Use of thrombolytic agents to treat neonatal thrombosis in clinical practice
Bibliographic record
Abstract
Among children, neonates have the highest incidence of thrombosis. Thrombolytic agents are used for the management of life and/or organ-threatening thrombosis. Literature on the efficacy and safety of thrombolytic agents in neonates is limited. We reviewed the evidence on dosing, administration, monitoring and treatment duration of tissue plasminogen activator (tPA), streptokinase and urokinase (URK) in neonates (≤ 28days). A systematic literature search was conducted of current databases from inception until 31 March 2021. The initial search yielded 6881 articles and 18 were retained for review. tPA, streptokinase and URK was utilized in 12, seven and four studies on 115, 51 and 16 patients, respectively. The dose range for tPA, streptokinase and URK was 0.01 -0.6 mg/kg/h, 50-2000 and 1000-0 000 units/kg/h, respectively, and treatment duration ranged from 30 min to 30 days. This is the first study to objectively summarize the efficacy and safety of thrombolytic agents in neonates. Overall, thrombolysis was associated with 87.9% complete or partial thrombus resolution and 7.4% recurrence risk. The bleeding risk associated with thrombolytic agents was 23.1% on pooled analysis, which is higher than other anticoagulants. Larger prospective studies are required to determine effective dosing regimens of these therapeutic drugs and further clarify their efficacy and safety. Blood Coagul Fibrinolysis 33:000-000 Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.
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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 | 0.005 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".