P350 SAFIIR: Study of Anemia Following Intravenous Iron Repletion
Bibliographic record
Abstract
Abstract Background The main objective of this study was to assess the prevalence of anemia and the secondary objectives aimed to evaluate the real-life impact of intravenous iron therapy on anemia correction in patients living with Inflammatory Bowel Disease (IBD). Methods We performed a retrospective cohort study of adult patients (18 to 80 years old) with a Crohn’s Disease or Ulcerative Colitis diagnosis who were followed at our clinic between January 2018 and March 2020. Clinical data were obtained from the patients’ electronic medical records. Iron-deficiency anemia was defined as hemoglobin (Hb) < 12,0 g/dL and/or transferrin saturation (TSAT)< 20 % and/or low serum iron (≤ 10 μmol/L). Intravenous (IV) iron treatment was defined as at least one infusion of iron isomaltoside, iron sucrose, or sodium ferric gluconate. The secondary analyses were performed in terms of IV iron treatments. Results Of the cohort of 556 IBD patients, 223 (40.1%) had an anemia diagnosis. Among the latter, 39 patients received an intravenous iron treatment and had laboratory results in the 8 weeks preceding and in the 8 weeks following the treatment. Table 1 shows the response to intravenous iron treatment in patients with baseline Hb < 12,0 g/dL (n=28 patients, 47 IV iron infusions). Table 2 shows the changes in anemia-related laboratory values in the 8 weeks preceding and in the 8 weeks following intravenous iron treatment. Conclusion This was the first study to evaluate the prevalence of iron-deficiency anemia and the real-life impact of intravenous iron treatment among patients living with IBD in Quebec, Canada. The findings will serve as a baseline for subsequent interventions to improve the wellbeing and the quality of life of IBD patients with anemia.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".