Bibliographic record
Abstract
The aim of the study is to discriminate β-thalassemia from iron defficiency anemia (IDA) using common mathematical indices. A complete blood count (CBC) sample of 100 children (aged 6 months – 18 years) treated for β-thalassemia and IDA in Department for Pediatric Hematology and Oncology University Hospital Centre Zagreb was randomly selected. Only children diagnosed with microcytic hypochromic anemia (MCV <80 fl; MCH < 26 pg; hemoglobin < 109 g/l) were enrolled in the study. Diagnosis of β-thalassemia was confirmed with a hemoglobin A2 level > 3.5% by liquid chromatography while serum iron levels <4 umol/L and serum feritin levels <15 ng/dl indicated iron defficiency anemia (IDA). Children below < 6 months of age or with other diseases that could cause microcytic hypochromic anemia were excluded. Sensitivity, specificity and receiver operating characteristic (ROC) analysis of most common discriminating indices (Matos & Carvalho, Mentzer Index, RDW Index, Green and King, Ehsani Index) used in differential diagnosis of these two diseases was calculated using MedCalc.v15.2 statistical software. Nonparametric nature of the CBC sample was assessed using the Kolmogorov–Smirnov test. Mann–Whitney test was used to investigate differences between the two groups. Area under the ROC curve was calculated for each index and their differences were assessed. A p-value < 0.05 was considered significant. Among the 5 tested indices, the Ehsani index correctly diagnosed the highest number of children with β-thalassemia, but failed to properly recognize children with IDA (sensitivity 92%, specificity 46%). The most commonly used Mentzer index showed similar results (sensitivity 88%, specificity 48%). The best ratio between sensitivity and specificity was observed for the new Matos & Cavalho index (sensitivity 74%, specificity 88%) with highest area under the ROC curve. Pairwise comparison of ROC curves obseved a significant difference between Matos & Cavalho index and the remaining four tested indices (RDWI p<0,0008; Ehsani p<0,0001; Green and King p<0,0001; Mentzer p<0,0001). Kolmogorov–Smirnov test for normal distribution of CBC values showed a p>0,05 while Mann–Whitney U test for independent samples showed a p<0.05 difference between IDA and β- thalassemia. Our results show that the most optimal index for discriminating between β- thalassemia and IDA in analysed children is Matos & Cavalho Index. Therefore, it is more appropriate for discernment than the other analysed indexes. All indexes with low specificity (Mentzer, Ehsani, Green and King) were of low validity as they have a low proportion of IDA correctly identified as such.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".