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Institute
Background: Healthy volunteer registry donors have become the backbone of stem cell transplantation programs. While most registrants will never become actual donors, a small minority are called upon twice, most commonly for the same patient because of poor graft function. Anecdotal evidence provides no hard reasons to disallow second-time mobilized apheresis, but few centers have treated enough two-time donors for definitive conclusions. Moreover, for reasons unknown, the efficiency of G-CSF varies greatly between donations.
Methods: Comparison of outcomes of first vs. second donations can formally confirm G-CSF responsiveness as intrinsically, likely genetically, determined. In our database, we identified 60 donors (1.3%) who received two cycles of G-CSF 24 days to 4 years apart and systematically compared mobilization outcomes.
Results: First and second mobilization and collection proceeded without severe or unusual adverse effects. First-time mobilization efficiency was highly predictive of second-time mobilization. Neither mobilization efficiency nor time lag between donations affected the similarity of first- and second-time mobilization outcomes.
Conclusions: With the caveat that only donors with an unremarkable first donation were cleared for a second, our data indicate that a second donation is feasible, equally tolerable as a first donation, and efficient. Moreover, the data strongly support the notion of donor-intrinsic variables dictating mobilization response and argue against relevant damage to the stem cell compartment during mobilization with rhG-CSF.
Background: The ability to approximate intra-operative hemoglobin loss with reasonable precision and linearity is prerequisite for determination of a relevant surgical outcome parameter: This information enables comparison of surgical procedures between different techniques, surgeons or hospitals, and supports anticipation of transfusion needs. Different formulas have been proposed, but none of them were validated for accuracy, precision and linearity against a cohort with precisely measured hemoglobin loss and, possibly for that reason, neither has established itself as gold standard. We sought to identify the minimal dataset needed to generate reasonably precise and accurate hemoglobin loss prediction tools and to derive and validate an estimation formula.
Methods: Routinely available clinical and laboratory data from a cohort of 401 healthy individuals with controlled hemoglobin loss between 29 and 233 g were extracted from medical charts. Supervised learning algorithms were applied to identify a minimal data set and to generate and validate a formula for calculation of hemoglobin loss.
Results: Of the classical supervised learning algorithms applied, the linear and Ridge regression models performed at least as well as the more complex models. Most straightforward to analyze and check for robustness, we proceeded with linear regression. Weight, height, sex and hemoglobin concentration before and on the morning after the intervention were sufficient to generate a formula for estimation of hemoglobin loss. The resulting model yields an outstanding R2 of 53.2% with similar precision throughout the entire range of volumes or donor sizes, thereby meaningfully outperforming previously proposed medical models.
Conclusions: The resulting formula will allow objective benchmarking of surgical blood loss, enabling informed decision making as to the need for pre-operative type-and-cross only vs. reservation of packed red cell units, depending on a patient’s anemia tolerance, and thus contributing to resource management.