Streamlining Apheresis: A Dual‐Intervention Quality Improvement Initiative to Increase the Efficiency in Stem Cell Collection
Bibliographic record
Abstract
ABSTRACT Autologous stem cell transplantation ( ASCT ) requires efficient collection of peripheral blood stem cells. At London Health Sciences Centre ( LHSC ), high‐risk multiple myeloma patients are routinely booked for three‐day apheresis collections to meet higher CD34 + cell count targets, though many do not require all scheduled days, leading to resource inefficiencies. A quality improvement initiative was implemented to reduce unnecessary apheresis sessions through two interventions: (1) lowering CD34 + cell count target thresholds (from 6 × 10 6 to 5 × 10 6 cells/kg for tandem collections and from 3 × 10 6 to 2.5 × 10 6 for single collections), and (2) increasing total blood volume ( TBV ) processed from 3× to 4× for patients within certain target thresholds. Two Plan‐Do‐Study‐Act ( PDSA ) cycles were conducted between March 2024 and March 2025 involving 76 patients. Outcome measures included collection days saved and cost savings, and post‐transplant engraftment times served as a balancing measure. A total of 39.4% of patients avoided at least one collection day due to these interventions. Third‐day collection usage in high‐risk myeloma patients decreased from 25% to 5.9%. Mean collection days fell significantly in this group (2.21–1.8; p = 0.0015), with total cost savings of CAD $72 734.97. No significant differences were observed in neutrophil or platelet engraftment times, confirming preserved clinical efficacy. Implementing lower CD34 + cell count targets and increased TBV processing significantly reduced apheresis sessions and costs without compromising engraftment outcomes. These changes have become the standard of care at LHSC and may serve as a feasible model for other transplant centers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".