Delirium, agitation, and symptom distress within the final seven days of life among cancer patients receiving hospice care
Bibliographic record
Abstract
OBJECTIVE: Knowledge of symptom prevalence and adequate assessment of such symptoms at the end of life is important in clinical practice. We determined the frequency and severity of symptom distress and delirium using the Edmonton Assessment Scale (ESAS) and the Memorial Delirium Assessment Scale (MDAS) and evaluated the clinical utility of the Nursing Delirium Screening Scale (Nu-DESC) as scored by a caregiver as a screening tool for delirium. METHOD: We conducted a secondary analysis of the data from a previous randomized controlled trial on parenteral hydration at the end of life of patients admitted to home hospice. Only patients that had assessments within the last week of life were included. We collected the ESAS, MDAS, Nu-DESC, and Richmond Agitation Sedation Scale (RASS) results. The sensitivity and specificity of the Nu-DESC were then calculated. RESULTS: Some 78 of 261 patients were included in our study, 62 (80%) of which had moderate-to-severe symptoms corresponding to an ESAS score >4. These symptoms include: 73 (94%) anorexia, 63 (81%) fatigue, 56 (73%) drowsiness, 58 (75%) decreased well-being, and 39 (51%) pain. Delirium was diagnosed in 34 (44%) of patients using the MDAS. The Nu-DESC was found to have a sensitivity of 35%, a specificity of 80%, a positive predictive value (PPV) of 58%, and an negative predictive value (NPV) of 61% when used by caregivers. SIGNIFICANCE OF RESULTS: Hospice patients at the end of life have a high rate of symptom distress and delirium. The Nu-DESC is not a reliable tool for screening delirium when scoring is conducted by a caregiver. Our study illustrates the need for routine use of assessment tools to improve 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 | 0.007 |
| 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 | 0.000 | 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".