The evolving management algorithm for the patient with newly diagnosed cold agglutinin disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Cold agglutinin disease (CAD) is driven by IgM autoantibodies reactive at <37°C and able to fix complement. The activation of the classical complement pathway leads to C3-mediated extravascular hemolysis in the liver and to intravascular hemolytic crises in case of complement amplifying conditions. C3 positivity at direct Coombs test along with high titer agglutins are required for the diagnosis. Treatment is less standardized. AREAS COVERED: This review recapitulates CAD diagnosis and then focus on the evolving management of the disease. Both current approach and novel targeted drugs are discussed. Literature search was conducted in PubMed and Scopus from 2000 to 2024 using 'CAD' and 'autoimmune hemolytic anemia' as keywords. EXPERT OPINION: Rituximab represents the frontline approach in patients with symptomatic anemia or disabling cold-induced peripheral symptoms and is effective in 50-60% of cases. Refractory/relapsing patients are an unmet need and may now benefit from complement inhibitors, particularly the anti-C1s sutimlimab, effective in controlling hemolysis thus improving anemia in >80% of patients, but not active on cold-induced peripheral symptoms. Novel drugs include long-acting complement inhibitors, plasma cells, and B-cell targeting agents (proteasome inhibitors, anti-CD38, BTKi, PI3Ki, anti-BAFF). Combination therapy may be the future answer to CAD unmet needs.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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