Snapshot of symptoms of advanced cervical cancer patients referred to the palliative care service in a cancer center in Mexico
Bibliographic record
Abstract
OBJECTIVE: To report the clinical and demographic characteristics of patients with advanced cervical cancer referred to the palliative care service (PC) at a major cancer center in Mexico. METHODS: This is a retrospective cohort study of patients with advanced cervical cancer referred to the PC of INCan, between January 2011 and December 2015. Demographic and clinical characteristics at the time of admission to the INCan, time to referral to PC, initial Edmonton Symptom Assessment System evaluation, and follow up were recorded. RESULTS: In all, 359 patients were included, median age 51 years, predominantly poor with low education. Most patients 322 (90%) received tumor-specific treatment; presence of nephrostomies and other tumor-related complication was frequent. Median time to referral was 335 days, more than 180 (50%) had five or more symptoms, pain and fatigue were the most prevalent. CONCLUSION: Women with advanced cervical cancer have a high burden of symptoms; PC is only considered at the end of life. Efforts for an early referral to PC should be made.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".