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Record W4388841297 · doi:10.22246/jikm.2023.44.5.920

A Case of Postherpetic Neuralgia Treated with Korean Medicine, including Soeumin <italic>Bojungikgitang-gagambang</italic>

2023· article· en· W4388841297 on OpenAlexaboutno aff
Nayoung Kim, Tae-ju Kim, Min-jin Kwon, Yu-Ra Im, Dong Hwan Lee

Bibliographic record

VenueThe Journal of Internal Korean Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Venom Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePostherpetic neuralgiaAcupunctureNeuropathic painNeuralgiaPain scalePhysical therapyAlternative medicineAnesthesia

Abstract

fetched live from OpenAlex

Objectives: This study reports on the effect of Korean medicine treatment, including Soeumin <i>Bojungikgitang-gagambang</i>, on a patient with postherpetic neuralgia.Methods: The patient received Korean herbal medicine, pharmacopuncture treatment, and acupuncture treatment for 22 days. We assessed changes in symptoms due to the treatment using the Numeric Rating Scale (NRS), the McGill Pain Questionnaire-Short Form (SF-MPQ), and the European Quality of Life-5 Dimensions (EQ-5D) scale. We also measured the Leeds Assessment of Neuropathic Symptoms and Signs (LANSS) to distinguish neuropathic pain.Results: After treatment, the patient showed decreased NRS, SF-MPQ, and EQ-5D scores.Conclusion: The results indicate that Korean medicine treatment, including Soeumin <i>Bojungikgitang-gagambang</i>, is an effective management of symptoms in patients with postherpetic neuralgia.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.069
GPT teacher head0.372
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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