Assessment of psycho-emotional symptoms in cancer patients in an Oncology-Palliative Care Department from Romania
Bibliographic record
Abstract
Introduction. Anxiety and depression have an increased prevalence in cancer patients, especially in those in an advanced stage of the disease. These disorders have a major impact on the social life, existential concerns and quality of life of cancer patients. Materials and Methods. A number of 114 consecutive patients were included in the study (in a period of 2 weeks) who were screened for anxiety, depression and for other common symptoms, using Hospital Anxiety and Depression Scale (HADS) and Edmonton Symptom Assessment System (ESAS). Results. Regarding the age - the abnormal level of anxiety and depression: the percentage of patients over 65 years was higher than the percentage of patients under 64 years, both in terms of anxiety and depression. Regarding the Performance status ECOG - abnormal level of anxiety and depression: the percentage of patients with ECOG = 3-4 is higher than that of patients with ECOG = 0-2. Results. The increased prevalence of anxiety and depression requires psychological counseling and treatment. It is important for these symptoms to be identified as soon as possible, in order to provide a good quality of life. Conclusions. The model we propose is for the HADS to be a screening tool on admission to a palliative care ward, for certain categories of patients.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".