The predictive value of symptoms for anxiety in hospice inpatients with advanced cancer
Bibliographic record
Abstract
ABSTRACTObjective:Insight into symptoms as predictors for anxiety may help to foster early identification of anxiety and to ameliorate anxiety management. The aim of this study was to determine which frequently occurring symptoms are predictors for anxiety in advanced cancer patients recently admitted to a hospice. METHOD: Symptom burden was measured in patients admitted to a hospice who died ≤3 month after admission using the Utrecht Symptom Diary. This is a Dutch-translated and adapted version of the Edmonton Symptom Assessment System to self-assess the 11 most prevalent symptoms and overall well-being on a 0-10 numerical rating scale. Multiple linear regression analysis was employed to analyze the predictive value of fatigue, nausea, pain, dyspnea, depressed mood, insomnia, and well-being on anxiety. RESULTS: A total of 211 patients were included, 42% of whom were men, and the median age was 71 years (range = 31-95). Anxiety was uncommon and rarely severe: 25% had a score ≥1, and 14% had a score >3. After correction for age, gender, and marital status, depressed mood (p = 0.00) and dyspnea (p = 0.01) were independent predictors for anxiety and explained 23% of the variance in anxiety. SIGNIFICANCE OF RESULTS: Hospice inpatients with advanced cancer who suffer from dyspnea and/or depressed mood are at increased risk for anxiety. Treatment of dyspnea and depressed mood may contribute to adequate anxiety management. Further research should explore other factors associated with anxiety, especially in the psychological, social, and spiritual domains.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".