The Use of the Anticoagulant Heparin and Corticosteroid Dexamethasone as Prominent Treatments for COVID-19
Bibliographic record
Abstract
COVID-19 is spreading worldwide at disturbing rates, overwhelming global healthcare. Mounting death cases due to disease complications highlight the necessity of describing efficient drug therapy strategies for severe patients. COVID-19 severity associates with hypercoagulation and exacerbated inflammation, both influenced by ACE2 downregulation and cytokine storm occurrence. In this review, we discuss the applicability of the anticoagulant heparin and the anti-inflammatory corticosteroid dexamethasone for managing severe COVID-19 patients. The upregulated inflammation and blood clotting may be mitigated by administrating heparin and its derivatives. Heparin enhances the anticoagulant property of anti-thrombin (AT) and may be useful in conjunction with fibrinolytic drugs for severe COVID-19 patients. Besides, heparin can also modulate immune responses, alleviating TNF-α-mediated inflammation, impairing IL-6 production and secretion, and binding to complement proteins and leukotriene B4 (LTB4). Moreover, heparin may present anti-SARS-CoV-2 potential once it can impact viral infectivity and alter SARS-CoV-2 Spike protein architecture. Another feasible approach is the administration of the glucocorticoid dexamethasone. Although glucocorticoid's administration for viral infection managing is controversial, there is increasing evidence demonstrating that dexamethasone treatment is capable of drastically diminishing the death rate of patients presenting with Acute Respiratory Distress Syndrome (ARDS) that required invasive mechanical ventilation. Importantly, dexamethasone may be detrimental by impairing viral clearance and inducing hyperglycemia and sodium retention, hence possibly being deleterious for diabetics and hypertensive patients, two major COVID-19 risk groups. Therefore, while heparin's multitarget capacity shows to be strongly beneficial for severe COVID-19 patients, dexamethasone should be carefully administered taking into consideration underlying medical conditions and COVID-19 disease severity. Therefore, we suggest that the multitarget impact of heparin as an anti-viral, antithrombotic and anti-inflammatory drug in the early stage of the COVID-19 could significantly reduce the need for dexamethasone treatment in the initial phase of this disease. If the standard treatment of heparins fails on protecting against severe illness, dexamethasone must be applied as a potent anti-inflammatory shutting-down the uncontrolled and exacerbated inflammation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".