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. 2025 Mar 5;26:117. doi: 10.1186/s12882-025-04033-2

Incidence of acute kidney injury-associated mortality in hospitalized children: a systematic review and meta-analysis

Hamed Zarei 1, Amir Azimi 1, Arash Ansarian 1, Arian Raad 1, Hossein Tabatabaei 1, Shayan Roshdi Dizaji 1, Narges Saadatipour 1, Ayda Dadras 1, Neamatollah Ataei 2, Mostafa Hosseini 3,4,✉, Mahmoud Yousefifard 1,✉
PMCID: PMC11883935  PMID: 40045255

Abstract

Background

Acute kidney injury (AKI) is a significant health concern in hospitalized children and is associated with increased mortality. However, the true burden of AKI-associated mortality in pediatric populations remains unclear.

Objective

To determine the pooled incidence of mortality independently associated with AKI in hospitalized children globally.

Data sources

Medline and Embase were searched for studies published by March 2024.

Study eligibility criteria

The inclusion criteria encompassed observational studies involving hospitalized pediatric patients (< 18 years old) with AKI. Only studies that identified AKI as an independent risk factor for increased mortality in multivariate analysis were considered.

Study appraisal and synthesis methods

Studies with at least 100 AKI patients were included in the meta-analysis. Two authors extracted data on the study and patients’ characteristics and mortality across AKI stages and assessed the risk of bias. We used a random-effects meta-analysis to generate pooled estimates of mortality.

Results

Analysis of 60 studies including 133,876 children with AKI revealed a pooled in-hospital mortality rate of 18.27% (95% CI: 14.89, 21.65). Mortality increased with AKI severity; 8.19% in stage 1, 13.44% in stage 2, and 27.78% in stage 3. Subgroup analyses showed no significant differences across geographical regions, income levels, or AKI definition criteria. The pooled post-discharge mortality rate was 6.84% (95% CI: 5.86, 7.82) in a 1–9-year follow-up period.

Conclusions

This meta-analysis demonstrates a substantial global burden of AKI-associated mortality in hospitalized children, with higher mortality rates in more severe AKI stages. These findings highlight the critical need for early detection and intervention strategies in pediatric AKI management.

Clinical trial number

Not applicable.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-025-04033-2.

Keywords: Acute kidney injuries; Acute renal injury; Infant; Child, preschool; Cause of death; Child mortality; Acute kidney failures; Fetal outcome; Hospital mortality; Infant, newborn

Introduction

Acute kidney injury (AKI) poses a significant health concern for hospitalized children, leading to adverse outcomes and increased in-hospital and post-discharge mortality rates [1]. In efforts to standardize AKI diagnosis, several classification systems like KDIGO and RIFLE have been introduced to gain better insights into this condition and its effects on children. The lack of consensus on a universally accepted standardized definition for AKI in children has resulted in variations in its incidence and staging [2]. Furthermore, AKI has been significantly associated with short-term adverse outcomes, including prolonged hospital stays and in-hospital mortality [3]. Additionally, AKI has demonstrated links to long-term consequences such as hypertension, proteinuria, and chronic kidney disease in infants and children, potentially leading to post-discharge mortality. This highlights the necessity for comprehensive management strategies [4]. Nevertheless, irrespective of the setting of patients, mortality rates are proved to be higher among patients with AKI compared to those without AKI [1] and there is an ongoing investigation into the incidence of AKI-associated mortality in different pediatric populations.

To devise effective interventions, it is crucial to comprehend the incidence of AKI-associated mortality in diverse groups of children. Studies have indicated that the occurrence of AKI varies, with rates ranging from 5 to 31% in non-critically ill hospitalized children and up to 55% in critically ill hospitalized children [5–8]. Moreover, the burden and causes of AKI vary worldwide, with different resource settings facing distinct challenges. Some studies show low and low-to-middle-income countries experience a higher incidence of AKI due to factors like contaminated water and endemic diseases, such as malaria [4]. In such settings, the mortality of AKI can be worse than high-income countries [4].

Despite the existing literature on AKI mortality, a knowledge gap remains regarding the true burden and mortality rates associated with AKI in children. A previous meta-analysis have reported mortality rates of 11% among hospitalized children with AKI, but these rates have not been statistically proven to be independently associated with AKI via multivariate analysis in many of the included studies [1]. Confounding factors and the complexity of critically ill children contribute to the challenges in attributing mortality solely to AKI. Therefore, our systematic review and meta-analysis aims to determine the overall rate of mortality that is directly linked to AKI in children on a global scale. By synthesizing available evidence, this study intends to enhance our understanding of the impact of AKI on pediatric patients.

Methods

Study design

This review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines [9] and was prospectively registered on the International Prospective Register of Systematic Reviews (PROSPERO ID: CRD42024527413). To identify relevant studies, an extensive literature search was performed across Medline (via Pubmed) and Embase in March 18th 2024. In order to optimize search results, tailored search strategies were developed for each database, incorporating pertinent keywords and Medical Subject Headings (MeSH) terms directly related to acute kidney injury (AKI) in the pediatric population (Supplemental material 1). Language restrictions were avoided during the literature search process. Articles in languages other than English were translated using online services such as Doc Translator, and then have them reviewed by an expert translator fluent in both the original language and English to ensure accuracy. Additionally, to enrich our electronic search, we manually scrutinized the bibliographies of eligible studies that met our inclusion criteria.

