COVID-19 Lung Injury: Unique and Familiar Aspects of Pathophysiology
Bibliographic record
Abstract
Acute lung injury (ALI), diagnosed clinically as acute respiratory distress syndrome (ARDS), refers to a spectrum of acute inflammatory processes culminating in increased permeability of the pulmonary alveolar–capillary barrier and impaired gas exchange. The pandemic caused by the novel coronavirus, SARS-CoV-2, has raised questions as to the similarities and differences between COVID-19 lung injury and ALI of other etiologies. This review summarizes current knowledge regarding the pathophysiology of ALI and COVID-19 lung injury and draws comparisons between the latter and other infectious etiologies of ALI. Indeed, severe COVID-19 is characterized by a unique array of disease mechanisms including suppression of interferon responses, widespread inflammasome activation, altered leukocyte phenotypes, and hyperactive thrombotic activity. Moreover, these mechanisms manifest as a unique clinical progression, which further differentiates COVID-19 from other viral respiratory pathogens such as SARS, MERS, and influenza. These unique features of COVID-19 pathophysiology bear important implications for current and future therapeutic strategies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 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".