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Record W4207032305 · doi:10.1093/ibd/izac015.134

IBD MIMICS PRESENTED AT IBD LIVE: WHEN IT IS NOT INFLAMMATORY BOWEL DISEASE

2022· article· en· W4207032305 on OpenAlexaboutno aff
Chris Ward, Shiraz A. Shah, Francis A. Farraye, Alka Goyal, John S. Hanson, Stefan D. Holubar, Andrew Watson, Steven D. Wexner, David G. Binion, Jill Gaidos, Tracy L. Hull, Badr Al‐Bawardy, Jana Hashash, Myron Brand, Tanya Bruckel, Kofi Clarke, Benjamin L. Cohen, Raymond K. Cross, Jeffrey Dueker, Sean Fine, E Förster, Hans Herfath, Colleen Kelly, Mark Lazarev, L. Campbell Levy, Amy L. Lightner, Taha Qazi, Joel R. Rosh, Abbas Rupawala, Corey A. Siegel, Miguel Regueiro

Bibliographic record

VenueInflammatory Bowel Diseases · 2022
Typearticle
Languageen
FieldMedicine
TopicIgG4-Related and Inflammatory Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInflammatory bowel diseaseUlcerative colitisInternal medicineGastroenterologySarcoidosisColitisDifferential diagnosisDiseasePathology

Abstract

fetched live from OpenAlex

Abstract BACKGROUND A group of Inflammatory Bowel Disease (IBD) specialists have been utilizing a weekly live video conference “IBD Live” to discuss multidisciplinary management of challenging cases. Since 2009 the conference has featured robust interactive case discussions among 150-200 gastroenterologists and colorectal surgeons from multiple academic institutions. Although the majority of cases presented are IBD, there have been a number of cases where IBD was not the ultimate diagnosis. Hence, we sought to characterize these “IBD mimics” to provide a structure for differential diagnosis. METHODS All 106 hours of case conferences recorded and archived between May 2018 and June 2021 were reviewed. A total of 183 of the 215 cases discussed had an IBD diagnosis including 124 Crohn’s disease (CD), 54 ulcerative colitis (UC) and 5 IBD unclassified. RESULTS Many of the remaining 32 (14.9%) cases (Table 1) were referred to a specialist with a prior diagnosis of IBD. There were 10 cases of colonic inflammation initially diagnosed as UC. Etiologies included drug-induced colitis secondary to checkpoint inhibitors for cancers, ocrelizumab for multiple sclerosis, and nintedanib for pulmonary fibrosis. There were cases of ischemic colitis, idiopathic myointimal hyperplasia of mesenteric veins, segmental colitis associated with diverticulosis, and diversion colitis. There were 8 cases of systemic diseases, diagnosed as Common Variable Immunodeficiency, sarcoidosis and vasculitis, including cases of Henoch–Schönlein purpura and CTLA4 haploinsufficiency with autoimmune infiltrates. There were 5 cases of ileal disorders, ultimately diagnosed as lymphoma, tuberculosis, Meckel’s diverticulum, and appendiceal carcinoid all previously thought to be CD. There were small bowel mucosal disorders including collagenous sprue and autoimmune enteropathy, and 2 polyposis cases secondary to Cronkhite-Canada and juvenile polyposis syndromes. There were also cases thought to be penetrating complications of CD, including a case of abdominal actinomyces infection. Finally, there were 3 cases where no consensus diagnosis was made, with broad differential diagnoses including cryptogenic multifocal ulcerous stenosis enteritis. CONCLUSIONS IBD mimics were found in 15% of cases presented at a global IBD webinar in a 3-year period. Clinicians should have a high level of suspicion and actively pursue alternative etiologies when patients do not respond as anticipated to IBD therapy and/or when the disease characteristics are not completely consistent with IBD. These non-IBD diagnoses will lead to a significant change in medical, surgical and pharmacological treatment approaches, which will impact total cost, unplanned care and quality. Our IBD Live conference has positively impacted the care of our patients, and magnified the importance of considering a broad differential for IBD "mimics."

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0170.002

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 head0.013
GPT teacher head0.247
Teacher spread0.233 · 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; both teacher heads agree on what is shown here.

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
Published2022
Admission routes1
Has abstractyes

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