American Society of Hematology 2018 guidelines for management of venous thromboembolism: heparin-induced thrombocytopenia
Bibliographic record
Abstract
BACKGROUND: Heparin-induced thrombocytopenia (HIT) is an adverse drug reaction mediated by platelet-activating antibodies that target complexes of platelet factor 4 and heparin. Patients are at markedly increased risk of thromboembolism. OBJECTIVE: These evidence-based guidelines of the American Society of Hematology (ASH) are intended to support patients, clinicians, and other health care professionals in their decisions about diagnosis and management of HIT. METHODS: ASH formed a multidisciplinary guideline panel balanced to minimize potential bias from conflicts of interest. The McMaster University GRADE Centre supported the guideline development process, including updating or performing systematic evidence reviews. The panel prioritized clinical questions and outcomes according to their importance for clinicians and patients. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach was used to assess evidence and make recommendations, which were subject to public comment. RESULTS: The panel agreed on 33 recommendations. The recommendations address screening of asymptomatic patients for HIT, diagnosis and initial management of patients with suspected HIT, treatment of acute HIT, and special situations in patients with acute HIT or a history of HIT, including cardiovascular surgery, percutaneous cardiovascular intervention, renal replacement therapy, and venous thromboembolism prophylaxis. CONCLUSIONS: Strong recommendations include use of the 4Ts score rather than a gestalt approach for estimating the pretest probability of HIT and avoidance of HIT laboratory testing and empiric treatment of HIT in patients with a low-probability 4Ts score. Conditional recommendations include the choice among non-heparin anticoagulants (argatroban, bivalirudin, danaparoid, fondaparinux, direct oral anticoagulants) for treatment of acute HIT.
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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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.018 | 0.015 |
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".