Prevalence of distressing symptoms in hospitalised patients on medical wards: A cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Many patients with advanced, serious, non-malignant disease belong to the population generally seen on medical wards. However, little research has been carried out on palliative care needs in this group. The aims of this study were to estimate the prevalence of distressing symptoms in patients hospitalised in a Department of Internal Medicine, estimate how many of these patients might be regarded as palliative, and describe their main symptoms. METHODS: Cross-sectional (point prevalence) study. All patients hospitalised in the Departments of Internal Medicine, Pulmonary Medicine, and Cardiology were asked to do a symptom assessment by use of the Edmonton Symptom Assessment System (ESAS). Patients were defined as "palliative" if they had an advanced, serious, chronic disease with limited life expectancy and symptom relief as the main goal of treatment. RESULTS: 222 patients were registered in all. ESAS was completed for 160 patients. 79 (35.6%) were defined as palliative and 43 of them completed ESAS. The patients in the palliative group were older than the rest, and reported more dyspnea (70%) and a greater lack of wellbeing (70%). Other symptoms reported by this group were dry mouth (58%), fatigue (56%), depression (41%), anxiety (37%), pain at rest (30%), and pain on movement (42%). CONCLUSION: More than one third of the patients in a Department of Internal Medicine were defined as palliative, and the majority of the patients in this palliative group reported severe symptoms. There is a need for skills in symptom control on medical wards.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".