Blood and Transplant Research Unit in Donor Health and Behaviour, Cambridge, UK.
Dept of Public Health & Primary Care, University of Cambridge, Cambridge, UK.
Transfusion. 2023 Mar;63(3):541-551. doi: 10.1111/trf.17277. Epub 2023 Feb 16.
Deferrals due to low hemoglobin are time-consuming and costly for blood donors and donation services. Furthermore, accepting donations from those with low hemoglobin could represent a significant safety issue. One approach to reduce them is to use hemoglobin concentration alongside donor characteristics to inform personalized inter-donation intervals.
We used data from 17,308 donors to inform a discrete event simulation model comparing personalized inter-donation intervals using "post-donation" testing (i.e., estimating current hemoglobin from that measured by a hematology analyzer at last donation) versus the current approach in England (i.e., pre-donation testing with fixed intervals of 12-weeks for men and 16-weeks for women). We reported the impact on total donations, low hemoglobin deferrals, inappropriate bleeds, and blood service costs. Personalized inter-donation intervals were defined using mixed-effects modeling to estimate hemoglobin trajectories and probability of crossing hemoglobin donation thresholds.
The model had generally good internal validation, with predicted events similar to those observed. Over 1 year, a personalized strategy requiring ≥90% probability of being over the hemoglobin threshold, minimized adverse events (low hemoglobin deferrals and inappropriate bleeds) in both sexes and costs in women. Donations per adverse event improved from 3.4 (95% uncertainty interval 2.8, 3.7) under the current strategy to 14.8 (11.6, 19.2) in women, and from 7.1 (6.1, 8.5) to 26.9 (20.8, 42.6) in men. In comparison, a strategy incorporating early returns for those with high certainty of being over the threshold maximized total donations in both men and women, but was less favorable in terms of adverse events, with 8.4 donations per adverse event in women (7.0, 10,1) and 14.8 (12.1, 21.0) in men.
Personalized inter-donation intervals using post-donation testing combined with modeling of hemoglobin trajectories can help reduce deferrals, inappropriate bleeds, and costs.
由于血红蛋白水平低而导致的献血者和献血服务的延迟既耗时又昂贵。此外，接受低血红蛋白献血者的献血可能代表着一个重大的安全问题。减少这种情况的一种方法是结合献血者特征和血红蛋白浓度来确定个性化的献血间隔。
我们使用了来自 17308 名献血者的数据，通过离散事件模拟模型比较了使用“献血后”检测（即根据上次献血时血液分析仪测量的血红蛋白值来估计当前的血红蛋白值）与英国目前的方法（即男性 12 周、女性 16 周的固定间隔的献血前检测）来确定个性化的献血间隔。我们报告了对总献血量、因血红蛋白低而被延迟献血、不适当的出血和血液服务成本的影响。个性化的献血间隔是通过混合效应模型来确定的，以估计血红蛋白的轨迹和跨越血红蛋白献血阈值的概率。
该模型具有较好的内部验证，预测事件与观察到的事件相似。在 1 年的时间里，采用个性化策略，要求至少有 90%的概率超过血红蛋白阈值，可使男女两性的不良事件（因血红蛋白低而被延迟献血和不适当的出血）和女性的成本降到最低。与目前的策略相比，女性的不良事件每例献血量从 3.4（95%置信区间 2.8，3.7）提高到 14.8（11.6，19.2），男性从 7.1（6.1，8.5）提高到 26.9（20.8，42.6）。相比之下，纳入那些极有可能超过阈值的献血者早期返回策略可以使男女两性的总献血量最大化，但在不良事件方面的效果较差，女性每例不良事件的献血量为 8.4（7.0，10.1），男性为 14.8（12.1，21.0）。
使用献血后检测结合血红蛋白轨迹建模的个性化献血间隔可以帮助减少延迟献血、不适当的出血和成本。
