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Record W2371874718

The Effect of Yi-Shen-Huo-Xue Yin(YSHXY)Plus Arsenic Trioxide on Multiple Myeloma Lytic Bone Disease

2009· article· en· W2371874718 on OpenAlexaff
Yongzhen Hu

Bibliographic record

VenueLiaoning zhongyi zazhi · 2009
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsMedicineRANKLOsteoprotegerinMultiple myelomaInternal medicineBone painArsenic trioxideBone remodelingBone resorptionN-terminal telopeptideEndocrinologyBone diseaseAlkaline phosphataseOsteoporosisOsteocalcinActivator (genetics)ReceptorArsenicBiochemistryChemistry
DOInot available

Abstract

fetched live from OpenAlex

Objective:Observe the effect of Yi-Shen-Huo-Xue Yin(YSHXY)on the bone matabolism of multiple myeloma bone disease.Methods:30 patients were randomized to recieve YSHXY plus Arsenic Trioxide(AT),or only AT for 6 months respectively.Bone pain were evaluated by VAS count,and bone matabosism were tested by serum albumin-adjusted calcium,urinary N-telopeptide/creatinine(NTx/Cr),serum bone-specific alkaline phosphatase(bALP),serum receptor activator of NF-kappa B ligand(RANKL),serum osteoprotegerin(OPG),and RANKL/OPG.Results:YSHXY plus AT improved bone pain and bone matabolism indices(NTx/Cr,bALP,RANKL,OPG,RANKL/OPG),while AT only decreased bone pain and serum RANKL level.YSHXY plus AT was more effective than AT on Multiple Myeloma Lytic Bone Disease.Conclusion:YSHXY is an efficient decoction for multiple myeloma bone disease.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.374
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.013
GPT teacher head0.294
Teacher spread0.281 · 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 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
Published2009
Admission routes1
Has abstractyes

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