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Record W3133258115 · doi:10.2188/jea.je20200540

Assessing the Relationship Between High-sensitivity C-reactive Protein and Kidney Function Employing Mendelian Randomization in the Japanese Community-based J-MICC Study

2021· article· en· W3133258115 on OpenAlexaff
Ryosuke Fujii, Asahi Hishida, Takeshi Nishiyama, Masahiro Nakatochi, Keitaro Matsuo, Hidemi Ito, Yuichiro Nishida, Chisato Shimanoe, Yasuyuki Nakamura, Tanvir Chowdhury Turin, Sadao Suzuki, Miki Watanabe, Rie Ibusuki, Toshiro Takezaki, Haruo Mikami, Yohko Nakamura, Hiroaki Ikezaki, Masayuki Murata, Kiyonori Kuriki, Nagato Kuriyama, Daisuke Matsui, Kokichi Arisawa, Sakurako Katsuura‐Kamano, Mineko Tsukamoto, Takashi Tamura, Yoko Kubo, Takaaki Kondo, Yukihide Momozawa, Michiaki Kubo, Kenji Takeuchi, Kenji Wakai

Bibliographic record

VenueJournal of Epidemiology · 2021
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsUniversity of Calgary
FundersRIKENJapan Society for the Promotion of ScienceMinistry of Education, Culture, Sports, Science and TechnologyJapan Agency for Medical Research and Development
KeywordsMendelian randomizationMedicineRenal functionConfidence intervalInternal medicineSingle-nucleotide polymorphismKidney diseaseOncologyGeneticsGeneGenetic variantsGenotypeBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Inflammation is thought to be a risk factor for kidney disease. However, whether inflammatory status is either a cause or an outcome of chronic kidney disease remains controversial. We aimed to investigate the causal relationship between high-sensitivity C-reactive protein (hs-CRP) and estimated glomerular filtration rate (eGFR) using Mendelian randomization (MR) approaches. METHODS: explained 3.4% and 3.9% of the variation in hs-CRP, respectively. RESULTS: : 0.001; 95% CI, -0.036 to 0.036). CONCLUSION: Our two-sample MR analyses with different IVs did not support a causal effect of hs-CRP on eGFR.

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)0.035
metaresearch head score (Gemma)0.042
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0020.001
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 head0.128
GPT teacher head0.388
Teacher spread0.260 · 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
Published2021
Admission routes1
Has abstractyes

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Same venueJournal of EpidemiologySame topicAdipokines, Inflammation, and Metabolic DiseasesFrench-language works237,207