Red blood cell transfusion in myelodysplastic syndromes: A systematic review
Bibliographic record
Abstract
Patients with myelodysplastic syndrome (MDS) frequently receive red blood cell (RBC) transfusions for anaemia resulting from ineffective erythropoiesis. While RBC transfusions may rapidly increase haemoglobin values, their impact on clinical and health services outcomes in MDS patients has not previously been summarized. We conducted a systematic review of the literature to evaluate risks and benefits of RBC transfusions in MDS patients. We searched electronic databases (MEDLINE, Embase, CENTRAL, CINAHL) from inception through June 4, 2021 to identify studies reporting data on RBC transfusions in MDS patients. Full text publications that assessed RBC transfusions as an intervention and reported at least one clinical, laboratory, or healthcare outcome associated with transfusion were included. Study characteristics, transfusion information and transfusion-related outcomes were extracted and reported. We identified 1243 original studies, of which 38 met eligibility requirements and were included. Fourteen reported on survival following diagnosis of MDS, with the majority reporting poorer survival among patients receiving or requiring more frequent transfusions. Nine reported on transfusion-related iron overload and its complications. Other outcomes included rates of allo/autoimmunization and adverse transfusion reactions, and healthcare costs incurred by patients with a greater transfusion burden. Only two studies reported on symptom relief following transfusion. This review underscores transfusion dependence as a negative prognostic factor for MDS patients and highlights the paucity of evidence surrounding quality of life and symptom-related outcomes following RBC transfusions in this population. Further study of patient-important outcomes associated with transfusion in MDS patients is warranted to improve therapeutic recommendations and inform resource allocation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".