Differential Diagnosis of Microcytic Anemia, Thalassemia or Iron Deficiency Anemia: A Diagnostic Test Accuracy Meta-Analysis
Bibliographic record
Abstract
Diagnostic test accuracy (DTA)We evaluated the most common indices to compare their sensitivity and specificity to introduce the most sensitive and specific index.We systematically searched five international indexing databases up to Dec 2018.For each index, we measured the diagnostic odds ratio (DOR), as well as summary ROC (SROC) curve which was used to compare the performance of each index.Deeks̕ tests of all discriminant indices indicated that there is no potential publication bias.The area under curves (AUCs) of all discriminant indices indicate overall good differential performance.The M/H ratio index was more sensitive and specific compared to other studied indices.In this meta-analysis, the M/H ratio index was more potential to discriminate iron deficiency anemia (IDA) from thalassemia trait.However, we cannot use this index alone to achieve the final diagnosis.The capability of this index to discriminate IDA from thalassemia trait must be used alongside with the common laboratory procedure to ensure the final differentiation.
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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 | 0.022 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.041 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".