Iron and Vitamin B12 Deficiency in Patients with Autoimmune Gastritis and <i>Helicobacter pylori</i> Gastritis: Results from a Prospective Multicenter Study
Bibliographic record
Abstract
INTRODUCTION: Iron and vitamin B12 deficiencies are common in patients with atrophic gastritis, but there are limited data on the prevalence of these deficiencies in different types of atrophic gastritis. METHODS: This multicenter, prospective study assessed micronutrient concentrations in histologically confirmed autoimmune gastritis (AIG, n = 45), Helicobacter pylori-related non-autoimmune gastritis (NAIG, n = 109), and control patients (n = 201). A multivariate analysis was performed to determine factors influencing those deficiencies. RESULTS: The median vitamin B12 concentration was significantly lower in AIG (367.5 pg/mL, Q1, Q3: 235.5, 524.5) than in NAIG (445.0 pg/mL, Q1, Q3: 355.0, 565.0, p = 0.001) and control patients (391.0 pg/mL, Q1, Q3: 323.5, 488.7, p = 0.001). Vitamin B12 deficiency was found in 13.3%, 1.5%, and 2.8% of AIG, NAIG, and control patients, respectively. Similarly, the median ferritin concentration was significantly lower in AIG (39.5 ng/mL, Q1, Q3: 15.4, 98.3 ng/mL) than in NAIG (80.5 ng/mL, Q1, Q3: 43.6, 133.9, p = 0.04) and control patients (66.5 ng/mL, Q1, Q3: 33.4, 119.8, p = 0.007). Iron deficiency and iron deficiency adjusted to CRP were present in 28.9% and 33.3% of AIG, 12.8% and 16.5% of NAIG, and 12.9% and 18.4% of controls, respectively. Multivariate analysis demonstrated that AIG patients had a higher risk of developing vitamin B12 deficiency (OR: 11.52 [2.85-57.64, p = 0.001]) and iron deficiency (OR: 2.92 [1.32-6.30, p = 0.007]) compared to control patients. Factors like age, sex, and H. pylori status did not affect the occurrence of vitamin B12 or iron deficiency. CONCLUSION: Iron and vitamin B12 deficiencies are more commonly observed in patients with AIG than in those with NAIG or control patients. Therefore, it is essential to screen for both iron and vitamin B12 deficiencies in AIG patients and include the treatment of micronutrient deficiencies in the management of atrophic gastritis patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".