Study selection

To generate pooled global estimates of AKI mortality, we established rigorous inclusion criteria for selecting relevant studies. Specifically, we only included cohort and cross-sectional studies that reported AKI-related mortality, given that they demonstrated an independent association between AKI and mortality through the application of multivariate analysis. We investigated mortality rates during hospitalization and after discharge, in the pediatric population aged below 18 years. To ensure methodological consistency and the integrity of our analysis, we implemented a series of exclusion criteria. Studies on adults aged over 18 years were excluded from consideration. Additionally, we omitted studies in the form of conference abstracts that did not provide sufficient information for a robust assessment of diagnostic criteria and risk of bias. To achieve an objective screening process, eight authors in pairs independently assessed the titles and abstracts of the electronic records initially. Subsequently, the same authors meticulously evaluated the full texts of relevant articles to determine the final selection of studies for incorporation into our review. In the event of any disagreements between the two authors, a collaborative discussion was undertaken to reach a consensus. This methodological approach guarantees the quality and reliability of our pooled estimates of AKI mortality in the global pediatric population.

Data extraction and quality assessment

The full set of records was divided into four equal parts, with each part independently screened (title/abstract and full-text) by a pair of authors. Each pair reviewed their assigned portion, discussing and resolving any discrepancies between them. Any unresolved conflicts were addressed with the involvement of a third reviewer (MY). This division and screening process ensured that all records were reviewed independently by at least two authors, as recommended by the PRISMA guidelines, while accommodating the high volume of records.

The data extracted included the first author’s name, year of publication, country, data gathering period, study design, clinical setting (e.g., intensive care unit, cardiac surgery, etc.), participants’ age, sample size, number of children with AKI and its severity, in-hospital and post-discharge mortality number in AKI patients among each stage, AKI criteria and definition, and follow-up duration. We also extracted data indicating countries’ development and overall health status including gross domestic income per capita (GDP) [10], % GDP spent on total health expenditure [11], and maternal mortality ratio (MMR) [12] defined as deaths due to complications from pregnancy or childbirth per 100,000 live births.

Based on KDIGO criteria, we equaled the AKI stages in all studies into 3 stages. For RIFLE, pRIFLE, and nRIFLE, “Risk”, “Injury”, and “Failure”, were considered equivalent to KDIGO stage 1, stage 2, and stage 3, respectively. Since many studies had categorized AKI with merged stages, we reported stage-1 and 2, and stage-2 and 3 together for these studies. To assess the risk of bias in the included studies, we utilized the National Heart, Lung, and Blood Institute Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies [13].

Statistical analysis

All statistical analyses were conducted using the STATA 18.0 statistical program. To calculate the incidence of mortality among hospitalized patients with AKI, we employed the “meta” package with the random-effect model and reported a pooled incidence with a 95% confidence interval (95% CI). Statistical heterogeneity was assessed using I2 and Chi-square tests. To explore the potential sources of heterogeneity, we performed subgroup analyses as per severity of AKI, clinical setting, study design, and economic groups of countries classified by World Bank.

To better understand and interpret the results with and without small-study effects on the incidence of AKI-associated mortality, we conducted meta-analyses on studies of any sample size and separately on studies with a minimum of 100 AKI patients. Our findings primarily emphasize the results from the latter group, which are presented in the manuscript. For interested readers, the supplementary material includes a table providing subgroup analysis and meta-regressions that incorporate studies without excluding studies with smaller sample sizes.

Meta-regressions were performed to assess the effects of gross domestic product (GDP) per capita in the year 2022 and % of GDP spent on health expenditure (the year 2020), and maternal mortality ratio (2000–2020) on AKI-associated mortality.

Since only five included studies assessed post-discharge mortality, subgroup analysis and meta-regression was not applicable for post-discharge mortality.

Results

Study selection and characteristics of the included studies

We identified 26,797 records from electronic databases. After screening 363 full-text articles, 96 studies were included in this systematic review [3, 14–108] (Fig. 1). The meta-analysis data comprised 96 in-hospital and 5 post-discharge mortality observations. These studies, from over 24 countries, enrolled a total of 135,448 hospitalized children with AKI. All of these studies reported mortality, which was confirmed to be independently associated with AKI. The characteristics of the included studies are reported in Table 1.

Fig. 1.

Fig. 1

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The PRISMA flow diagram depicts the flow of the study selection process through the different phases of the present systematic review

Table 1.

