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Record W4309352493 · doi:10.5009/gnl220350

Clinical Characteristics of Korean Patients with Elderly-Onset Crohn’s Disease: Results from the Prospective CONNECT Study

2022· article· en· W4309352493 on OpenAlexaboutno aff
You Sun Kim, Min Jeong Na, Byong Duk Ye, Jae Hee Cheon, Jong Pil Im, Joo Sung Kim

Bibliographic record

VenueGut and Liver · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsnot available
FundersKorea Disease Control and Prevention Agency
KeywordsMedicineProspective cohort studyInternal medicineCrohn's diseaseCohortAge of onsetYoung adultDiseaseCohort studyPediatricsGastroenterology

Abstract

fetched live from OpenAlex

The clinical course and prognosis of patients with elderly-onset Crohn's disease (CD) remain unclear. This study aimed to analyze the clinical characteristics and outcomes of elderly-onset CD patients from the prospective CONNECT study cohort, a nationwide, multicenter cohort study of patients with CD in Korea. Among a total of 1,175 patients in the prospective CONNECT study cohort, 94 patients (Montreal age A3) were included and divided into two groups according to their age at diagnosis: the elderly-onset group (diagnosed with CD after 60 years of age, n=26, 67.54±6.7 years) and late adult-onset group (diagnosed as CD at age 41 to 59 years, n=68, 48.06±5.1 years). The elderly-onset group was characterized by a lower Crohn's disease activity index at diagnosis (124.89±101.9 vs 189.55±128.6, p=0.023) and higher rates of previous anti-tuberculosis treatment (34.6% vs 4.4%, p<0.001) than the late adult-onset group. Compared with the late adult-onset group, the elderly-onset group showed a significantly less use of thiopurines (p=0.003), as well as anti-tumor necrosis factor-alpha agents (p=0.047). Additionally, the elderly-onset group was less likely to require bowel resection than the late adult-onset group (p=0.067), suggesting that elderly-onset CD patients in Korea appear to have more favorable clinical outcomes than late adult-onset CD patients.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.004
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.240
Teacher spread0.231 · 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 teacher head, 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

Citations2
Published2022
Admission routes1
Has abstractyes

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