Department of Donor Studies, Sanquin Research, Nijmegen, The Netherlands.
Transfusion. 2012 Dec;52(12):2559-69. doi: 10.1111/j.1537-2995.2012.03655.x. Epub 2012 Apr 23.
Each year, approximately 5% of the invited blood donors is eventually deferred from donation because of low hemoglobin (Hb) levels. Estimating the risk of Hb deferral in blood donors can be helpful in the management of the donation program. We developed and validated a prediction model for Hb deferral in whole blood donors, separately for men and women.
Data from a Dutch prospective cohort of 220,946 whole blood donors were used to identify predictors for Hb deferral using multivariable logistic regression analyses. Validity of the prediction models was assessed with a cross-validation.
A total of 12,865 donors (5.8%) were deferred because of a low Hb level. The strongest predictors of Hb deferral were Hb level measured at the previous visit, age, seasonality, difference in Hb levels between the previous two visits, time since the previous visit, deferral at the previous visit, and the total number of whole blood donations in the past 2 years for both men and women. The prediction models had an area under the receiver operating characteristic curve of 0.89 for men and 0.84 for women. Cross-validation showed similar results and good calibration.
Using a limited number of easy-to-measure characteristics enables a good prediction of Hb deferral risk in whole blood donors. The prediction models may guide the decision which donors to invite for a next donation and for which donors the invitation should be postponed. Potentially, this could decrease the number of Hb deferrals in blood donors.
每年约有 5%的受邀献血者因血红蛋白 (Hb) 水平低而最终被拒绝献血。估计献血者 Hb 不合格的风险有助于管理献血计划。我们分别为男性和女性开发并验证了一种全血献血者 Hb 不合格预测模型。
使用荷兰前瞻性队列 220946 名全血献血者的数据,通过多变量逻辑回归分析确定 Hb 不合格的预测因素。通过交叉验证评估预测模型的有效性。
共有 12865 名献血者(5.8%)因 Hb 水平低而被拒绝。Hb 不合格的最强预测因素是上一次就诊时测量的 Hb 水平、年龄、季节性、前两次就诊时 Hb 水平的差异、上次就诊后的时间间隔、上一次就诊时的不合格以及过去两年内的全血献血次数对于男性和女性都是如此。男性和女性的预测模型的受试者工作特征曲线下面积分别为 0.89 和 0.84。交叉验证显示了类似的结果和良好的校准。
使用少数易于测量的特征可以很好地预测全血献血者 Hb 不合格的风险。预测模型可以指导邀请哪些献血者进行下一次献血,以及应推迟邀请哪些献血者。这可能会减少血液中 Hb 不合格的献血者数量。