Summary characteristics of the included studies

Author, year Country Study Design Etioology Neonates/Infants & Children Admission sites Aki Criteria AKI (n) Mortality (Overall) Mortality Assessment
Adegboyega, 2022 [109] USA Retrospective LBW Only neonate NICU KDIGO 116 21 In-hospital
Ahn, 2024 [108] USA Retrospective Hypoxic ischemic encephalopathy Only neonate NICU KDIGO 64 10 In-hospital
Akcan-Arikan, 2007 [107] USA Prospective Mixed Non-neonate PICU pRIFLE 123 18 In-hospital
Al Gharabieh, 2023 [106] USA retrospective Sepsis Only neonate NICU KDIGO 16 7 In-hospital
Algadeeb, 2021 [104] Saudi Arabia Retrospective Mixed Only neonate NICU KDIGO 396 122 In-hospital
Al-Mouqdad, 2021 [105] Saudi Arabia Retrospective LBW Only neonate NICU KDIGO 268 79 In-hospital
Alobaidi, 2019 [103] Canada Retrospective Mixed Non-neonate PICU KDIGO 308 21 In-hospital
Alvarez-Hernandez, 2015 [102] Mexico Retrospective Infection Neonate and non-neonate PICU, NICU and ward NR 14 7 In-hospital
Arruda Moraes, 2023 [15] Brazil Retrospective LBW Only neonate NICU KDIGO 61 22 In-hospital
Bakkaloglu, 2024 [101] Turkey Retrospective Crush-AKI Neonate and non-neonate Mix oligo/anuria or serum creatinine level > 2 times the upper limit of age- and sex-referenced normal levels 314 20 In-hospital
Basu, 2021 [100] multinational Prospective Sepsis/Infectious Non-neonate PICU KDIGO 307 37 In-hospital
Bauer, 2023 [99] USA Retrospective Hematopoietic cell transplantation Non-neonate PICU and ward KDIGO 186 47 In-hospital
Bezerra, 2013 [91] Brazil Retrospective Infectious Only neonate NICU pRIFLE 51 19 In-hospital
Bradshaw, 2019 [98] USA Retrospective Diarrheal illness Neonate and non-neonate PICU, NICU and ward ICD-9-CM 616 4 in-hospital
Chen, 2023 [97] Taiwan Retrospective Prematurity Only neonate NICU mKDIGO 204 55 In-hospital
Coggins, 2021 [96] USA Retrospective Sepsis Only neonate NICU mKDIGO 56 17 In-hospital
Conroy, 2019 [95] Uganda Prospective Malaria Non-neonate PICU KDIGO 168 20 In-hospital and Post-discharge
Conroy, 2022 [94] Uganda retrospective Blackwater fever + Malaria Non-neonate PICU and ward KDIGO 495 20 In-hospital
Cui, 2022 [93] China Retrospective Non-Cardiac surgery Only neonate NICU KDIGO 28 9 In-hospital
Dang, 2022 [92] China Retrospective Mixed Non-neonate PICU and ward KDIGO 419 30 In-hospital
Deep, 2018 [90] UK Prospective Septic shock Non-neonate PICU KDIGO 31 9 In-hospital
Demiroz, 2024 [89] Turkey Retrospective Liver transplant Non-neonate PICU and ward KDIGO 60 27 In-hospital
Dos Santos El Halal, 2013 [88] Brazil Prospective Cardiac surgery Non-neonate PICU pRIFLE 38 7 In-hospital
Downes, 2017 [87] USA Retrospective Antibiotic associated AKI Non-neonate PICU KDIGO 157 7 In-hospital
Elgendy,2023 [85] USA retrospective Diaphragmatic hernia Only neonate NICU ICD9,10 445 239 In-hospital
Elgendy, 2021 [84] USA Retrospective LBW Only neonate NICU NR 19,603 6872 In-hospital
Elgendy, 2024 [86] USA retrospective Hypoxic-ischemic encephalopathy Only neonate NICU ICD9,10 2719 786 In-hospital
Esmaeili, 2024 [83] IRAN Retrospective Cardiac surgery Non-neonate PICU KDIGO 58 16 In-hospital
Fitzgerald, 2016 [82] multinational Prospective Sepsis/Infectious Non-neonate PICU KDIGO 102 53 In-hospital
Fleming, 2016 [81] milticenter Retrospective ECMO Neonate and non-neonate PICU and NICU KDIGO 615 311 In-hospital
Gil-Ruiz, 2014 [80] Spain Retrospective Cardiac surgery Non-neonate PICU pRIFLE 107 16 In-hospital
Hasson, 2024 [79] USA retrospective Cardiac surgery Only neonate NICU mKDIGO 205 18 In-hospital
Hessey, 2018 [78] Canada Retrospective Non-Cardiac surgery Non-neonate PICU KDIGO 355 34 Post-discharge
Hingorani, 2021 [77] USA Prospective LBW Only neonate NICU KDIGO 350 45 In-hospital
Hirabayashi, 2022 [76] Japan retrospective Prematurity Only neonate NICU nRIFLE 47 12 In-hospital
Hui, 2013 [75] Hong Kong Retrospective Mixed Non-neonate PICU pRIFLE 71 16 In-hospital
Iamwat, 2021 [74] Thailand Retrospective ECMO Neonate and non-neonate PICU and NICU KDIGO 10 7 In-hospital
Ibrahim, 2023 [73] Nigeria Retrospective Malaria Non-neonate Mix KDIGO 237 19 In-hospital
Imani, 2013 [72] Uganda Prospective Infectious Non-neonate PICU pRIFLE 272 68 In-hospital
Jetton, 2017 [71] multinational Retrospective Mixed Only neonate NICU KDIGO 605 59 In-hospital
Kaddourah, 2017 [70] Asia, AU, EU, NA Prospective Mixed Non-neonate PICU KDIGO 1261 82 In-hospital
Kari, 2017 [14] Saudi Arabia Prospective Mixed Non-neonate PICU KDIGO 511 99 In-hospital
Kasililika, 2020 [69] Tanzania Prospective Mixed Non-neonate PICU KDIGO 53 19 In-hospital
Khatana, 2023 [68] USA retrospective Severe Sepsis Non-neonate not specified ICD 45,463 9005 In-hospital
Kriplani, 2016 [67] USA Retrospective Mixed Non-neonate PICU KDIGO 28 8 In-hospital
Kuai, 2022 [17] China Prospective Mixed Non-neonate PICU KDIGO 22 14 In-hospital
Kuai, 2022 [66] China Prospective Mixed Non-neonate PICU KDIGO 247 47 In-hospital
Kumar Sethi, 2024 [65] multinational prospective Continuous kidney replacement therapy Non-neonate PICU KDIGO 308 99 In-hospital
Lazarovits, 2023 [64] Israel retrospective Prematurity Only neonate NICU NIDDK 32 13 In-hospital
Leow, 2022 [63] Singapore Retrospective Acute respiratory distress syndrome Non-neonate PICU KDIGO 64 41 In-hospital
Lobasso, 2021 [62] USA retrospective Cardiac surgery Neonate and non-neonate PICU/NICU KDIGO 701 80 In-hospital
Lu, 2022 [61] China retrospective Cardiac surgery Only neonate CICU, NICU KDIGO 131 38 In-hospital
Medar, 2015 [60] USA Retrospective Heart failure Non-neonate Not specified pRIFLE 44 4 In-hospital
Mengqi, 2020 [59] China Retrospective Malignancy Non-neonate Not specified KDIGO 1657 90 in-hospital
Moffett, 2022 [58] USA Retrospective Mixed Non-neonate Not specified KDIGO 10,246 590 In-hospital
Mohamed, 2023 [57] USA retrospective Non-Cardiac surgery Only neonate NICU ICD-9 and 10 2625 431 In-hospital
Morgan, 2013 [56] Canada Prospective Cardiac surgery Only neonate NICU AKIN 163 10 Post-discharge
Murdeshwar, 2023 [55] India ambispective Mixed Non-neonate PICU/Ward ADQI 200 37 In-hospital
Nakwan, 2016 [54] Thailand Retrospective Pulmonary hypertension Only neonate NICU

