A Retrospective Chart Review of Transfusion Practices in the Palliative Care Unit Setting
Bibliographic record
Abstract
BACKGROUND: There remains limited data in the literature on the frequency, clinical utility and effectiveness of transfusions in palliative care, with no randomized controlled trials or clinical practice guidelines on this topic. There are no routinely accepted practices in place for the appropriate transfusion of blood products in this setting. AIM: The aim of this study was to retrospectively review all transfusions in the palliative care units of 2, tertiary care hospitals in Canada. The goals were to elucidate the frequency, indications, patient characteristics, and practices around this intervention. DESIGN: Descriptive, retrospective chart review. SETTING/PARTICIPANTS: The clinical charts of patients admitted to the palliative care unit and who obtained blood transfusions for the period of April 1, 2015, to March 31, 2017, were reviewed. All patients admitted who obtained a transfusion were included. There were no exclusion criteria. RESULTS: Transfusions in the palliative care units were rare despite their availability (0.9% at Sunnybrook and 1.4% Baycrest) and were primarily given to patients with cancer. The main symptom issues identified for transfusion were fatigue and dyspnea. The majority of patients endorsed symptomatic benefit with minimal adverse reactions though pre- and post-transfusion assessment practices varied greatly between institutions. CONCLUSIONS: Transfusions in the palliative care units were infrequent, symptom targeted, and well tolerated, though the lack of standardized pre/post assessment tools limits any ability to draw conclusions about utility. Patients would benefit from additional research in this area and the development of clinical practice guidelines for transfusions in palliative care.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".