Acute kidney injury associated with <scp>COVID</scp>‐19—Cumulative evidence and rationale supporting against direct kidney injury (infection)
Bibliographic record
Abstract
Acute kidney injury (AKI) is a common complication, affecting up to 37% of hospitalized patients with SARS-CoV-2 infection and is proportional to its severity and portends poor prognosis. Diverse mechanisms have been proposed and studies reported conflicting results. Moreover, renal tropism of SARS-CoV-2 does not equate to its renal pathogenicity. For a virus to be pathogenic, in addition to its affinity (tropism) for specific tissue(s), host cells must allow viral entry, and discuss the important role played by transmembrane protease, serine 2 (TMPRSS2) and coexpression of both ACE2 and TMPRSS2 in the same cells is important to cause damage. Lack of coexpression of ACE2 and TMPRSS2 in the same cells of the kidneys is the limiting factor of SARS-CoV-2 direct effects in the kidney. We present the rationale and cumulative evidence supporting that AKI is secondary to hemodynamic and immunologic effects of SARS-CoV-2 infection than the direct injury or infection.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".