The Indirect Antiglobulin (Coombs’) Test Is Specific but Less Sensitive Than the Direct Antiglobulin Test for Detecting Anti-Erythrocytic Autoantibodies and Thereby Immune-Mediated Hemolytic Anemia in Dogs
Bibliographic record
Abstract
The immunodiagnostic assessment of dogs suspected of having immune-mediated hemolytic anemia (IMHA) is based on persistent autoagglutination of erythrocytes (after three saline washes), marked spherocytosis, and a positive direct antiglobulin (Coombs') test (DAT). However, the value of using the indirect antiglobulin test (IAT) for the detection of anti-erythrocytic autoantibodies in serum from dogs suspected of having IMHA is unclear. To evaluate the IAT, leftover serum samples from a large cohort of 94 dogs suspected of having IMHA and for which DAT results were known were incubated with DAT- erythrocytes, and five IAT techniques were performed (in part with different reagents and temperatures): microtiter plate (MICRO), microcapillary, laboratory gel column, gel minitube kit (GEL KIT), and immunochromatographic strip kit. Two IAT techniques (MICRO at 37 °C and GEL KIT with rabbit anti-dog polyvalent reagent) detected autoantibodies against erythrocytes in serum from 53% and 57% of DAT+ dogs, respectively, while other IATs performed less well. Moreover, while the analytic specificity of the IAT methods compared to the DAT ranged from 96-100%, the sensitivity range was only 9-57%. Thus, we still recommend DAT for diagnosis and monitoring of IMHA in dogs but conclude that a positive IAT result may aid diagnostically when serum is available, but fresh red blood cells are not.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".