“End-of-life blood transfusion can improve quality of life”—a narrative review of debate on scope and consideration
Bibliographic record
Abstract
Background and Objective: The European Society for Medical Oncology has defined the term “end-of-life” in their clinical practice guideline as care for people with advanced disease once they have reached a point of rapid physical decline, typically the last few weeks or months before and inevitable death as a natural result of a disease. End-of-life care is often delivered at home, hospital, or in hospice facilities, while palliative care can be provided in various settings. Blood transfusions provide symptomatic relief and improve subjective well-being of end-of-life or hospice care patients. The objective of this study was to narrate the accessibility of transfusion facilities, different guidelines, and policy issues in ‘end-of-life’ patients. Methods: We performed literature search on “PubMed” and “Google Scholar” within 1994–2024 using search terms “blood transfusion” OR “blood product” AND “end-of-life” OR “terminal illness” OR “palliative” OR “advanced diseases” OR “hospice care” OR “terminal care”, “actively dying”. A narrative review is conducted to assess the potential benefits of transfusion in end-of-life care patients in comparison to adverse outcomes, associated guidelines for end-of-life transfusion, potential barriers to these services and to resolve myths associated in this service pathway. Key Content and Findings: Patients having hematological or non-hematological malignancies and suffering from anemia or thrombocytopenia, and other transfusion-dependent chronic conditions like hemoglobinopathies are important candidates for end-of-life transfusion support. The potential barriers for end-of-life blood transfusion have been identified as reimbursement issues, lack of knowledge of physicians, unavailable round the clock facilities, and to some extent transportation issues. Administration of treatment in home environment is evolving over the last few decades to decrease hospital-acquired infection risks and substantial reduction of medical costs and it is a potentially feasible option. Conclusions: Home transfusion, also called out-of-hospital transfusion is a great alternative for transfusion dependent chronically ill patients for whom it is difficult to receive blood transfusion in traditional hospital setting. However, further research is needed to establish the effectiveness of end-of-life transfusion, resolve certain ethical queries like appropriate usage of blood products, as well as organizational and economic issues.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".