Management of heparin-induced thrombocytopenia: systematic reviews and meta-analyses
Bibliographic record
Abstract
Heparin-induced thrombocytopenia (HIT) is a prothrombotic adverse drug reaction occurring in <0.1% to 7% of patients receiving heparin products depending on the patient population and type of heparin. Management of HIT is highly dependent on a sequence of tests for which clinicians may or may not have the results when care decisions need to be made. We conducted systematic reviews of the effects of management strategies in persons with acute HIT, subacute HIT A or B, and remote HIT. We searched Medline, EMBASE, and the Cochrane Database through July 2019 for previously published systematic reviews and primary studies. Two investigators independently screened and extracted data and assessed the certainty of the evidence using the Grading of Recommendations Assessment, Development and Evaluation approach. We found primarily noncomparative studies and case series assessing effects of treatments, which led to low to very low certainty evidence. There may be little to no difference in the effects between nonheparin parenteral anticoagulants and direct oral anticoagulants in acute HIT. The benefits of therapeutic-intensity may be greater than prophylactic-intensity anticoagulation. Using inferior vena cava filters or platelet transfusion may result in greater harm than not using these approaches. Evidence for management in special situations, such as for patients undergoing cardiovascular interventions or renal replacement therapy, was also low to very low certainty. Additional research to evaluate nonheparin anticoagulants is urgently needed, and the development of novel treatments that reduce thrombosis without increasing hemorrhage should be a priority.
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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 | 0.019 | 0.056 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.028 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".