Evaluation of Quality of Life and Satisfaction of Patients with Neuropathic Pain and Breakthrough Pain: Economic Impact Based on Quality of Life
Bibliographic record
Abstract
OBJECTIVE: The study objective was to assess the quality of life and satisfaction with treatment of patients with chronic neuropathic pain (CNP) who experience breakthrough pain (BTP) and to assess its economic impact. DESIGN: Cross-sectional observational study. SETTING: Fifteen pain units from Spanish hospitals completed the study. PARTICIPANTS: A total of 124 patients with adequately controlled CNP who experienced BTP were enrolled into the study. INTERVENTION: No interventions were required. MAIN OUTCOME MEASURES: Quality of life was assessed using the SF12 v2 questionnaire, the results of which were used to calculate the estimated costs per patient and month and the SF-6D Health Utility Index. Patient satisfaction with treatment received for CNP and for BTP was assessed using a 10-point visual analogue scale. Other associated symptoms were analyzed using the ESAS (Edmonton Symptom Assessment System). RESULTS: Patients had a mean age of 60.2 years (95% CI 58.4-63.3), and 46.8% (58) were males. 18.9% (23) experienced their first episode of BTP. A severe impairment of the physical component of SF12v2 was noted, with 94% of patients below the mean score of the population, while 88% had values lower than normal for the mental component. Mean cost per patient and month was $679 and was significantly greater in males ($763 versus $606), 4.96 times greater than in healthy population, and approximately double the cost of patients with CNP in Spain. CONCLUSIONS: Occurrence of BTP in patients with CNP causes a substantial increase in healthcare costs which is significantly greater in older males.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".