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Risk Factors for Acute Kidney Injury in Critically Ill Neonates: A Systematic Review and Meta-Analysis.

ABSTRACT: Background and Objective: Acute kidney injury (AKI) is recognized as an independent risk factor for mortality and long-term poor prognosis in neonates. The objective of the study was to identify the risk factors for AKI in critically ill neonates to provide an important basis for follow-up research studies and early prevention. Methods: The PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, WanFang Med, SinoMed, and VIP Data were searched for studies of risk factors in critically ill neonates. Studies published from the initiation of the database to November 19, 2020, were included. The quality of studies was assessed by the Newcastle-Ottawa Scale and the Agency for Healthcare Research and Quality (AHRQ) checklist. The meta-analysis was conducted with Stata 15 and drafted according to the guidelines of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement. Results: Seventeen studies (five cohort studies, ten case-control studies, and two cross-sectional studies) were included in meta-analysis, with 1,627 cases in the case group and 5,220 cases in the control group. The incidence of AKI fluctuated from 8.4 to 63.3%. Fifteen risk factors were included, nine of which were significantly associated with an increased risk of AKI in critically ill neonates: gestational age [standardized mean difference (SMD) = -0.31, 95%CI = (-0.51, -0.12), P = 0.002], birthweight [SMD = -0.37, 95%CI = (-0.67, -0.07), P = 0.015], 1-min Apgar score [SMD = -0.61, 95%CI = (-0.78, -0.43), P = 0.000], 5-min Apgar score [SMD = -0.71, 95%CI = (-1.00, -0.41), P = 0.000], congenital heart disease (CHD) [odds ratio (OR) = 2.94, 95%CI = (2.08, 4.15), P = 0.000], hyperbilirubinemia [OR = 2.26, 95%CI = (1.40, 3.65), P = 0.001], necrotizing enterocolitis (NEC) [OR = 6.32, 95%CI = (2.98, 13.42), P = 0.000], sepsis [OR = 2.21, 95%CI = (1.25, 3.89), P = 0.006], and mechanical ventilation [OR = 2.37, 95%CI = (1.50, 3.75), P = 0.000]. Six of them were not significantly associated with AKI in critically ill neonates: age [SMD = -0.25, 95%CI = (-0.54, 0.04), P = 0.095], male sex [OR = 1.10, 95%CI =(0.97, 1.24), P = 0.147], prematurity [OR = 0.90, 95%CI(0.52, 1.56), P = 0.716], cesarean section [OR = 1.52, 95%CI(0.77, 3.01), P = 0.234], prenatal hemorrhage [OR = 1.41, 95%CI = (0.86, 2.33), P = 0.171], and vancomycin [OR = 1.16, 95%CI = (0.71, 1.89), P = 0.555]. Conclusions: This meta-analysis provides a preliminary exploration of risk factors in critically ill neonatal AKI, which may be useful for the prediction of AKI. Systematic Review Registration: PROSPERO (CRD42020188032).

SUBMITTER: Hu Q

PROVIDER: S-EPMC8316634 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundResearch on acute kidney injury (AKI) has focused on identifying early biomarkers. However, whether AKI could be diagnosed in the absence of the classic signs of clinical AKI and whether the condition of subclinical AKI, identified by damage or functional biomarkers in the absence of oliguria or increased serum creatinine (sCr) levels, is clinically significant remains to be elucidated in critically ill children. The aims of the study were to investigate the associations between urinary cystatin C (uCysC) levels and AKI and mortality and to determine whether uCysC-positive subclinical AKI is associated with adverse outcomes in critically ill neonates and children.MethodsIn this prospective cohort study, uCysC levels were serially measured during the first week after intensive care unit (ICU) admission in a heterogeneous group of patients (n = 510) presenting to a tertiary neonatal and pediatric ICU. The diagnosis of neonatal AKI that developed during the first week after admission was based on neonatal KDIGO criteria or sCr >1.5 mg/dL, and pediatric AKI was based on Kidney Disease: Improving Global Outcomes (KDIGO) criteria. The term "uCysC(-)" or "uCysC(+)", indicating the absence or presence of tubular injury, was defined by the optimal peak uCysC cutoff value for predicting ICU mortality.ResultsThe initial and peak uCysC levels were significantly associated with AKI and mortality, and had an area under the receiver operating characteristic curve of 0.76 and 0.81, respectively, for predicting mortality. At the optimal cutoff value of 1260 ng/mg uCr, the peak uCysC displayed sensitivity of 79.2% and specificity of 72.3% for predicting mortality. Among all patients, 130 (25.5%) developed uCysC(+)/AKI(-) status during the first week after admission. The adjusted odds ratio for patients with uCysC(+)/AKI(-) status in association with an increased risk of mortality compared with that for patients with uCysC(-)/AKI(-) was 9.34 (P <?0.001). Patients with uCysC(+)/AKI(-) spent 2.8 times as long in the ICU as those with uCysC(-)/AKI(-) (P <?0.001).ConclusionsBoth initial and peak uCysC levels are associated with AKI and mortality and are independently predictive of mortality in critically ill neonates and children. Subclinical AKI may occur without detectable loss of kidney function, and uCysC-positive subclinical AKI is associated with worse clinical outcomes in this population.

Project description:IntroductionAcute kidney injury (AKI) has high morbidity and mortality in intensive care units, which can lead to chronic kidney disease, more costs and longer hospital stay. Early identification of AKI is crucial for clinical intervention. Although various risk prediction models have been developed to identify AKI, the overall predictive performance varies widely across studies. Owing to the different disease scenarios and the small number of externally validated cohorts in different prediction models, the stability and applicability of these models for AKI in critically ill patients are controversial. Moreover, there are no current risk-classification tools that are standardised for prediction of AKI in critically ill patients. The purpose of this systematic review is to map and assess prediction models for AKI in critically ill patients based on a comprehensive literature review.Methods and analysisA systematic review with meta-analysis is designed and will be conducted according to the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS). Three databases including PubMed, Cochrane Library and EMBASE from inception through October 2020 will be searched to identify all studies describing development and/or external validation of original multivariable models for predicting AKI in critically ill patients. Random-effects meta-analyses for external validation studies will be performed to estimate the performance of each model. The restricted maximum likelihood estimation and the Hartung-Knapp-Sidik-Jonkman method under a random-effects model will be applied to estimate the summary C statistic and 95% CI. 95% prediction interval integrating the heterogeneity will also be calculated to pool C-statistics to predict a possible range of C-statistics of future validation studies. Two investigators will extract data independently using the CHARMS checklist. Study quality or risk of bias will be assessed using the Prediction Model Risk of Bias Assessment Tool.Ethics and disseminationEthical approval and patient informed consent are not required because all information will be abstracted from published literatures. We plan to share our results with clinicians and publish them in a general or critical care medicine peer-reviewed journal. We also plan to present our results at critical care international conferences.Osf registration number10.17605/OSF.IO/X25AT.

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Risk Factors for Acute Kidney Injury in Critically Ill Neonates: A Systematic Review and Meta-Analysis.

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