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Record W2792667478 · doi:10.1093/jcag/gwy008.095

A94 USE OF LOW-DOSE CTE IN PREDICTING ACTIVE INFLAMMATION IN CROHN’S PATIENTS WITH INTERMEDIATE FECAL CALPROTECTIN LEVELS

2018· article· en· W2792667478 on OpenAlexaff
O. Gerami, J. A. Brown, Patrick M. Vos, Jonathon Leipsic, T Lee, Robert Enns, Brian Bressler, Greg Rosenfeld

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCalprotectinMedicineInternal medicineGastroenterologyBiomarkerGold standard (test)Inflammatory bowel diseaseInflammationCohortDiseaseLogistic regressionCrohn's diseaseFaecal calprotectin

Abstract

fetched live from OpenAlex

Crohn’s disease (CD) is a condition that affects young individuals. Clinically assessed disease activity by a Gastroenterologist is the gold standard for identifying patients with active inflammation and relapse. Fecal Calprotectin (FC) is a biomarker that is an independent indicator of active inflammation. Bressler et al has shown that FC levels <100 µg/g strongly predict quiescent CD, and those >250 µg/g strongly predict active inflammation/relapse. FC levels between 100–250 µg/g is an indeterminate zone that warrants further testing to confirm the presence/absence of disease. Computed tomography enterography (CTE) is a proposed next test. Recent research has shown that low-dose CTE using model-based iterative reconstruction (MBIR) is non-inferior to standard dose CTE for identifying signs of small bowel inflammation. To assess the utility of MBIR CTE signs, in patients with intermediate FC levels, for predicting those who would have active inflammation on clinical assesment. A single-center, retrospective cohort study of 163 patients subjected to clinical assessment, FC measurement and low dose CTE to evaluate CD activity between November 2012 & February 2015. The CTE studies for each patient were reviewed by two radiologists for radiographic findings of small bowel CD inflammation. Clinically assessed disease activity by a Gastroenterologist served as the reference standard. Multivariate logistic regression was used to build a scoring equation based on FC levels & radiographic signs to predict active disease in the reference standard. Of the 163 patients, 92 (56%) patients had active inflammation based on clinical assessment. Sixty-five (71%) of the 92 patients clinically diagnosed with active inflammation also had CTE that was deemed active by overall radiologist impression. Fifty (70%) of the 71 patients clinically diagnosed with inactive inflammation also had CTE that was deemed inactive by overall radiologist impression. Sensitivity, specificity, PPV & NPV of overall radiologic impression for CD activity was 0.70, 0.71, 0.75, 0.65, respectively. 138 patients had measured FC levels. Seventy-eight (57%) had clinically active disease & 60 (43%) had clinically inactive disease. In those with active disease, 16 (20%), 13(17%) & 49(63%) had FC levels <100 µg/g, 100–250 µg/g, >250 µg/g, respectively. In those with inactive disease, 53 (88%), 7(12%) & 0(0%) had FC levels <100 µg/g, 100–250 µg/g, >250 µg/g, respectively. An equation based on mural stratification & FC level predicted active disease the best. This equation had a sensitivity, specificity, PPV, NPV & accuracy of 0.82, 0.90, 0.91, 0.79 & 0.85, respectively. In patients with FC levels between 101–250, MBIR CTE is a reasonable further test to confirm the presence/absence of disease None

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)0.002
metaresearch head score (Gemma)0.006
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 score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.010
GPT teacher head0.223
Teacher spread0.213 · 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
Published2018
Admission routes1
Has abstractyes

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