A serum

creatinine level of 41.5 mg/dL on two separate occasions at

least 12 h apart, while maternal kidney function was normal

 31 22 In-hospital
Namazzi, 2022 [53] Uganda Prospective Malaria Non-neonate Not specified KDIGO 271 37 In-hospital and Post-discharge
Özçakar, 2009 [52] Turkey Retrospective Mixed Non-neonate Not specified AKIN 100 33 In-hospital
Patel, 2023 [51] USA retrospective Mixed Neonate and non-neonate PICU/NICU/ward KDIGO 528 138 In-hospital
Pedersen, 2008 [50] Denmark Retrospective Cardiac surgery Neonate and non-neonate PICU and NICU need for dialysis after surgery 130 26 In-hospital
Pillon, 2019 [49] Italy Retrospective Malignancy Non-neonate PICU KDIGO 17 12 In-hospital
Piyaphanee, 2020 [48] Thailand Retrospective Mixed Non-neonate PICU KDIGO 169 53 in-hospital
Plumb, 2023 [47] UK retrospective Mixed Only neonate NM KDIGO 712 59 In-hospital
Plumb, 2023 [47] UK retrospective Mixed Non-neonate NM KDIGO 4900 150 In-hospital
Prodhan, 2012 [46] USA Retrospective Trauma Non-neonate PICU pRIFLE 52 10 In-hospital
Raina, 2022 [45] USA retrospective Covid/infectious Non-neonate PICU KDIGO 274 21 In-hospital
Raina, 2023 [44] USA retrospective Mixed Neonate and non-neonate NM ICD-10 2424 11 In-hospital
Robinson, 2021 [43] Canada Retrospective Mixed Neonate and non-neonate Not specified ICD-9 and 10 1688 113 Post-discharge
Rozmiarek, 2004 [42] USA Retrospective Diaphragmatic hernia Only neonate NICU NR 14 10 In-hospital
Sainathan, 2022 [41] USA Retrospective LBW Non-neonate Not specified ICD-10 98 8 In-hospital
Sainathan, 2022 [41] USA Retrospective Fontan Operation Non-neonate PICU and ward NR 97 8 In-hospital
Sanchez-Pinto, 2015 [40] USA Retrospective Mixed Non-neonate PICU KDIGO 974 246 in-hospital
Schneider, 2010 [39] USA Retrospective Mixed Non-neonate PICU pRIFLE 339 104 In-hospital
Schueller, 2017 [38] USA Retrospective ECMO Only neonate NICU KDIGO 15 7 In-hospital
Selewski, 2014 [37] USA Retrospective Mixed Non-neonate PICU and CICU KDIGO 737 83 In-hospital
Selewski, 2023 [36] multinational prospective mixed Non-neonate PICU KDIGO 1258 78 In-hospital
Shalaby, 2018 [35] Saudi Arabia Prospective Mixed Only neonate NICU nKDIGO 120 34 In-hospital
Sharma, 2022 [34] India Retrospective Covid/infectious Non-neonate Not specified NR 12 9 In-hospital
Singh, 2022 [33] India Prospective Mixed Non-neonate PICU KDIGO 44 14 In-hospital
Slagle, 2021 [32] USA Prospective Non-Cardiac surgery Only neonate NICU mKDIGO 33 8 In-hospital
Smith, 2009 [31] USA Retrospective ECMO Neonate and non-neonate PICU and NICU pRIFLE 32 23 In-hospital
Srinivasan, 2018 [30] USA Retrospective LBW Only neonate NICU mAKIN 89 25 In-hospital
Stanski, 2023 [29] USA Prospective Mixed Non-neonate PICU KDIGO 77 14 In-hospital
Starr, 2020 [28] USA Prospective septic shock Non-neonate PICU KDIGO 176 27 In-hospital
Stojanović, 2017 [27] Serbia Retrospective LBW Only neonate NICU mAKIN 57 35 In-hospital
Umapathi, 2020 [26] USA Retrospective Drowning Non-neonate PICU and ward NR 752 403 In-hospital
Üstün, 2021 [25] Turkey Retrospective LBW Only neonate NICU KDIGO 102 34 In-hospital
Varadarajan, 2022 [24] India Prospective Multisystem Inflammatory syndrome Non-neonate PICU and ward KDIGO 34 22 In-hospital
Vincent, 2023 [23] USA Retrospective Mixed Only neonate NICU KDIGO 100 14 In-hospital
Wang, 2022 [22] China Retrospective Metabolic Acidosis Non-neonate PICU and SICU (Surgical ICU) pROCK 181 22 In-hospital
Wei, 2021 [21] China Retrospective Mixed Non-neonate PICU pROCK 257 32 In-hospital
Wingert, 2021 [20] USA Retrospective Non-Cardiac surgery Neonate and non-neonate PICU, NICU and ward KDIGO 288 23 in-hospital
Xu, 2018 [18] China Retrospective Mixed Non-neonate PICU and ward KDIGO 19,908 842 In-hospital
Xu, 2023 [19] China Retrospective Mixed Only neonate NICU Cys-C based criteria 6336 96 In-hospital
Zwiers, 2013 [16] Netherlands Prospective ECMO Only neonate NICU RIFLE 153 43 In-hospital
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ADQI: Acute Dialysis Quality Initiative; AKIN: Acute Kidney Injury Network; CICU: Cardiac Intensive Care Unit; Cys-C: Cystatin C; ECMO: Extracorporeal Membrane Oxygenation; ICD-9-CM: International Classification of Diseases, Ninth Revision, Clinical Modification; KDIGO: Kidney Disease: Improving Global Outcomes; LBW: Low Birth Weight; mAKIN: Modified Acute Kidney Injury Network; NICU: Neonatal Intensive Care Unit; NR: Not Reported; nKDIGO: Neonatal Kidney Disease: Improving Global Outcomes; PICU: Pediatric Intensive Care Unit; pRIFLE: Pediatric Risk, Injury, Failure, Loss, End-Stage Renal Disease; pROCK: Pediatric Reference Operative Check for Kidney Dysfunction; SICU: Surgical Intensive Care Unit

