The need for palliative and support care services for heart failure patients in the community
Bibliographic record
Abstract
BACKGROUND: Palliative care is a care option considered appropriate for those with heart failure, but is uncommon partially due to a lack of timely identification of those needing palliative care. A standard mechanism that triggers which heart failure patients should receive palliative care is not available. The Gold Standards Framework (GSF) identifies those needing palliative care but has not been investigated with heart failure patients. OBJECTIVES: To describe palliative care provided in the community and determine whether the GSF can identify heart failure patients in need of palliative care. METHODS: Descriptive study. A total of 252 heart failure patients in the community completed a demographic characteristics questionnaire, the Edmonton symptom assessment scale-revised and the Minnesota living with heart failure questionnaire. Clinical data were collected from the medical chart and the primary physician completed the GSF prognostic indicator guidance. RESULTS: Participants had a mean age of 76.9 years (standard deviation 10.9), most at New York Heart Association level III (n=152, 60%). Fewer than half received pain medications (n=76, 30%), anxiolytics (n=35, 14%), antidepressants (n=64, 25%) or sleep medications (n=65, 26%). Eight patients spoke with a psychologist or psychologist (3%). One had an advanced directive and 16 (6%) had a record of discussions with their family caregivers. Three (1%) had end-of-life discussions with their healthcare providers. Most healthcare providers responded 'no' to the 'surprise question' (n=160, 63%). Sensitivity and specificity of the gold standards framework was poor. CONCLUSIONS: Few community dwelling heart failure patients received most aspects of palliative care. The gold standards framework was not a good indicator of those who should receive 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".