Practice review: Evidence-based and effective management of anaemia in palliative care patients
Bibliographic record
Abstract
BACKGROUND: Anaemia is a common sequela of advanced disease and is associated with significant symptom burden. No specific guidance exists for the investigation and management of anaemia in palliative care patients. AIM: We aim to offer a pragmatic overview of the approaches to investigate and manage anaemia in advanced disease, based on guidelines and evidence in disease specific patient groups, including cancer, heart failure and chronic kidney disease. DESIGN: Scoping review methodology was used to determine the strength of evidence supporting the investigation and management of anaemia in patients with advanced disease. DATA SOURCES: A search for guidelines was performed in 2020. National or international guidelines were examined if they described the investigation or management of anaemia in adult patients with health conditions seen by palliative care services written within the last 5 years in the English language. Searches of MEDLINE, the Cochrane library and WHO guidance were made in 2019 to identify key publications that provided additional primary data. RESULTS: Evidence supports patient-centred investigation of anaemia, results of which should guide targeted intervention. Blanket use of blood transfusion should be avoided, with evidence supporting a more restrictive approach to transfusion. Routine use of oral iron and erythropoetin stimulating agents (ESAs) are not recommended. Insufficient evidence exists to determine the effectiveness of IV iron in this patient group. CONCLUSION: We advocate early consideration and investigation of anaemia, guided by symptom burden and patient preferences. Correction of reversible causes should be the mainstay of treatment, with a restrictive approach to blood transfusion. Research is required to evaluate the efficacy of IV iron in these patients.
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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 | 0.013 | 0.104 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".