Among 101 observations, 13 reported AKI in children with prematurity-related outcomes, 14 with infections, 9 with cardiac surgery, 7 with non-cardiac surgery, 6 with sepsis/septic shock, 5 with ECMO, 33 with mixed conditions, and 14 with miscellaneous conditions. Twenty-seven of the studies were prospective. The geographical distribution of the studies was as follows: 49 from the Region of the Americas (AMR), 15 from the Western Pacific Region (WPR), 12 from the European Region (EUR), 8 from the African Region (AFR), 7 from the South-East Asia Region (SEAR), and 6 from the Eastern Mediterranean Region (EMR). The remaining studies were multinational. Thirty-eight studies included urine output in their AKI diagnostic criteria, and 33 studies enrolled exclusively neonates.

Risk of bias assessment

In the quality control section, it was noted that the majority of studies did not provide justification for the sample size (item 5). Moreover, the blinding status of the outcome observer was not a concern for causing bias since the outcome measured was mortality (item 12). The proportion of patients lost to follow-up could not be determined or was not reported in some studies (item 13). Most studies exhibited a low risk of bias in other domains (Table 2).

Table 2.

Risk of bias assessment by NHLBI tool in included studies

Study Item 1 Item 2 Item 3 Item 4a Item 4b Item 5 Item 6 Item 7 Item 8 Item 9 Item 10 Item 11 Item 12 Item 13 Item 14
Adegboyega, 2022 Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes NA Yes Yes
Ahn, 2024 Yes Yes CD No No No Yes Yes Yes Yes Yes Yes NA Yes Yes
Akcan-Arikan, 2007 Yes No CD Yes Yes No Yes Yes Yes Yes Yes Yes NA NR Yes
Al Gharabieh, 2023 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Algadeeb, 2021 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Al-Mouqdad, 2021 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Alobaidi, 2019 Yes Yes Yes Yes Yes No Yes Yes Yes No Yes Yes NA Yes Yes
Alvarez-Hernandez, 2015 Yes Yes CD Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Arruda Moraes, 2023 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Bakkaloglu, 2024 Yes Yes CD Yes CD No Yes Yes Yes Yes Yes Yes NA NR Yes
Basu, 2021 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Bauer, 2023 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Bradshaw, 2019 Yes Yes Yes Yes CD No Yes CD NR No CD Yes NA Yes No
Chen, 2023 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Coggins, 2021 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Conroy, 2019 Yes Yes Yes Yes Yes No Yes Yes Yes Yes No Yes NA Yes Yes
Conroy, 2022 Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes CD Yes NA Yes Yes
Cui, 2022 Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes NA Yes Yes
Dang, 2022 Yes Yes No Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Bezerra, 2013 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Deep, 2018 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Demiroz, 2023 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Dos Santos El Halal, 2013 Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes NA Yes Yes
Downes, 2017 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Elgendy, 2024 Yes Yes Yes Yes Yes No Yes CD NR CD CD Yes NA Yes Yes
Elgendy,2023 Yes Yes Yes Yes Yes No Yes CD NR CD CD Yes NA Yes Yes
Elgendy, 2021 Yes Yes Yes Yes Yes No Yes CD NR CD CD Yes NA Yes Yes
Esmaeili, 2024 Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes CD Yes NA Yes Yes
Fitzgerald, 2016 Yes No Yes Yes Yes No Yes Yes Yes Yes CD Yes NA Yes Yes
Fleming, 2016 Yes Yes Yes Yes Yes No Yes Yes Yes No Yes Yes NA Yes Yes
Gil-Ruiz, 2014 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Hasson, 2024 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Hessey, 2018 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Hingorani, 2021 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Hirabayashi, 2022 Yes Yes No Yes Yes No Yes Yes Yes No Yes Yes NA Yes Yes
Hui, 2013 Yes Yes CD Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Iamwat, 2021 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Ibrahim, 2023 Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes CD Yes NA Yes Yes
Imani, 2013 Yes Yes No Yes Yes No Yes Yes Yes Yes No Yes NA Yes Yes
Jetton, 2017 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Kaddourah, 2017 Yes Yes Yes Yes Yes No Yes Yes Yes Yes CD Yes NA Yes Yes
Kari, 2017 Yes Yes CD Yes Yes No Yes Yes Yes Yes CD Yes NA CD Yes
Kasililika, 2020 Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes NA Yes Yes
Khatana, 2023 Yes Yes CD Yes Yes No Yes CD CD CD CD Yes NA CD Yes
