A critical review of the pathophysiology of thrombotic complications and clinical practice recommendations for thromboprophylaxis in pregnant patients with COVID‐19
Bibliographic record
Abstract
Those who are infected with Severe Acute Respiratory Syndrome-related CoronaVirus-2 are theoretically at increased risk of venous thromboembolism during self-isolation if they have reduced mobility or are dehydrated. Should patients develop coronavirus disease (COVID-19) pneumonia requiring hospital admission for treatment of hypoxia, the risk for thromboembolic complications increases greatly. These thromboembolic events are the result of at least two distinct mechanisms - microvascular thrombosis in the pulmonary system (immunothrombosis) and hospital-associated venous thromboembolism. Since pregnancy is a prothrombotic state, there is concern regarding the potentially increased risk of thrombotic complications among pregnant women with COVID-19. To date, however, pregnant women do not appear to have a substantially increased risk of thrombotic complications related to COVID-19. Nevertheless, several organizations have vigilantly issued pregnancy-specific guidelines for thromboprophylaxis in COVID-19. Discrepancies between these guidelines reflect the altruistic wish to protect patients and lack of high-quality evidence available to inform clinical practice. Low molecular weight heparin (LMWH) is the drug of choice for thromboprophylaxis in pregnant women with COVID-19. However, its utility in non-pregnant patients is only established against venous thromboembolism, as LMWH may have little or no effect on immunothrombosis. Decisions about initiation and duration of prophylactic anticoagulation in the context of pregnancy and COVID-19 must take into consideration disease severity, outpatient vs inpatient status, temporal relation between disease occurrence and timing of childbirth, and the underlying prothrombotic risk conferred by additional comorbidities. There is currently no evidence to recommend the use of intermediate or therapeutic doses of LMWH in thromboprophylaxis, which may increase bleeding risk without reducing thrombotic risk in pregnant patients with COVID-19. Likewise, there is no evidence to comment on the role of low-dose aspirin in thromboprophylaxis or of anti-cytokine and antiviral agents in preventing immunothrombosis. These unanswered questions are being studied within the context of clinical trials.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".