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Record W2369992726

Trigeminal neuralgia treatment with lujingningfang

2011· article· en· W2369992726 on OpenAlexaboutno aff
Zhenzhong Zhang

Bibliographic record

VenueAnhui Medical and Pharmaceutical Journal · 2011
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Venom Research
Canadian institutionsnot available
Fundersnot available
KeywordsCarbamazepineTrigeminal neuralgiaMedicineStatistical significanceAnesthesiaCorneal reflexTreatment and control groupsSignificant differenceClinical significanceNeuralgiaReflexInternal medicineEpilepsyNeuropathic painPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Aim To observe the clinical effects of trigeminal neuralgia treatment with lujingningfang.Methods First,Fifty-eight patients were divided into treatment group and control group according to the selecting order.Patients in treatment group were treated with carbamazepine and lujingningfang.Patients in control group were treated only with carbamazepine.Then,the scores of Simplified McGill Table,change of EMG and blink reflex indexes were observeds.Results As for Scores of Simplified McGill Table,PRI feeling score and total score of treatment group were lower than those of control group and of statistical significance(P0.05).The comparative result of scores difference as well as the result of pain relief of treatment group was better than control group and of statistical significance(P0.05).As for blink reflex,significant improvement was shown in R1 and R2 of involvement side in both groups.However,better improvement was shown in treatment group with significant difference(P0.05).Conclusion Using lujingningfang with carbamazepine to treat trigeminal neuralgia has better clinical curative effect than using carbamazepine only.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.229
GPT teacher head0.451
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2011
Admission routes1
Has abstractyes

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