Kriplani, 2016 Yes Yes CD Yes Yes No Yes Yes Yes Yes Yes Yes NA CD Yes
Kuai, 2022 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Kuai, 2022 Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes NA Yes Yes
Kumar Sethi, 2023 Yes Yes CD Yes Yes No Yes Yes Yes Yes Yes Yes NA CD Yes
Leow, 2022 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No CD Yes
Lobasso, 2021 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No Yes Yes
Lu, 2022 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No CD Yes
Medar, 2015 Yes Yes Yes Yes Yes No Yes CD No Yes NA Yes No CD Yes
Mengqi, 2020 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No CD Yes
Moffett, 2022 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No CD Yes
Mohamed, 2023 Yes Yes Yes Yes Yes No Yes CD No Yes NA Yes No CD Yes
Morgan, 2013 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No CD Yes
Murdeshwar, 2023 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No Yes Yes
Nakwan, 2016 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No Yes Yes
Namazzi, 2022 Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes NA Yes No Yes Yes
Özçakar, 2009 Yes Yes Yes Yes Yes No Yes CD Yes Yes NA Yes No CD Yes
Patel, 2023 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No CD Yes
Pedersen, 2008 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No CD Yes
Pillon, 2019 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No Yes Yes
Piyaphanee, 2020 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No No Yes
Plumb, 2023 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No CD Yes
Prodhan, 2012 Yes Yes Yes Yes Yes No Yes CD Yes Yes NA Yes No CD Yes
Raina, 2022 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No CD Yes
Raina, 2023 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No CD Yes
Robinson, 2021 Yes Yes Yes Yes Yes Yes Yes Yes No Yes NA Yes No Yes Yes
Rozmiarek, 2004 Yes Yes Yes Yes Yes No Yes CD No Yes NA Yes No CD Yes
Sainathan, 2022 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No CD Yes
Sanchez-Pinto, 2015 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No CD Yes
Schneider, 2010 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No CD Yes
Schueller, 2017 Yes Yes Yes Yes Yes Yes Yes CD No Yes NA Yes No CD Yes
Selewski, 2014 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No CD Yes
Selewski, 2023 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No Yes Yes
Shalaby, 2018 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No Yes Yes
Sharma, 2022 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No CD Yes
Singh, 2022 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No Yes Yes
Slagle, 2021 Yes Yes Yes Yes Yes No Yes CD No Yes NA Yes No Yes Yes
Smith, 2009 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No CD Yes
Srinivasan, 2018 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No CD Yes
Stanski, 2023 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No No Yes
Starr, 2020 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No No Yes
Stojanović, 2017 Yes Yes Yes Yes Yes No Yes CD Yes Yes NA Yes No CD Yes
Umapathi, 2020 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No CD Yes
Üstün, 2021 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No No Yes
Varadarajan, 2022 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No CD Yes
Vincent, 2023 Yes Yes Yes Yes Yes Yes Yes Yes No Yes NA Yes No CD Yes
Wang, 2022 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No Yes Yes
Wei, 2021 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No CD Yes
Wingert, 2021 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No CD Yes
Xu, 2023 Yes Yes Yes Yes Yes No Yes Yes No Yes NA Yes No CD Yes
Xu, 2018 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No CD Yes
Zwiers, 2013 Yes Yes Yes Yes Yes No Yes Yes Yes Yes NA Yes No Yes Yes
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CD, cannot determine; NA, Not applicable; NR, not reported

Meta-analysis of the AKI-associated in-hospital and post-discharge mortality

Since the meta-analysis was conducted using a random-effects model, small studies (n < 100) were assigned weights comparable to larger studies (n ≥ 100), leading to a pronounced small-study effect (Supplementary Fig. 1). To provide more robust and generalizable estimates of AKI-associated mortality across diverse patient- and country-level characteristics, we excluded studies with fewer than 100 AKI patients in the main meta-analysis. For comparison, the pooled AKI-associated in-hospital mortality, including small studies (n < 100), is shown in Supplementary Fig. 2.

