COVID-19 Coagulopathies: Highlights of 2020–2021 Reported Data
Bibliographic record
Abstract
Background: The COVID-19 pandemic has evolved dramatically over the past two years, and literature on COVID-19 coagulopathy has been overwhelming, which complicates the process of understanding the literature or assessing the quality of the data available. The objective of this narrative review was to highlight and analyze data reported on COVID-19-induced coagulopathy and its outcomes in patients with severe or critical disease over two years of the pandemic. Methods: Studies published in high-impact journals reporting on hospitalized adult COVID-19 patients, their coagulation parameters, and their thrombotic complications were included. We searched MEDLINE, Embase, and Ovid between Dec 1, 2019 and July 18, 2021. We abstracted the following data: country; date of publication; total number, age, and sex of patients; detailed coagulation parameters; thrombotic complications; and anticoagulation data. Descriptive statistics, including percentages and averages, were used where applicable; otherwise, individual study data were presented. We used the New Ottawa Scale (NOS) to assess risk of bias in the included studies. Results: A total of 18,581 patients (9,255 males) reported in 62 studies from 16 different countries published between March 2020 and July 2021 were included this review. The highest number of studies was reported in July–August 2020, with additional peaks in February and May 2021. Coagulation laboratory parameters were reported in most studies, with considerable heterogeneity. A key finding is a more pronounced pro-coagulant profile in intensive care unit (ICU) patients. Controversy existed around thrombocytopenia and other platelet abnormalities in association with severe or late disease. Elevated D-dimer was consistently reported and was predictive of thrombosis and poor outcomes. Thrombosis occurred despite guideline-recommended thromboprophylaxis. Anticoagulation was reported in all studies, but practices were diverse, with 83% and 88% of studies in 2020 and 2021 respectively reporting thromboprophylaxis or thromboprophylaxis alongside treatment. Conclusion: This narrative review provided highlights of the literature regarding coagulation impairments, thrombotic complications, and anticoagulation use in COVID-19 patients over two years of the pandemic. We hope this analysis contributes to better understanding of COVID-19-induced coagulopathy and supports investigators designing future studies.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".