Multiorgan Failure With Emphasis on Acute Kidney Injury and Severity of COVID-19: Systematic Review and Meta-Analysis
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,255 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».