MétaCan
Menu
Back to cohort
Record W4312192307 · doi:10.1155/2022/6106993

Efficacy of Traditional Chinese Medicine on Animal Model of IgA Nephropathy: A Systematic Review and Meta-Analysis

2022· review· en· W4312192307 on OpenAlexaff
Tianying Chang, Hongan Wang, Yinping Wang, Jinhui Ma, Di Zou, Shoulin Zhang, Lehana Thabane

Bibliographic record

VenueEvidence-based Complementary and Alternative Medicine · 2022
Typereview
Languageen
FieldMedicine
TopicRenal Diseases and Glomerulopathies
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster UniversityImpact
FundersPeople's Government of Jilin ProvinceNational Natural Science Foundation of ChinaNatural Science Foundation of Jilin Province
KeywordsMeta-analysisMedicineNephropathyTraditional Chinese medicineAnimal modelTraditional medicineInternal medicineAlternative medicinePathologyEndocrinology

Abstract

fetched live from OpenAlex

Objective. Traditional Chinese medicine (TCM) has a long history in the treatment of Immunoglobulin A nephropathy (IgAN). A large number of animal experiments focused on the TCM treatment of IgAN are conducted every year. The evidence for these preclinical studies is not clear. This study summarized and evaluated the results of animal experiments on TCM treatment for IgAN. Methods. We systematically searched animal studies from 6 databases from inception to August 30, 2022. We included Chinese studies from the key magazine of China technology. The quality of the included studies was evaluated with the SYRCLE animal experimental bias risk assessment tool and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE). Results. Out of 832 records identified in the initial search, 30 studies were selected. The results indicated that, compared with the control group, the TCM treatment group improved 24 h urine protein (24 h-UP) level (standardized mean difference (SMD) 3.57, 95% confidence interval (CI) 4.48 to 2.66, <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi>P</a:mi> <a:mo>&lt;</a:mo> <a:mn>0.001</a:mn> </a:math> ), urine red blood cell (U-RBC) (SMD 13.66, 95% CI 17.99 to 9.32, <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" id="M2"> <c:mi>P</c:mi> <c:mo>&lt;</c:mo> <c:mn>0.001</c:mn> </c:math> ), serum creatinine (Scr) (mean difference (MD) 10.89, 95% CI 17.00 to 4.77, <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" id="M3"> <e:mi>P</e:mi> <e:mo>&lt;</e:mo> <e:mn>0.001</e:mn> </e:math> ), blood urea nitrogen (BUN) (MD 2.44, 95% CI 3.42 to 1.47, <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" id="M4"> <g:mi>P</g:mi> <g:mo>&lt;</g:mo> <g:mn>0.001</g:mn> </g:math> ), tumor necrosis factor-α (TNF-α) (MD 171.28 to 95% CI 323.68 to 18.88, <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" id="M5"> <i:mi>P</i:mi> <i:mo>=</i:mo> <i:mn>0.03</i:mn> </i:math> ), transforming growth factor-β1 (TGF-β) (SMD 4.02, 95% CI 7.26 to 0.77, <k:math xmlns:k="http://www.w3.org/1998/Math/MathML" id="M6"> <k:mi>P</k:mi> <k:mo>=</k:mo> <k:mn>0.02</k:mn> </k:math> ), matrix metalloproteinase-9/tissue inhibitors of metalloproteinase-1(MMP-9/TIMP-1) (MD 0.03, 95% CI 0.00 to 0.06, <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" id="M7"> <m:mi>P</m:mi> <m:mo>=</m:mo> <m:mn>0.02</m:mn> </m:math> ), nephrin mRNA (SMD 3.39, 95% CI 2.59 to 4.18, <o:math xmlns:o="http://www.w3.org/1998/Math/MathML" id="M8"> <o:mi>P</o:mi> <o:mo>&lt;</o:mo> <o:mn>0.001</o:mn> </o:math> ). However, there is no difference in albumin level (MD 1.10, 95% CI 0.06 to 2.26, <q:math xmlns:q="http://www.w3.org/1998/Math/MathML" id="M9"> <q:mi>P</q:mi> <q:mo>=</q:mo> <q:mn>0.06</q:mn> </q:math> ) and interleukin-6 (IL-6) (MD 170.77, 95% CI 365.3 to 23.75, <s:math xmlns:s="http://www.w3.org/1998/Math/MathML" id="M10"> <s:mi>P</s:mi> <s:mo>=</s:mo> <s:mn>0.09</s:mn> </s:math> ). Conclusions. TCM can improve 24 h-UP, U-RBC, Scr, BUN, MMP-9/TIMP-1, TNF-α, TGF-β, and nephrin mRNA of IgAN animal models. Moreover, there is a need for rigorous reporting of preclinical research methodology, which is essential to support the quality of preclinical research. Registration. This review was registered with a systematic review record CRD42020171404 in the PROSPERO database.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.692
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0120.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.355
GPT teacher head0.423
Teacher spread0.068 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations8
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueEvidence-based Complementary and Alternative MedicineSame topicRenal Diseases and GlomerulopathiesFrench-language works237,207