Associação da Intensidade de Dor no Tempo Até à Morte dos Doentes Oncológicos Referenciados aos Cuidados Paliativos
Bibliographic record
Abstract
INTRODUCTION: Pain is a common symptom experienced by cancer patients, especially in those with advanced disease. Our aim was to describe pain intensity in advanced cancer patients, referred to the palliative care unit, the factors underlying moderate to severe pain and its prognostic values. MATERIAL AND METHODS: This was a prospective observational study. All patients with mestastatic solid tumors and with no specific oncologic treatment were included. Pain intensity was accessed using the pain scale from Edmonton Symptom Assessment Scale, rated from 0 to 10 on a numerical scale, where zero = no pain and 10 = worst possible pain. RESULTS: Between October 2012 and June 2015, a total of 301 patients participated in the study. The median age was 69 years, (37 - 94); most of the patients were men (57%) and 64.8% had a performance status of 3/4. About 42% reported pain severity ≥ 4 and 74% were medicated with opioids. Multivariate analysis indicated a correlation between performance status and reported pain (OR: 1.7; IC 95%: 1.0 - 2.7; p = 0.045). Median overall survival was 37 days (IC 95%: 28 - 46). Patients reporting moderate to severe pain (pain severity ≥ 4) had a median survival of 29 days (IC 95%: 21 - 37), comparing with those who had no or moderate pain with median survival of 49 days (IC 95%: 35 - 63) (p = 0.022). DISCUSSION: The performance status was associated with more intense pain. The performance status, hospitalization, intra-abdominal metastization and opioid analgesia were associated with shorter time to death in advanced cancer patients referred to palliative care. CONCLUSION: Cancer pain continues to be a major clinical problem in advanced cancer 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 | 0.001 | 0.006 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".