system
Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: BACKGROUND, METHODS, RESULTS. Meshes: Blood Donors, Body Weight, Hematocrit, Humans, Linear Models, Models, Statistical, Platelet Count, Plateletpheresis, Time Factors.
user
Does a statistical model for estimating donor postdonation platelet count after plateletpheresis? Context: To avoid the need, in serial apheresis donors, either to delay plateletpheresis until a predonation platelet count is completed or to obtain a postdonation count after each procedure, a statistical model has been developed to predict the postdonation platelet count from the donor predonation platelet count, weight, and hematocrit. Predonation and postdonation platelet counts were measured in two groups of approximately 100 consecutive donors (Group A to test the model and Group B to validate it), and the postdonation counts were calculated with the model. Using stepwise multiple linear regression from donor data, estimated postdonation platelet counts were found to be comparable to the postdonation platelet counts actually measured. Estimated postdonation platelet counts x 10(9) per L (mean +/- SD) for each group, respectively, were Group A, 195 +/- 35, versus actual platelet counts of 195 +/- 39 (p = 0.43), and Group B, 183 +/- 36, versus actual platelet counts of 189 +/- 34 (p = 0.14). Sensitivity and specificity, respectively, were Group A, 57 and 99 percent and Group B, 62 and 99 percent.
assistant
For most serial apheresis donors, application of this predictor model should preclude the need to obtain an extra postdonation platelet count. Final Decision: yes