A comparison of the prevalence of dry mouth and other symptoms using two different versions of the Edmonton Symptom Assessment System on an inpatient palliative care unit
Bibliographic record
Abstract
BACKGROUND: Symptom assessment is key to effective symptom management and palliative care for patients with advanced cancer. Symptom prevalence and severity estimates vary widely, possibly dependent on the assessment tool used. Are symptoms specifically asked about or must the patients add them as additional symptoms? This study compared the prevalence and severity of patient-reported symptoms in two different versions of a multi-symptom assessment tool. In one version, three symptoms dry mouth, constipation, sleep problems were among those systematically assessed, while in the other, these symptoms had to be added as an "Other problem". METHODS: This retrospective cross-sectional study included adult patients with advanced cancer at an inpatient palliative care unit. Data were collected from two versions of the Edmonton Symptom Assessment System (ESAS): modified (ESAS-m) listed 11 symptoms and revised (ESAS-r) listed 9 and allowed patients to add one "Other problem". Seven similar symptoms were listed in both versions. RESULTS: In 2013, 184 patients completed ESAS-m, and in 2017, 156 completed ESAS-r. Prevalence and severity of symptoms listed in both versions did not differ. In ESAS-m, 83% reported dry mouth, 73% constipation, and 71% sleep problems, but on ESAS-r, these symptoms were reported by only 3%, 15% and < 1%, respectively. Although ESAS-r severity scores for these three symptoms were higher than on ESAS-m, differences did not reach statistical significance. CONCLUSION: We identified significant differences in patient symptom reporting based on whether symptoms like dry mouth, obstipation and sleep problems were specifically assessed or had to be added by patients as an "Other problem".
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".