Patient-Reported Outcomes in Subjects with Painful Trigeminal Neuralgia Receiving Pregabalin: Evidence from Medical Practice in Primary Care Settings
Bibliographic record
Abstract
Effects of pregabalin (PGB) on patient-reported health outcomes were assessed in 65 PGB-naive subjects with trigeminal neuralgia refractory to previous analgesic therapy in a prospective, multicentre observational study carried out in primary care. Twelve weeks' monotherapy with PGB (n = 36) or add-on (n = 29), reduced baseline intensity of pain by a mean +/- S.D. of -40.0 +/- 22.1 mm [-55.4%, effect size (ES) 2.32; P < 0.0001] with 59.4% of responders (pain reduction >or= 50%), and produced 34.6 +/- 29.3 additional days with no/mild pain. Anxiety/depression symptoms decreased by -3.8 +/- 3.5 and -4.5 +/- 4.2 points (ES 0.95 and 1.02; P < 0.0001), respectively. PGB improved sleep by -17.9 +/- 19.6 points (ES 1.18; P < 0.0001) and improved patient functioning (Sheehan Disability Index) by decreasing overall scoring by -8.6 +/- 5.9 points (ES 1.59; P < 0.0001). Health state (EQ-5D) increased by 31.6 +/- 22.2 mm (ES 1.67; P < 0.0001), with 0.0388 +/- 0.0374 gained quality-adjusted life-years. In spite of the small sample size, results support the effectiveness of PGB for the improvement in pain and related health symptoms.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".