Strategies to overcome the diagnostic challenges of autoimmune hemolytic anemias
Bibliographic record
Abstract
INTRODUCTION: The direct antiglobulin test (DAT) or Coombs test is the cornerstone of the diagnosis of autoimmune hemolytic anemia (AIHA). It can be performed by several methods with different sensitivity and specificity and enables the distinction of warm, cold, and mixed forms, which require different therapies. AREAS COVERED: The review describes the different DAT methods, including the tube test with monospecific antisera, microcolumn and solid phase methods that are routinely accessible in most laboratories. Additional investigations include the use of cold washes and low ionic salt solutions, the identification of auto-Ab specificity and thermal range, the study of the eluate, and the Donath-Landsteiner test, available in most reference laboratories. Experimental techniques are the dual-DAT, flow cytometry, ELISA, immuno-radiometric assay, and mitogen-stimulated DAT, which may help the diagnosis of DAT-negative AIHAs, a clinical challenge with delayed diagnosis and possible improper therapy. Further diagnostic challenges include the correct interpretation of hemolytic markers, the infectious and thrombotic complications, and the possible underlying conditions (lymphoproliferative disorders, immunodeficiencies, neoplasms, transplants, and drugs). EXPERT OPINION: These diagnostic challenges may be overcome by a 'hub' and 'spoke' organization among laboratories, a clinical validation of experimental techniques, and a continuous dialogue between clinicians and immune-hematologic laboratory experts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".