The pooled incidence of AKI-associated in-hospital mortality (60 studies, 133876 participants) was 18.27% (95% CI: 14.89, 21.65) (Fig. 2). Using a KDIGO-equivalent AKI definition, the pooled AKI-associated mortality rate among patients with AKI stage 1, stage 2, and stage 3 was 8.19% (95% CI: 5.65, 10.73), 13.44% (95% CI: 8.69, 18.19), and 27.78% (95% CI: 21.82, 33.74), respectively, as depicted in Figs. 3, 4 and 5. Some studies reported AKI in merged staging of 1 to 2, and 2 to 3. Pooled mortality in AKI stage 1 to 2 and AKI stage 2 to 3 was 12.54% (95% CI: 8.05, 17.02) and 23.50% (95% CI: 18.62, 28.39), respectively (Supplementary Figs. 3–4). We observed significant heterogeneity in the overall in-hospital mortality pooled estimate (I2 = 99.84%). Considering that we pooled data from studies with diverse sample sizes, clinical settings, and severities of AKI, some heterogeneity was expected. To explore potential sources of heterogeneity, we performed subgroup analyses and meta-regressions, as reported in Table 3. Compared to AKI stage 1, the mortality rate was significantly higher in AKI stage 3 (meta-regression coefficient = 0.19 [95% CI: 0.12, 0.25]; p < 0.001), and from AKI stage 2 to stage 3 (meta-regression coefficient = 0.15 [95% CI: 0.09, 0.20]; p < 0.001). The pooled mortality rates were 21.81% (95% CI: 16.84, 80.75) for neonates and 16.56% (95% CI: 12.37, 20.75) for older children. Thirty-nine studies used only a serum creatinine-based definition for AKI, reporting a pooled mortality rate of 18.19% (95% CI: 14.08, 22.30). In comparison, 18 studies using both urine output and serum creatinine-based criteria reported a mortality rate of 17.31% (95% CI: 11.96, 22.66). No differences in the pooled incidence of mortality were observed between prospective and retrospective studies, nor among different geographical regions or countries with different income levels (Fig. 6). AKI-associated mortality rates using KDIGO/mKDIGO and pRIFLE/RIFLE/nRIFLE criteria were 16.76% (95% CI: 13.01, 20.51) and 22.81% (95% CI: 17.46, 33.94), respectively. Meta-regression showed no significant difference (meta-regression coefficient = 0.06 [95% CI: -0.07, 0.19]; p = 0.634). The median sampling period was not significantly associated with the incidence of AKI-associated mortality (meta-regression coefficient = -0.007 [95% CI: -0.014, 0.0004]; p = 0.065). A meta-regression assessing the effects of GDP, its proportion spent on health, and maternal mortality rate (Supplementary Fig. 5) revealed no significant associations with AKI mortality rate (p = 0.491, p = 0.662, and p = 0.308, respectively). The pooled post-discharge mortality rate associated with AKI (from 5 studies including 2,556 participants) was 6.84% (95% CI: 5.86, 7.82) with a median follow-up ranging from 1 to 9 years, as shown in Fig. 7. Subgroup analyses and meta-regressions for all studies including the ones with less than 100 AKI patients are presented in Supplementary Table 1.

Fig. 2.

Fig. 2

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The forest plot for the incidence of in-hospital mortality among hospitalized children with acute kidney injury

Fig. 3.

Fig. 3

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The forest plot for the incidence of in-hospital mortality among hospitalized children with stage 1 acute kidney injury

Fig. 4.

Fig. 4

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The forest plot for the incidence of in-hospital mortality among hospitalized children with stage 2 acute kidney injury

Fig. 5.

Fig. 5

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The forest plot for the incidence of in-hospital mortality among hospitalized children with stage 3 acute kidney injury

Table 3.

Subgroup analysis and meta-regression for incidence of in-hospital AKI-associated mortality (excluding smaller studies with < 100 AKI patients)

