Association of impairments in activities of daily living (ADLs) with symptom burden, health care utilization, and survival among hospitalized patients with advanced cancer.
Bibliographic record
Abstract
203 Background: Hospitalized patients with cancer often have impaired ADLs related to age, comorbidities, and both cancer and treatment-related morbidity. However, the relationship between ADL impairment and patients’ symptom burden and clinical outcomes has not been well described. Methods: We prospectively enrolled patients with advanced cancer with unplanned hospitalizations at an academic medical center. Upon admission, nurses assessed patients’ ADLs (mobility, feeding, bathing, dressing, and grooming). We used the Edmonton Symptom Assessment Scale (ESAS) and Patient Health Questionnaire-4 to assess physical and psychological symptoms, comparing symptom burden between patients with and without ADL impairment. We used regression models adjusted for age, sex, education, Charlson comorbidity index, months since advanced cancer diagnosis, and cancer type to assess the relationship between any ADL impairment and hospital length of stay, the composite outcome of death or readmission within 90 days of discharge, and survival. Results: Among 932 patients, 40.2% had at least one ADL impairment. Patients with ADL impairment were older (67.2 vs. 60.8 years, p<0.001), had higher Charlson comorbidity index (1.1 vs. 0.7, p<0.001), and higher physical symptom burden (ESAS Physical 35.2 vs. 30.9, p<0.001). Those with ADL impairment were more likely to have moderate to severe constipation (46.7% vs. 36.0%, p<0.01), pain (74.9% vs. 63.1%, p<0.01), drowsiness (76.6% vs. 68.3%, p<0.01), as well as symptoms of depression (38.3% vs. 23.6%, p<0.01) and anxiety (35.9% vs. 22.4%, p<0.01). In adjusted models, ADL impairment was associated with longer hospital length of stay (B=1.30, p<0.01), higher odds of death or readmission within 90 days (odds ratio=2.26, p<0.01), and worse survival (hazard ratio=1.73, p<0.01). Conclusions: Hospitalized patients with advanced cancer who have ADL impairment experience a significantly higher symptom burden and worse health outcomes compared to those without ADL impairment. These findings highlight the need to assess and address ADL impairment among this population to enhance their quality of life and care.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".