Clinical Outcomes of Operating an Acute Palliative Care Unit at a Comprehensive Cancer Center
Bibliographic record
Abstract
PURPOSE: Acute palliative care units (APCUs) are inpatient services in tertiary hospitals that provide intensive symptom management and assist in hospital discharge for transitions to hospice care. We aimed to analyze the clinical outcomes of operating an APCU at a comprehensive cancer center. PATIENTS AND METHODS: We retrospectively reviewed the medical records of 1,440 consecutive patients admitted to the APCU and analyzed demographic and clinical information, discharge outcomes, symptom assessments using the Edmonton Symptom Assessment System, spiritual distress, and financial distress. RESULTS: The median age of patients was 67.0 (range, 23-97) years, and 41% were female. The most common primary cancer types were lung (21.9%), hepatopancreatobiliary (14.1%), and colorectal cancers (12.9%). The median length of stay was 8.0 days (range, 1-60 days), and 31.0% of patients died in the APCU. Death in the APCU showed a significant decrease over time, and overall inpatient death in oncology wards did not increase after APCU opening. In total, 44.7% of patients were discharged to government-certified hospice centers. The proportion of patients discharged to certified hospice centers increased from 32.2% in 2015 to 62.4% in 2018. Among 715 patients with a follow-up evaluation 1 week after admission, Edmonton Symptom Assessment System symptom scores, spiritual distress, and financial distress showed statistically significant improvements compared with the baseline symptom scores ( P < .001). This improvement was limited to patients who did not die in the APCU. CONCLUSION: Patients with advanced cancer admitted to the APCU may experience significant improvements in distressing symptoms. The majority of patients requiring transition to hospice were successfully transferred to certified hospice centers. The percentage discharged alive improved over time.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".