ANALYSIS OF COMMON SYMPTOMS USING THE EDMONTON SYMPTOM ASSESSMENT SYSTEM IN TERMINALLY ILL CANCER PATIENTS RECEIVING PALLIATIVE CARE AT A TERTIARY CARE CENTER OF NEPAL
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: The Edmonton Symptom Assessment System (ESAS) is a reliable tool to assess the severity of Symptom over time. It evaluates nine symptoms commonly experienced by patients with cancer and other advanced illness. The aim of this study is to find the prevalent symptoms, intensity and prognostic significance of common symptoms in cancer patients. Methods: This prospective cross-sectional study enrolled 110 patients with terminal cancer receiving palliative care admitted at clinical oncology department of Bir Hospital. Patients providing informed written consent were advised to complete ESAS questionnaire within 24 hours of hospital admission. Data entry and analysis done in Microsoft Excel Version 2013. Frequency distributions, percentages, means, and standard deviations of various symptoms were analyzed. Scatter diagram was prepared to evaluate the time trend of all nine ESAS items toward death. Results: One hundred ten patients (mean age 53.76 ± 10.63 years, 70 female and 40 male) completed ESAS score questionnaire. The most common symptom experienced was poor well-being 97(88.18%), followed by tiredness 91(82.72%) and lack of appetite 88(80%). Most severe symptoms were poor well-being with a mean score of 5.27 ± 3.08, followed by tiredness (3.55 ± 2.46), pain (3.24 ± 2.61) and lack of appetite (3.15 ± 2.53) and all the symptoms tend to deteriorate towards end of life. Conclusions: Edmonton Symptom Assessment System (ESAS) can be used easily to assess common symptoms and their intensity in cancer patients which help to provide specific symptom directed treatment and care.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it