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Record W4391218361 · doi:10.1093/ibd/izae020.049

LEUCINE-RICH ALPHA 2 GLYCOPROTEIN: A USEFUL BIOMARKER TO DISCRIMINATE SMALL INTESTINAL MUCOSAL HEALING IN C-REACTIVE PROTEIN-NEGATIVE CROHN’S DISEASE

2024· article· en· W4391218361 on OpenAlexaboutno aff
Akihito Tanaka, Shuji Kanmura, Nobuhisa Maeda, Kosuke Kuwazuru, Fukiko Komaki, Yuga Komaki, Akio Ido

Bibliographic record

VenueInflammatory Bowel Diseases · 2024
Typearticle
Languageen
FieldMedicine
TopicClusterin in disease pathology
Canadian institutionsnot available
Fundersnot available
KeywordsBiomarkerCrohn's diseaseGlycoproteinMedicineAlpha (finance)DiseaseCrohn diseaseImmunologyPathologyBiologyMolecular biologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract BACKGROUND The treatment goals for inflammatory bowel disease, including Crohn's disease (CD), have shifted from clinical remission to mucosal healing. However, frequent endoscopies burden patients. Leucine-rich alpha 2 glycoprotein (LRG), produced by hepatocytes, neutrophils, and the intestinal epithelium, is more gut-specific than C-reactive protein (CRP). We examined whether LRG, as a biomarker, can detect small intestinal mucosal healing in CD patients, especially in those who are CRP-negative. METHOD 1) This study examined CD patients who visited our department from May 2021 to April 2023, had LRG measured, and underwent image evaluation using capsule endoscopy or balloon-assisted endoscopy. We analyzed their clinical background, looked for a correlation between LRG and CRP, assessed the ROC-AUC of LRG and CRP for mucosal healing, and measured the LRG and CRP cutoff values to determine mucosal healing. 2) Next, in CRP-negative CD patients, we analyzed the ROC-AUC of LRG for mucosal healing and LRG cutoff value to determine mucosal healing. Endoscopic evaluation was done within 3 months before and after LRG measurement. Absent open ulcers indicated mucosal healing. The upper limit of normal CRP value was <3 mg/L. We used the Spearman correlation coefficient to determine the correlation. RESULTS 1) Here, 67 CD patients were analyzed; 43 (64%) were men. The median age (range) of onset was 25.6 (3-57) years. The median disease duration (range) was 7.6 (0-27) years. B1, B2, and B3 of Montreal Classification were established in 31 (46.2%), 21 (31.3%), and 15 (22.3%) patients, respectively. The median (range) of LRG was 21.7 (7.6-67.4) μg/mL. The median (range) of CRP was 10.8 (0.0-86.9) mg/L. LRG and CRP were strongly correlated (r=0.878, p<0.001). The ROC-AUC of LRG for mucosal healing was 0.839 (95% confidence interval [CI] 0.760-0.918). LRG cutoff value for discriminating mucosal healing was 15.5 μg/mL (sensitivity 77%, specificity 75%). The ROC-AUC of CRP for mucosal healing was 0.811 (95% CI 0.721-0.900). The CRP cutoff value to differentiate mucosal healing was 0.9 mg/L (sensitivity 55%, specificity 90%). 2) Forty CRP-negative CD patients were analyzed; 23 (57%) were men. The median age (range) of onset was 21.9 (3-57) years. The median disease duration (range) was 7.0 (0-27) years. B1, B2, and B3 of Montreal Classification were established in 17 (42.5%), 12 (30.0%), and 11 (27.5%) patients, respectively. The median (range) of LRG was 12.3 (7.6-23.5) μg/mL. The ROC-AUC of LRG for mucosal healing was 0.817 (95% CI 0.696-0.938). The LRG cutoff value to differentiate mucosal healing was 14.1 μg/mL (sensitivity 61%, specificity 76%). CONCLUSION LRG may be a better biomarker than CRP for assessing endoscopic remission of the small intestinal mucosa in CD. In CRP-negative CD patients, LRG level of ≥14.1 μg/mL could indicate small intestinal ulcers.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.030
GPT teacher head0.298
Teacher spread0.268 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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