How do we operate a large monthly red blood cell exchange program.

BACKGROUND: Red blood cell (RBC) exchange for sickle cell disease presents unique difficulties due to RBC phenotyping, complex antibody work-ups, large number of RBC units required, and vascular access considerations, any of which can delay the procedure. Multidisciplinary coordination and systemic processes ensure that monthly appointments remain on schedule. STUDY DESIGN AND METHODS: A high-volume chronic RBC exchange program is described, highlighting the importance of multidisciplinary coordination and process improvement strategies involving initial referral, vascular access, order sets, and allocation of antigen-negative or phenotypically matched RBCs. RESULTS: Approximately 50 outpatient RBC exchanges are performed each month with an 82% kept-appointment rate. Specific factors for program success include open communication across services and improvements to referrals and standardized order sets. CONCLUSION: A combination of multidisciplinary coordination and process improvement can ensure the success of a high volume RBC exchange program. Frequent communication of upcoming appointments between the referring hematologists, the hemapheresis clinic, transfusion service, and interventional radiology is critical. Advance notice to the immunohematology reference lab of upcoming appointments is needed to allow enough time for allocating antigen-negative RBCs. Order sets can be leveraged to standardize and streamline RBC exchanges. Lastly, numerous mechanisms help patients compensate for the cognitive sequelae of stroke.

An unusual case of anti-D detection in two consecutive D+ patient samples: Antibody carryover on an automated gel platform.

BACKGROUND: Laboratory results can be affected by sample to sample carryover. Carryover of different analytes occurring in automated clinical chemistry, immunology, hematology, and molecular laboratories is well described. However, carryover in a transfusion service laboratory is not reported in medical literature. MATERIALS AND METHODS: Immunohematology testing results, demographic data, and clinical data were reviewed on three patients retrospectively from 2015 to 2019. RESULTS: Type and screen samples tested on automated gel platform from two D+ patients were affected by anti-D carryover from a patient sample with a very high-titer anti-D. Additional immunohematology and molecular testing confirmed that anti-D in samples of two D+ patients was due to carryover. CONCLUSION: A case of anti-D carryover caused false detection of anti-D in two D+ patients. Carryover can have implications for patient management. Transfusion laboratory staff need to be aware of it and investigate any unexpected results further.

Electronic patient identification for sample labeling reduces wrong blood in tube errors.

BACKGROUND: Wrong blood in tube (WBIT) errors are a preventable cause of ABO-mismatched RBC transfusions. Electronic patient identification systems (e.g., scanning a patient's wristband barcode before pretransfusion sample collection) are thought to reduce WBIT errors, but the effectiveness of these systems is unclear. STUDY DESIGN AND METHODS: Part 1: Using retrospective data, we compared pretransfusion sample WBIT rates at hospitals using manual patient identification (n = 16 sites; >1.6 million samples) with WBIT rates at hospitals using electronic patient identification for some or all sample collections (n = 4 sites; >0.5 million samples). Also, we compared WBIT rates after implementation of electronic patient identification with preimplementation WBIT rates. Causes and frequencies of WBIT errors were evaluated at each site. Part 2: Transfusion service laboratories (n = 18) prospectively typed mislabeled (rejected) samples (n = 2844) to determine WBIT rates among samples with minor labeling errors. RESULTS: Part 1: The overall unadjusted WBIT rate at sites using manual patient identification was 1:10,110 versus 1:35,806 for sites using electronic identification (p < 0.0001). Correcting for repeat samples and silent WBIT errors yielded overall adjusted WBIT rates of 1:3046 for sites using manual identification and 1:14,606 for sites using electronic identification (p < 0.0001), with wide variation among individual sites. Part 2: The unadjusted WBIT rate among mislabeled (rejected) samples was 1:71 (adjusted WBIT rate, 1:28). CONCLUSION: In this study, using electronic patient identification at the time of pretransfusion sample collection was associated with approximately fivefold fewer WBIT errors compared with using manual patient identification. WBIT rates were high among mislabeled (rejected) samples, confirming that rejecting samples with even minor labeling errors helps mitigate the risk of ABO-incompatible transfusions.

Unexpectedly Weak Anti-B in 2 Group O Pediatric Patients on Parenteral Nutrition and Disease Specific Supplemental Enteral Feeds.

Anti-A and anti-B antibodies are naturally occurring and develop from exposure to intestinal bacteria after age 4 to 6 months. In the laboratory, strong agglutination with A1 and B cells, or B cells only and A1 cells only, on reverse typing in a healthy person with immunocompetence is expected for patients with ABO types O, A, and B, respectively. However, absent or weak anti-A and anti-B antibodies can be observed in some clinical scenarios, such as patients with immunodeficiencies, newborns, elderly patients, and patients who have recently received bone marrow transplants. In this article, we report the cases of 2 pediatric patients with group O blood type who were receiving total parenteral nutrition (TPN) and disease-specific enteral feeds and who have strong anti-A and absent/weak anti-B.