Clinical utility of next‐generation sequencing in the diagnosis of hereditary haemolytic anaemias
Why this work is in the frame
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Bibliographic record
Abstract
Hereditary haemolytic anaemias are genetically and phenotypically heterogeneous disorders characterized by increased red cell destruction, with consequences ranging from innocuous to severe life-threatening anaemia. Diagnostic laboratories endeavour to assist clinicians reach the exact patient diagnosis by using tests principally based on morphological and biochemical techniques. However, these routine studies may be inconclusive, particularly in newborn infants and when transfusions have recently been administered. Large numbers and size of the potentially involved genes also impose a practical challenge for molecular diagnosis using routine sequencing approaches. To overcome these diagnostic shortcomings, we have utilized next-generation sequencing to provide a high-throughput, highly sensitive assay. We developed a panel interrogating 28 genes encoding cytoskeletal proteins and enzymes with sequencing coverage of the coding regions, splice site junctions, deep intronic and regulatory regions. We then evaluated 19 samples, including infants with unexplained extreme hyperbilirubinaemia and patients with transfusion-dependent haemolytic anaemia. Where possible, inheritance patterns of pathogenic mutations were determined by sequencing of immediate relatives. We conclude that this next-generation sequencing panel could be a cost-effective approach to molecular diagnosis of hereditary haemolytic anaemia, especially when the family history is uninformative or when routine laboratory testing fails to identify the causative haemolytic process.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it