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Record W4406347990 · doi:10.1556/650.2025.33197

Az anaemia gyakoriságának felmérése, osztályozása, prediktív tényezői gyulladásos bélbetegségben szenvedő betegekben

2025· article· hu· W4406347990 on OpenAlexaff
F Balogh, Dorottya Angyal, Andor Áron Ecseki, Zsófia Veronika Sebeszta, Lóránt Gönczi, Livia Lontai, Pál Miheller, Péter L. Lakatos, Ákos Iliás

Bibliographic record

VenueOrvosi Hetilap · 2025
Typearticle
Languagehu
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineGastroenterologyInternal medicineGynecology

Abstract

fetched live from OpenAlex

Introduction: Anemia is a common complication of inflammatory bowel disease and serves as an indicator of severe disease. Objective: This study aims to evaluate the prevalence, etiology, predictive factors, and treatment of anemia in patients with inflammatory bowel disease from two tertiary centers. Method: In this retrospective, cross-sectional study, we assessed the frequency of anemia among patients presenting within a specified calendar year (June 1, 2022, to May 31, 2023), focusing on the lowest hemoglobin levels recorded during this period. We collected demographic data, disease activity scores, treatment regimens, inflammatory markers, and laboratory parameters related to iron balance. Clinical disease activity was evaluated using the Crohn’s Disease Activity Index and the partial Mayo Score. The World Health Organization’s criteria were utilized for anemia classification and severity assessment. Absolute iron deficiency was defined as a serum ferritin level <30 µg/L, while anemia of chronic disease was defined as a ferritin level >100 µg/L in conjunction with clinical or biochemical evidence of active disease. Results: The study included 400 patients (277 with Crohn’s disease and 123 with ulcerative colitis). Among the Crohn’s disease patients, 17.7% exhibited complex disease behavior, and 40.7% of the ulcerative colitis patients had extensive colonic involvement. Biological treatments were administered to 75% of the participants. Anemia was identified in 32.5% (130) of the patient cohort, with 57% classified as mild, 35% as moderate, and 8% as severe. In the subset of non-macrocytic anemia (116 patients), iron status data were available for 51% (n = 66). Of these, 73% had iron deficiency anemia, 6% had anemia of chronic disease, and 17% had chronic disease with functional iron deficiency. Anemia predictors included steroid treatment (p<0.001; OR: 4.2), clinical disease activity (p<0.001, OR: 381), and laboratory markers of disease activity (p<0.001, OR: 2.9). Intravenous iron supplementation was administered to 43 patients, while 12 received oral iron supplementation. Conclusion: The findings highlight the high prevalence of anemia, predominantly iron deficiency anemia, among patients with inflammatory bowel disease, which is closely associated with clinical and laboratory markers of disease activity. This study underscores the importance of diagnosis, classification (through assessment of iron balance parameters), and treatment of anemia in patients with inflammatory bowel disease. Orv Hetil. 2025; 166(2): 60–66.

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)0.001
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.004
GPT teacher head0.240
Teacher spread0.236 · 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
Published2025
Admission routes1
Has abstractyes

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