Seven variables including BMI, hematocrit, pre-phlebotomy heart rate and systolic blood pressure, history of blood donation, age group and primary disease were selected to build the nomogram, which was shown as prediction model. And the score was 0-1 for BMI, 0-2 for hematocrit, systolic blood pressure, heart rate and no blood donation history, 0-10 for age, 0-3 for primary disease. When the total cutoff score was 11, the predictive system for identifying VVRs displayed higher diagnostic accuracy. The area under the curve, specificity, and sensitivity of the training group were 0.942, 82.41 % and 97.17 %, respectively, whereas those of the validation group were 0.836, 78.26 % and 78.15 %, respectively.
A risk predictive scoring system was successfully developed to identify high-risk VVRs group form PABD patients that performed well.
血管迷走性反应（VVR）是献血过程中最常见的不良反应，也是术前自体采血（PABD）患者安全的主要因素。准确识别高危人群对 PABD 具有重要意义。本研究旨在建立一种基于列线图的评分系统，以筛选高危人群，为预防 VVR 的发生提供依据。
回顾性分析 2017 年 7 月至 2020 年 6 月在中国人民解放军总医院第一医学中心行 PABD 的 4829 例患者的临床资料，其中 3387 例（70%）纳入训练组（108 例 VVR 患者与 3279 例非 VVR 患者），1442 例（30%）纳入验证组（46 例 VVR 患者与 1396 例非 VVR 患者）。采用单因素和多因素逻辑回归分析筛选变量，利用 R 软件中的 RMS 工具建立评分系统的列线图。
筛选出 7 个变量（BMI、血细胞比容、采血前心率和收缩压、献血史、年龄组和原发疾病）构建列线图预测模型，其中 BMI 评分为 0-1 分，血细胞比容、收缩压、心率和无献血史评分为 0-2 分，年龄评分为 0-10 分，原发疾病评分为 0-3 分。当总分截点为 11 分时，预测 VVR 的系统具有较高的诊断准确性。训练组曲线下面积、特异度和敏感度分别为 0.942、82.41%和 97.17%，验证组分别为 0.836、78.26%和 78.15%。
成功建立了一种风险预测评分系统，能够识别 PABD 患者中发生 VVR 的高危人群，具有较好的预测性能。
