An Iron Deficient Patient with Opposite Iron Profiles within Five Days
Bibliographic record
Abstract
A 77-year-old woman with a long term iron deficiency anemia had routine blood work done because the patient was taking ferrous gluconate 300 mg/day irregularly. She had a subtotal colectomy (including cecum and a portion of terminal ileum) for Crohn’s disease 15 years ago. The complete blood count indicated as microcytic, hypochromic anemia with erythrocytes 3.45 x 10/L (reference interval (RI): 4 10 x 10/L), hemoglobin 87 g/L (RI: 115 155 g/L), hematocrit 26.7% (RI: 35 45%), mean corpuscular volume 77.3 fL (RI: 82 100 fL), and mean corpuscular hemoglobin 25.2 pg (RI: 27 34 pg). Due to the significant increase in serum iron (83 μmol/L) and transferrin saturation (93.3%), she was advised to stop taking her iron supplement. Considering the inconsistent laboratory results between iron profile, blood count and patient’s history, five days later the patient’s iron profile was repeated and results were completely opposite (Table 1). Therefore, the question of a possible laboratory error was raised. Laboratory investigation excluded sample labeling errors and analytical errors. Detailed patient inquiry revealed that on day 1, the patient took one iron dose (300 mg) with lunch and had blood drawn 4 hours later, whereas she was fasting and had not taken her iron medication for 2 days on day 6. A low serum ferritin value is the most sensitive and reliable serum indicator for iron deficiency [1], as it correctly reflected this patient’s iron depletion status on day 1. The patient’s iron supplementation should not be discontinued based on her low ferritin levels without repeating the iron profile. The slightly elevated ferritin on day 6 was due to inflammation from a sore throat; it dropped to 42 μg/L five weeks later. Because ferritin is an acute phase reactant, a normal or even elevated serum ferritin level cannot be used to exclude iron deficiency if a hepatic, malignant, or inflammatory condition is present [2]. Serum iron fluctuates with food and medication. It is often unreliable for the diagnosis of iron deficiency. Unsaturated iron-binding capacity, total iron binding capacity, and transferring saturation on day 1 were all misled by the erroneous high serum iron result due to supplementation only 4 hours prior to testing. For iron profile tests, patients should fast 8 12 hours and blood should be collected in the morning to avoid diurnal variation. In addition, iron containing supplements should be avoided for 24 hours prior to blood collection [3].
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".