Acute Kidney Injury in Adults due to COVID-19 infection: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: In COVID-19 infection, Acute Kidney Injury (AKI) poses a severe complication. To help clinicians to implement effective clinical therapy, we systematically documented evidence on AKI incidence and associated death in COVID-19 infection among adult populations. Methods: For the systematic review and meta-analysis Guidelines laid by Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) were followed. Studies were searched from Pubmed and MedRxiv databases published between December 2019 - June 19, 2021. Results: 55 out of 3175 total articles were identified as eligible for the qualitative review with 32 reports on adults (n=169560); mean age 65.34 years. Studies on AKI incidence, mortality, and AKI-related mortality in COVID-19-infected adults p were included in the meta-analysis. Estimated AKI incidence in adults was 16.4% ([95%CI, 12.8 – 20.0%], I2 =99.39%, P<0.001). Moreover, overall death 34.8% ([95%CI, 21.3- 48.3%], I2 = 99.88%, P<0.001) and AKI-related death 68.4% ([95%CI, 55.9–81.0%], I2=99.2%, P<0.001) among adults revealed high statistical heterogeneity. Conclusion: AKI- related mortality was significantly high in COVID-19-infected adults. Therefore, AKI is common in COVID-19 infection and clinical management must be accordingly formulated.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.001 | 0.007 |
| 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) | 0.000 | 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".