Delirium and its consequences in the specialized palliative care unit: Validation of the Korean version of Memorial Delirium Assessment Scale
Bibliographic record
Abstract
OBJECTIVES: Delirium is highly prevalent in patients with advanced cancer. This study aimed to investigate delirium rates and potential associated factors such as mortality in patients admitted to an acute palliative care unit (APCU). Our second aim was to validate the Korean version of the Memorial Delirium Assessment Scale (K-MDAS). METHODS: A total of 102 patients with advanced cancer, and who were admitted to the APCU, were assessed. Demographic data were collected alongside clinical diagnosis, Eastern Cooperative Oncology Group (ECOG) performance status, clinical symptoms according to the Edmonton Symptom Assessment System, history of smoking, alcohol use, hypnotic use, and daily dose of morphine were collected. The Confusion Assessment Method, the Delirium Rating Scale-Revised 98, and the K-MDAS were measured at admission and 1 week later. RESULTS: Twenty-four patients (23.52%) were diagnosed with delirium, and associated factors were old age (P = 0.007), higher ECOG (P = 0.011), and drowsiness (P < 0.001). The presence of delirium was an independent predictor of 1-month mortality; male gender, higher body mass index, and hypnotic use were also related to 1-month mortality. The K-MDAS had reliable internal consistency (α = 0.942) and showed sensitivity of 0.958 and specificity of 0.921 at the optimal cutoff score for diagnosing delirium of 9. CONCLUSIONS: Delirium was prevalent in patients admitted to the APCU and was associated with 1-month mortality. The K-MDAS showed acceptable reliability and validity and can be used to screen for delirium in a palliative care setting.
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 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 | 0.002 |
| 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 | 0.001 |
| 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".