Symptom burden and characteristics of patients who die in the acute palliative care unit of a tertiary cancer center.
Bibliographic record
Abstract
53 Background: Acute Palliative Care Units (ACPUs) are novel inpatient programs in tertiary care centers that provide aggressive symptom management and assist transition to hospice. However, patients often die in the APCU before successfully transferring to hospice. The aim of this study was to evaluate the symptom burden and characteristics of advanced cancer patients who die in the APCU. Methods: We retrospectively reviewed the medical records of all advanced cancer patients admitted to the APCU between April, 2015 and March, 2016 at a tertiary cancer center in Korea. Basic characteristics and symptom burden assessed by the Edmonton Symptom Assessment System (ESAS) were obtained from consultation upon APCU admission. Statistical analyses were conducted to compare patients who died in the APCU with those who were discharged alive. Results: Of the 267 patients analyzed, 87 patients (33%) died in the APCU. The median age of patients was 66 (range, 23-97). Patients who died in the APCU had higher ESAS scores of drowsiness (6 vs 5, P = 0.002), dyspnea (4 vs 2, P = 0.001), anorexia (8 vs 6, P = 0.014) and insomnia (6 vs 4, P = 0.001) compared to patients who discharged alive. Total symptom distress scores (SDS) were also significantly higher (47 vs 40, P = 0.001). Patients who died in the APCU were more likely to be male (odds ratio [OR] for female patients 0.38, 95% confidence interval [CI] 0.22-0.67, P < 0.001) and have higher ESAS scores of drowsiness (OR 2.08, 95% CI, 1.08-3.99, P = 0.029) and dyspnea (OR 2.19, 95% CI 1.26-3.80, P = 0.005). These patients showed significantly shorter survival after APCU admission (7 days vs 31 days, P < 0.001). Conclusions: Advanced cancer patients who die in the APCU are more likely to be male and have significantly higher symptom burden that include drowsiness and dyspnea. These patients show rapid clinical deterioration after APCU admission. More proactive and timely end-of-life care is needed for 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".