Characteristics and outcomes of patients admitted to the acute palliative care unit (APUC) from the emergency center (EC) versus inpatient transfers (IP).
Bibliographic record
Abstract
e20581 Background: Most patients admitted to APCU are transferred from inpatient oncology units. We hypothesized that EC admissions have different symptom burden and outcomes compared to IP patients. In this retrospective cohort study, we compared the symptom burden and survival between the EC and IP groups. Methods: Among all 2,568 patients admitted to our APCU between September 1, 2003 and August 31, 2008, 312 (12%) were EC patients. We randomly selected 298 IP patients as controls. We retrieved the patient demographics, cancer diagnosis, Edmonton Symptom Assessment Scale (ESAS), discharge outcomes, and overall survival from time of admission. Results: EC patients were more like to be black (22% v 11%, p=0.0006) and less likely to have hematologic cancer (5% v 14%, p=0.0003). EC patients had higher pain (5.4 v 4.6, p=0.0004), fatigue (6.7 v 6.1, p=0.0049), nausea (2.7 v 1.6, p<0.0001), insomnia (4.8 v 4.2, p=0.03) and were less likely to be delirious (41% v 55%, p=0.001). EC patients had more public insurance (44% v 38%, p=0.0142), more home discharge (29% v 11%, p=0.0001), longer admission (8 v 7 days, p=0.0002), and were 2.3x as likely to be discharged alive as compared to IP patients (p<0.0001, Wald Chi-square test). Kaplan-Meier plots and log-rank test for survival from admission of APCU for EC and IP groups were not statistically significant (Median survival after admission were 34 v 31 days, p=0.08). In multivariate analysis, EC admission (OR= 1.9, 1.2-3.0), wellbeing (OR=1.12, 1.02-1.23), dyspnea (OR=0.85, 0.79-0.92) and delirium (OR=0.39, 0.24-0.64) were independently significant for being discharge alive. The c-statistic value was 0.71. Conclusions: EC patients have higher acute symptom burden, but more likely to be discharged alive as compared to IP transfer patients. The APCU is successful at managing symptoms and facilitating discharge to the community for EC patients. [Table: see text]
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".