Palliative Care Needs of Seriously Ill, Older Adults Presenting to the Emergency Department
Bibliographic record
Abstract
OBJECTIVES: The objective was to identify the palliative care needs of seriously ill, older adults in the emergency department (ED). METHODS: The authors conducted a cross-sectional structured survey. A convenience sample of 50 functionally impaired adults 65 years or older with coexisting cancer, congestive heart failure, end-stage liver or renal disease, stroke, oxygen-dependent pulmonary disease, or dementia was recruited from an urban academic tertiary care ED. Face-to-face interviews were conducted using the Needs Near the End-of-Life Screening Tool (NEST), McGill Quality of Life Index (MQOL), and Edmonton Symptom Assessment Survey (ESAS) to assess 1) range and severity of symptoms, 2) goals of care, 3) psychological well-being, 4) health care utilization, 5) spirituality, 6) social connectedness, 7) financial burden, 8) the patient-clinician relationship, and 9) overall quality of life (QOL). RESULTS: Mean (±SD) age was 74.3 (±6.5) years and cancer was the most common diagnosis. Mean (±SD) QOL on the MQOL was 3.6 (±2.9). Over half of the patients exceeded intratest severity-of-needs cutoffs in four categories of the NEST: physical symptoms (47/50, 94%), finances (36/50, 72%), mental health (31/50, 62%), and access to care (29/50, 58%). The majority of patients reported moderate to severe fatigue, pain, dyspnea, and depression on the ESAS. CONCLUSIONS: Seriously ill, older adults in an urban ED have substantial palliative care needs. Future work should focus on the role of emergency medicine and the new specialty of palliative care in addressing these needs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".