Critical appraisal of the mechanisms of gastrointestinal and hepatobiliary infection by COVID-19
Bibliographic record
Abstract
COVID-19 represents a novel infectious disease induced by SARS-CoV-2. It has to date affected 24,240,000 individuals and killed 2,735,805 people worldwide. The highly infectious virus attacks mainly the lung, causing fever, cough, and fatigue in symptomatic patients, but also pneumonia in severe cases. However, growing evidence highlights SARS-CoV-2-mediated extrarespiratory manifestations, namely, gastrointestinal (GI) and hepatic complications. The detection of 1) the virus in the GI system (duodenum, colon, rectum, anal region, and feces); 2) the high expression of additional candidate coreceptors/auxiliary proteins to facilitate the virus entry; 3) the abundant viral angiotensin-converting enzyme 2 receptor; 4) the substantial expression of host transmembrane serine protease 2, necessary to induce virus-cell fusion; 5) the viral replication in the intestinal epithelial cells; and 6) the primarily GI disorders in the absence of respiratory symptoms lead to increased awareness of the risk of disease transmission via the fecal-oral route. The objectives of this review are to provide a brief update of COVID-19 pathogenesis and prevalence, present a critical overview of its GI and liver complications that affect clinical COVID-19 outcomes, clarify associated mechanisms (notably microbiota-related), define whether gut/liver disorders occur more frequently among critically ill patients with COVID-19, determine the impact of COVID-19 on preexisting gut/liver complications and vice versa, and discuss the available strategies for prevention and treatment to improve prognosis of the patients. The novel SARS-CoV-2 can cause gastrointestinal and hepatobiliary manifestations. Metagenomics studies of virobiota in response to SARS-CoV-2 infection are necessary to highlight the contribution of bacterial microflora to COVID-19 phenotype, which is crucial for developing biomarkers and therapeutics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".