Trigeminal Neuralgia Treated With Pregabalin in Family Medicine Settings: Its Effect on Pain Alleviation and Cost Reduction
Bibliographic record
Abstract
The purpose of this study is to analyze the effect of pregabalin (PGB) on pain alleviation, use of health care and non-health care resources, and associated costs in patients with trigeminal neuralgia under usual clinical practice in primary care settings. Sixty-five PGB-naïve patients receiving PGB as monotherapy (n = 36, 55%) or combined with other drugs (n = 29, 45%) fulfill criteria for inclusion in a secondary analysis from a 12-week, multicenter, observational prospective study aimed to ascertain the cost of illness in subjects with neuropathic pain. Pain is evaluated using the Short Form McGill Pain Questionnaire. Use of health care and non-health care resources and lost workdays equivalents (LWDEs) are also recorded. PGB significantly reduces pain scores, use of health care resources (ancillary tests and unscheduled medical visits), and number of LWDEs. Additional cost of PGB treatment (+euro 174 +/- 106) is broadly compensated for by a reduction in both health care costs (-euro 621 +/-1211, P < .001) and indirect costs (-euro 1210 +/- 1141, P < .001). It is concluded that PGB as monotherapy or combined with other drugs is effective in pain management in patients with trigeminal neuralgia and reduces the cost of illness.
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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) | 0.001 | 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) | 0.002 | 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".