Multiorgan Failure With Emphasis on Acute Kidney Injury and Severity of COVID-19: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Abnormalities in hematologic, biochemical, and immunologic biomarkers have been shown to be associated with severity and mortality in Coronavirus Disease 2019 (COVID-19). Therefore, early evaluation and monitoring of both liver and kidney functions, as well as hematologic parameters, are pivotal to forecast the progression of COVID-19. Objectives: In this study, we performed a systematic review and meta-analysis to investigate the association between several complications, including acute kidney injury (AKI), acute liver injury (ALI), and coagulopathy, with poor outcomes in COVID-19. Design: Systematic review and meta-analysis Setting: Observational studies reporting AKI, ALI, and coagulopathy along with the outcomes of clinically validated death, severe COVID-19, or intensive care unit (ICU) care were included in this study. The exclusion criteria were abstract-only publications, review articles, commentaries, letters, case reports, non-English language articles, and studies that did not report key exposures or outcomes of interest. Patients: Adult patients diagnosed with COVID-19. Measurements: Data extracted included author, year, study design, age, sex, cardiovascular diseases, hypertension, diabetes mellitus, respiratory comorbidities, chronic kidney disease, mortality, severe COVID-19, and need for ICU care. Methods: We performed a systematic literature search from PubMed, SCOPUS, EuropePMC, and the Cochrane Central Database. AKI and ALI follow the definition of the included studies. Coagulopathy refers to the coagulopathy or disseminated intravascular coagulation defined in the included studies. The outcome of interest was a composite of mortality, need for ICU care, and severe COVID-19. We used random-effects models regardless of heterogeneity to calculate risk ratios (RRs) for dichotomous variables. Heterogeneity was assessed using I 2 . Random effects meta-regression was conducted for comorbidities and the analysis was performed for one covariate at a time. Results: There were 3615 patients from 15 studies. The mean Newcastle-Ottawa scale of the included studies was 7.3 ± 1.2. The AKI was associated with an increased the composite outcome (RR: 10.55 [7.68, 14.50], P < .001; I 2 : 0%). Subgroup analysis showed that AKI was associated with increased mortality (RR: 13.38 [8.15, 21.95], P < .001; I 2 : 24%), severe COVID-19 (RR: 8.12 [4.43, 14.86], P < .001; I 2 : 0%), and the need for ICU care (RR: 5.90 [1.32, 26.35], P = .02; I 2 : 0%). The ALI was associated with increased mortality (RR: 4.02 [1.51, 10.68], P = .005; I 2 : 88%) in COVID-19. Mortality was higher in COVID-19 with coagulopathy (RR: 7.55 [3.24, 17.59], P < .001; I 2 : 69%). The AKI was associated with the composite outcome and was not influenced by age ( P = .182), sex ( P = .104), hypertension ( P = .788), cardiovascular diseases ( P = .068), diabetes ( P = .097), respiratory comorbidity ( P = .762), and chronic kidney disease ( P = .77). Limitations: There are several limitations of this study. Many of these studies did not define the extent of AKI (grade), which may affect the outcome. Acute liver injury and coagulopathy were not defined in most of the studies. The definition of severe COVID-19 differed across studies. Several articles included in the study were published at preprint servers and are not yet peer-reviewed. Most of the studies were from China; thus, some patients might overlap across the reports. Most of the included studies were retrospective in design. Conclusions: This meta-analysis showed that the presence of AKI, ALI, and coagulopathy was associated with poor outcomes in patients with COVID-19.
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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 | 0.001 | 0.255 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".