Treatment of postherpetic neuralgia with 5% topical lidocaine plaster – experience from a small county hospital: case report
Bibliographic record
Abstract
Postherpetic neuralgia (PHN) characterized by chronic neuropathic pain is a common complication of herpes zoster. We investigated the efficacy, safety and cost of treating refractory chronic neuropathic pain with 5% topical lidocaine plaster (TLP) in a female patient attending pain unit at a small county hospital. An 80-year-old female diagnosed with PHN presented with severe left intercostal allodynia and hyperalgesia up to the root of the fourth to tenth thoracic dermatome. We administered the well established first- and second-line specific medications for PHN, but treatment regimens were not efficient. Then we introduced TLP and analyzed data from initial assessment and throughout follow up of 1313 days. The efficacy of treatment was based on pain severity that was assessed using the Short-Form McGill Pain Questionnaire and the related visual analog scale. In the last two years of observation, significant reduction was recorded in healthcare resource utilization (changes correlated with substantial reduction in direct cost (2012-2013: -425.90 €; and 2013-2014: -1,435 €) and clinically relevant reduction in pain severity. No unusual side effects were observed. In conclusion, treatment of PHN with 5% lidocaine plaster demonstrated efficacy in reducing pain severity and cost of medical care with a satisfactory safety profile. A starting point for future studies should be comparison of different treatment protocols and upgrading the knowledge, especially related to the cost of PHN treatment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".