Association of Functional Status and Symptom Severity Among Patients Who Received Palliative Care Consultations
Bibliographic record
Abstract
Background:The relationship between functional status and the severity of different symptoms in patients with serious illnesses has not been explored in detail. Methods:We retrospectively evaluated registry data of hospitalized patients who received inpatient palliative care consults at the Mount Sinai Health System between January 01, 2020, and December 31, 2022. The registry was approved by the local institutional review board. During the initial consult, palliative care clinicians administered the Australia-modified Karnofsky Performance Status (KPS) and the Edmonton Symptom Assessment System (ESAS). We extracted these measures and other variables of interest from electronic health records and billing data, and assessed the association of functional status and symptom severity for different symptoms using ordinal logistic regression models. Results:The study included 9800 patients who received a palliative care consult. When modeling the association of functional status and the severity of different symptoms, two distinct groups of symptoms emerged: Nausea, physical discomfort, anxiety, depression, and constipation were more prevalent and severe among patients with higher functional status. Conversely, drowsiness, inactivity, dyspnea, anorexia, and agitation were more prevalent and severe among patients with lower functional status. These findings remained statistically significant after adjusting for possible confounders. Conclusion:Among patients who received inpatient palliative care consults, lower functional status was associated with a higher symptom burden. Furthermore, symptom profiles differed between patients with reduced functional status and those with preserved functional status.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".