The Burden of Anemia Remains Significant over Time in Patients with Inflammatory Bowel Diseases at a Tertiary Referral Center
Bibliographic record
Abstract
BACKGROUND AND AIMS: Anemia is a common complication of inflammatory bowel diseases (IBD), as well as a predictor of poor outcomes. The aim of this study was to determine the prevalence of anemia over time and the management of moderate to severe anemia at a tertiary referral IBD center. METHODS: We retrospectively reviewed the occurrence of anemia at the time of referral or diagnosis and during follow-up at the McGill University Health Centre IBD center. Consecutive patients presenting with an outpatient visit between July and December 2016 and between December 2018 and March 2019 were included. Disease characteristics, biochemistry and medical management, including the need for intravenous iron therapy were recorded. RESULTS: 1,356 Crohn's disease (CD) and 1,293 ulcerative colitis (UC) patients [disease duration: 12 (IQR: 6-22) and 10 (IQR: 5-19) years respectively] were included. The prevalence of moderate to severe anemia at referral/diagnosis (15.4% and 8.5%) and during follow-up (11.1% and 8.1%) were higher in CD than in UC patients. In CD, previous resective surgery, perianal disease and elevated C-reactive protein (CRP) at assessment, while in UC steroid therapy, an elevated CRP and fecal calprotectin at assessment were associated with anemia in a multivariate analysis. Anemia improved by >2g/dL in 56.5% after 4-6 weeks (intravenous iron dose >1000 mg in 87% of patients). CONCLUSION: Anemia occurred frequently in this IBD cohort, at referral to the center and during follow-up, and contributes to the burden of IBD in referral populations. Most patients were assessed for anemia regularly and with accurate anemia workup; however, the targeted management of moderate to severe anemia was suboptimal.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".