Anemia and Iron Deficiency in Outpatients with Inflammatory Bowel Disease: Ubiquitous Yet Suboptimally Managed
Bibliographic record
Abstract
Background: Iron deficiency (ID) and anemia in patients with Inflammatory Bowel Disease (IBD) are associated with a reduced quality of life. We assessed the prevalence of ID and anemia in Dutch outpatients with IBD and compared routine ID(A) management among medical professionals to the European Crohn’s and Colitis Organisation (ECCO) treatment guidelines. Methods: Between January and November 2021, consecutive adult outpatients with IBD were included in this study across 16 Dutch hospitals. Clinical and biochemical data were extracted from medical records. Additionally, medical professionals filled out questionnaires regarding routine ID(A) management. Results: In total, 2197 patients (1271 Crohn’s Disease, 849 Ulcerative Colitis, and 77 IBD-unclassified) were included. Iron parameters were available in 59.3% of cases. The overall prevalence of anemia, ID, and IDA was: 18.0%, 43.4%, and 12.2%, respectively. The prevalence of all three conditions did not differ between IBD subtypes. ID(A) was observed more frequently in patients with biochemically active IBD than in quiescent IBD (ID: 70.8% versus 23.9%; p < 0.001). Contrary to the guidelines, most respondents prescribed standard doses of intravenous or oral iron regardless of biochemical parameters or inflammation. Lastly, 25% of respondents reported not treating non-anemic ID. Conclusions: One in five patients with IBD suffers from anemia that—despite inconsistently measured iron parameters—is primarily caused by ID. Most medical professionals treat IDA with oral iron or standard doses of intravenous iron regardless of biochemical inflammation; however, non-anemic ID is often overlooked. Raising awareness about the management of ID(A) is needed to optimize and personalize routine care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".