Incidence and Adverse Outcomes of Acute Kidney Disease: A Systematic Review and Meta-Analysis
Notice bibliographique
Résumé
RATIONALE & OBJECTIVE: Estimates of the incidence of acute kidney disease (AKD) and its associated adverse outcomes are inconsistent, which may be due in part to differences in prior studies' definitions of AKD. This study sought to summarize these reports and identify study-level characteristics, including the definition of AKD, that may explain the observed heterogeneity. STUDY DESIGN: Systematic review and meta-analysis. SETTING & STUDY POPULATIONS: Adults aged≥18 years and not receiving maintenance kidney replacement therapy. SELECTION CRITERIA FOR STUDIES: Observational studies that assessed the incidence of AKD and its association with adverse outcomes. DATA EXTRACTION: Two reviewers independently extracted data and assessed study quality. ANALYTICAL APPROACH: AKD definitions were classified as (1) Acute Disease Quality Initiative (ADQI) or ADQI-equivalent or (2) KDIGO (Kidney Disease: Improving Global Outcomes) or KDIGO-equivalent. A random-effects meta-analysis was used to calculate pooled estimates of incidence and the relationship between AKD and outcomes (mortality, kidney failure, onset of chronic kidney disease) summarized by ORs and 95% CIs. RESULTS: Among 1,883 identified studies, 59, involving nearly 6 million participants, met the inclusion criteria. Most studies were classified as being of good quality per the Newcastle-Ottawa scale (n=44). The pooled incidence of AKD was higher when defined by ADQI/ADQI-equivalent criteria compared with KDIGO/KDIGO-equivalent criteria (26.6% [95% CI, 20.3-34.9%] vs 11.1% [95% CI, 7.6-16.3%]; P<0.001). The pooled OR of all-cause mortality associated with AKD was similar whether defined with KDIGO/KDIGO-equivalent or ADQI/ADQI-equivalent criteria (3.8 [95% CI, 2.2-6.7] vs 3.0 [95% CI, 2.1-4.4]; P=0.5). After accounting for baseline acute kidney injury status, the incidence of AKD and its association with all-cause mortality were similar for the 2 definitions. The incidences of AKD were 13.6% and 11.1%, and the ORs for all-cause mortality were not different (4.2 [95% CI, 2.0-8.7] vs 3.8 [95% CI, 2.2-6.7]; P=0.8) using the ADQI/ADQI-equivalent and KDIGO/KDIGO-equivalent definitions, respectively. Similar results were observed for the association between AKD and the development of chronic kidney disease, but the association between AKD and kidney failure was stronger in studies that used the KDIGO/KDIGO-equivalent definition. LIMITATIONS: Heterogeneity persisted across most of the examined subgroups. CONCLUSIONS: Estimates for AKD incidence and AKD-associated risk for clinical outcomes vary by the definition used for AKD. These findings inform the assessment of the incidence and consequences of AKD in research and clinical settings. REGISTRATION: Registered at PROSPERO with identification number CRD42024515828. PLAIN-LANGUAGE SUMMARY: In this systematic review and meta-analysis of 59 studies involving nearly 6 million participants, we found that acute kidney disease (AKD) is globally prevalent and is associated with higher risks of adverse outcomes, including all-cause mortality, chronic kidney disease, and kidney failure. Estimates of AKD incidence and AKD-associated risks of clinical outcomes vary significantly depending on the definition of AKD used. The selection of the definition for AKD and the presence of baseline acute kidney injury influence the estimate of AKD incidence and its association with health consequences. The findings of this study should guide efforts to refine clinical guidelines and inform public health strategies to address the global burden of AKD more effectively.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,036 | 0,074 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,002 |
| Méta-épidémiologie (sens large) | 0,018 | 0,036 |
| Bibliométrie | 0,013 | 0,011 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 source (Gemma direct ou Codex distillé), 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 ».