Symptoms in palliative care inpatient and ımpact of palliative care unit on symptom control
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to determine the symptoms observed during admission to palliative care in patients that would be provided palliative support, to measure their intensity, and to evaluate the effect of palliative care on patient symptoms by recording changes during the first week after admission to hospital. METHODS: The sample of the study was determined as 108 according to the population mean significance test conducted by using preliminary application data. Patients who were able to complete the Edmonton Symptom Assessment Scale during admission to hospital, on the 3(rd) and 7(th) days of hospitalization were included into the evaluation. The Introductory Characteristics Questionnaire, Edmonton Symptom Assessment Scale and Palliative Performance Scale were used for the collection of the data. RESULTS: While 50% of the patients defined pain intensity as 5 and over during admission, this rate was determined to be 6.5% on the 7(th) day. Mean values of the symptoms of pain, insomnia, loss of appetite, and status of well-being decreased significantly on the 3(rd) and 7(th) days after admission compared to the time of admission to the hospital. Besides, no statistically significant difference was found among the symptoms of nausea, anxiety, shortness of breath, and constipation. CONCLUSION: In this study, it was determined that the intensity of symptoms deteriorating the life quality of cancer patients such as pain, fatigue, insomnia, loss of appetite, and status of well-being improved rapidly with palliative care support.
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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 | 0.000 | 0.004 |
| 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) | 0.002 | 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".