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99 Inflammatory Bowel Disease in Eldery Patients: Epidemiology and Clinical Characteristics in a Tertiary Brazilian Public Hospital

2025· article· en· W4417175934 on OpenAlexaboutno aff
Patrícia Ferreira Mattos, Bruna Moutinho, Thais Ferreira Gêda, Rita de Cássia Parente Prado, Luísa Leite Barros, Adérson Omar Mourão Cintra Damião, Alexandre de Sousa Carlos, Matheus Freitas Cardoso de Azevedo, Aytan Miranda Sipahi

Bibliographic record

VenueThe American Journal of Gastroenterology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsnot available
Fundersnot available
KeywordsInflammatory bowel diseaseEpidemiologyUlcerative colitisIncidence (geometry)Retrospective cohort studyDiseaseCohortObservational studyCrohn's disease

Abstract

fetched live from OpenAlex

Background: Inflammatory bowel diseases (IBD) are chronic, immune-mediated conditions associated with substantial morbidity and significant economic burden on healthcare systems. The epidemiological landscape of IBD is evolving, characterized by a rising incidence in developing regions and a growing proportion of elderly patients. The management of IBD in this subpopulation poses unique challenges, spanning from accurate diagnosis to therapeutic decision-making, as older individuals often present with multiple comorbidities and an increased susceptibility to infections and malignancies. Methods: A retrospective observational study included all patients with Crohn’s disease (CD) or ulcerative colitis (UC) followed since 2010 at a specialized IBD clinic in a tertiary hospital in Brazil, aged 60 years or older. Results: A total of 382 patients with IBD and age ≥60 years were included, 66.5% were female. The mean age was 70.2 years, whereas the mean age at diagnosis of IBD was 46.5 years. Notably, 13.6% of the patients in this cohort had a late-onset IBD, first presenting at an age of ≥60 years. Mean duration of disease (UC or CD) was 23.7 (SD 10.2) years. Most patients (55%) had a diagnosis of CD, of whom 65.7% presented with a more aggressive phenotype, characterized by either stenosing or fistulizing behavior (B2 or B3, according to the Montreal classification), and 20.9% had perianal disease. Patients with phenotypes B2/B3 had a significantly higher rate of surgical intervention compared to those with an inflammatory (B1) phenotype (71.7% vs 18.3%, respectively; P < 0.0001). Seventy-six percent of patients with CD were exposed to biologic therapy. Anti-TNF agents were the predominant class, used by 78.1% of them, while vedolizumab was used by 20%. On the other hand, in the UC cohort, most patients presented with pancolitis (57.5%), but exposure to immunobiologic therapy was only noted in 33.7% (29.6% received anti-TNFs and 15.1% were treated with vedolizumab). Seventy-eight patients (20.4%) developed a malignancy while treating for IBD. Among those, 71.8% were treated with immunobiologics and/or immunosuppressive therapies. In this cohort, neither a longer disease duration (>20 years) nor smoking history were found to be significantly associated with an increased risk of neoplasia (respectively, 19.8% vs 21.3%; P = 0.82 and 19.7% vs 20.9%; P = 0.88). Of note, opportunistic infections were reported in 52 individuals (13.6%), of whom 43 (82.7%) had been exposed to advanced therapies. Treatment with immunosuppressants or biologics was significantly associated with a higher risk of opportunistic infections (16.9% vs 4% for patients on other therapies; P = 0.0021). However, no such association was observed for neoplasia (19.8% vs 22%; P = 0.7431). Conclusions: The rising prevalence of elderly patients with inflammatory bowel disease (IBD) reflects evolving epidemiological trends and poses distinct clinical challenges. A comprehensive understanding of the demographic characteristics, therapeutic approaches, and clinical outcomes in this population is crucial to guide management strategies and enhance patient safety. Although the use of advanced therapies in older adults carries potential risks, these treatments are frequently required to achieve adequate disease control, particularly in individuals with an aggressive disease course.

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)0.000
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.265
Teacher spread0.259 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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