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S922 Multicenter Validation of Screening Tool for Diagnosing Non-Alcoholic Fatty Liver Disease in Patients with Crohn’s Disease

2022· article· en· W4316077385 on OpenAlexaffabout
Eric Prado, Yasi Xiao, Ankita Tirath, Carl Kay, Mithun Sharma, Giada Sebastiani, Matthew A. Ciorba, Nicholas O. Davidson, Anish Patel, Talat Bessisow, Rupa Banerjee, Scott McHenry, Parakkal Deepak

Bibliographic record

VenueThe American Journal of Gastroenterology · 2022
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsMcGill University Health CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineInternal medicineGastroenterologySteatosisFatty liverNonalcoholic fatty liver diseaseTransient elastographyGold standard (test)Logistic regressionDiseaseProspective cohort studyLiver biopsyBiopsy

Abstract

fetched live from OpenAlex

Introduction: Crohn’s Disease (CD) patients are twice as likely compared to controls to develop nonalcoholic fatty liver disease (NAFLD) leading to increased risk of cardiometabolic complications. Given this, we developed the first clinical screening tool for NAFLD in CD, Clinical Predictor for NAFLD in CD (CPN-CD) which uses readily accessible laboratory and clinical parameters. We have demonstrated CPN-CD outperforms the Hepatic Steatosis Index in detecting NAFLD in CD in an internal cohort. Here we performed a multicenter analysis to externally validate CPN-CD against transient elastography (TE) and establish its diagnostic accuracy to detect NAFLD in patients with CD at two different controlled attenuation parameter (CAP) thresholds. Methods: A total of 454 patients with CD across four prospective cohorts from tertiary IBD centers across United States, Canada and India were included in the study. Of these, 412 patients were screened with TE only to determine prevalence of hepatic steatosis while 42 were screened with additional gold standard magnetic resonance imaging derived proton density fat fraction (MRI-PDFF), where hepatic steatosis was defined as ≥ 5.5% fat density, then reflexed to TE. To evaluate discriminative ability of CPN-CD to screen for NAFLD, patients were split into two CAP categories on TE; CAP ≥ 248 dB/m or ≥ 300 dB/m. Results: In the four cohorts, the prevalence of NAFLD ranged from 32% to 76%. Using logistic regression, the relationship of CPN-CD to CAP ≥ 248 dB/m and CAP ≥ 300 dB/m revealed C-statistic 0.80 (0.75 – 0.84) and 0.79 (0.73 – 0.85) respectively. However, at CAP ≥ 300 dB/m, CPN-CD had higher specificity (74%) and NPV (80%) compared to CAP ≥ 248 dB/m (Table). For the group who first underwent screening MRI-PDFF the yield of finding NAFLD was 2- to 6-fold higher compared to TE alone. Conclusion: CPN-CD provides fair discrimination to detect NAFLD determined on TE at CAP ≥ 300 dB/m in an external validation study conducted in four multinational cohorts. Future directions include synchronous MRI-PDFF and TE to recalibrate the score to improve specificity and then test generalizability in ulcerative colitis. Table 1. - Diagnostic accuracy of CPN-CD in detecting NAFLD in CD patients using transient elastography as reference standard CAP ≥ 248 dB/m CAP ≥ 300 dB/m Sensitivity 36% 29% Specificity 17% 74% PPV 21% 22% NPV 30% 80% CAP, controlled attenuation parameter; CD, Crohn’s disease; CPN-CD, clinical predictor tool for NAFLD in Crohn’s disease; NPV, negative predictive value; PPV, positive predictive value.

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)0.007
metaresearch head score (Gemma)0.012
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 score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.250
Teacher spread0.238 · 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
Published2022
Admission routes2
Has abstractyes

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