Subgroups Studies (participants) Incidence of mortality (%), (95 CI) Heterogeneity (I²), P Coefficient (95 CI) Subgroup differences (P)
Severity of AKI
AKI stage 1 26 (14843) 8.19 (5.65, 10.73) 97.8, < 0.001 Reference
AKI stage 2 20 (8044) 13.44 (8.69, 18.19) 97.4, < 0.001 0.049 (-0.015, 0.113) 0.136
AKI stage 3 21 (8487) 27.78 (21.82, 33.74) 96.8, < 0.001 0.187 (0.123, 0.252) < 0.001
AKI stage 1 and 2 20 (21780) 12.54 (8.05, 17.02) 99.3, < 0.001 0.040 (-0.023, 0.104) 0.211
AKI stage 2 and 3 28 (17040) 23.50 (18.62, 28.39) 98.2, < 0.001 0.146 (0.088, 0.205) < 0.001
Age
< 1 month 18 (35190) 22.81 (16.84, 20.75) 99.57, < 0.001 Reference
> 1 month 34 (93070) 16.56 (12.37, 20.75) 99.78, < 0.001 -0.062 (-0.138, 0.013) 0.107
Study design
Prospective study 15 (5627) 19.34 (13.66, 25.03) 97.67, < 0.001 Reference
Retrospective study 44 (128049) 17.88 (13.70, 22.07) 99.90, < 0.001 -0.016 (-0.096, 0.064) 0.691
Country income classification (as per gross national income per capita)
Low income 5 (1443) 12.31 (5.44, 19.17) 94.80, < 0.001 Reference
Lower-middle income 1 (200) Insufficient data Insufficient data Insufficient data Insufficient data
Upper-middle income 12 (29821) 15.65 (8.87, 22.44) 99.8, < 0.001 0.033 (-0.097, 0.163) 0.623
High-income 35 (97956) 18.88 (14.56, 23.20) 99.8, < 0.001 0.064 (-0.052, 0.181) 0.279
Region
AFR 5 (1443) 12.31 (5.44, 19.17) 94.8, < 0.001 Reference
AMR 28 (92635) 18.66 (13.12, 24.20) 99.9, < 0.001 0.062 (-0.060, 0.184) 0.320
EMR 4 (1295) 26.69 (21.01, 32.37) 80.3, < 0.001 0.145 (-0.025, 0.315) 0.095
EUR 8 (6518) 17.77 (9.41, 26.13) 98.5, < 0.001 0.054 (-0.090, 0.199) 0.462
SEAR 2 (369) 24.73 (12.13, 37.33) 87.7, < 0.001 0.124 (-0.089, 0.337) 0.255
WPR 9 (29340) 12.64 (6.35, 18.94) 99.8, < 0.001 0.004 (-0.137, 0.145) 0.956
AKI criteria
KDIGO/mKDIGO 40 (50717) 16.76 (13.01, 20.51) 99.6, < 0.001 Reference
RIFLE/pRIFLE/nRIFLE 5 (994) 22.81 (16.28, 29.34) 83.5, < 0.001 0.059 (-0.068, 0.186) 0.364
AKIN/mAKIN 1 (100) Insufficient data Insufficient data Insufficient data Insufficient data
ICD-9/ICD-10 6 (54292) 19.91 (4.05, 35.77) 100.0, < 0.001 0.030 (-0.085, 0.145) 0.610
Miscellaneous 8 (27773) 19.96 (8.15, 31.76) 99.8, < 0.001 0.031 (-0.071, 0.134) 0.549
AKI criteria based on
SCr 39 (124124) 18.19 (14.08, 22.30) 99.9, < 0.001 Reference
SCr + UOP 18 (6376) 17.31 (11.96, 22.66) 98.0, < 0.001 -0.008 (-0.079, 0.063) 0.831
Predisposing condition
Prematurity-related outcomes 6 (20643) 25.88 (18.63, 33.13) 94.9, < 0.001 Reference
Sepsis/septic shock 3 (45946) 16.06 (11.21, 20.90) 86.5, < 0.001 -0.102 (-0.279, 0.076) 0.262
Infections 8 (2435) 14.94 (4.02, 25.86) 99.4, < 0.001 -0.112 (-0.248, 0.024) 0.108
Cardiac surgery 5 (1274) 16.27 (9.48, 23.06) 90.0, < 0.001 -0.093 (-0.246, 0.061) 0.235
Non-cardiac surgery 3 (3358) 25.98 (-1.48, 53.44) 99.6, < 0.001 -0.001 (-0.178, 0.176) 0.992
ECMO 2 (768) 39.54 (17.53, 61.55) 96.6, < 0.001 0.137 (-0.069, 0.344) 0.193
Mixed etiology 25 (53178) 14.61 (10.55, 18.67) 99.8, < 0.001 -0.112 (-0.227, 0.003) 0.056
Miscellaneous a 8 (6274) 21.00 (9.03, 32.97) 99.4, < 0.001 -0.050 (-0.186, 0.086) 0.475
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CI, confidence interval; AFR, African Region; AMR, Region of the Americas; EMR, Eastern Mediterranean Region; EUR, European Region; SEAR, South-East Asia Region; WHO, World Health Organization; WPR, Western Pacific Region; KDIGO, Kidney Disease: Improving Global Outcomes; mKDIGO, modified KDIGO; RIFLE, Risk, Injury, and Failure; and Loss; and End-stage kidney disease; pRIFLE, pediatric RIFLE; nRIFLE, neonatal RIFLE; AKIN, Acute Kidney Injury Network; mAKIN, modified AKIN; ICD, The International Classification of Diseases; SCr, serum creatinine; UOP, urine output; ECMO, extracorporeal membrane oxygenation

a Miscellaneous predisposing conditions include crush injury, hematopoietic cell transplantation, IV antibiotics, hypoxic-ischemic encephalopathy, continuous kidney replacement therapy, malignancy, drowning, and metabolic Acidosis

Fig. 6.

Fig. 6

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The map illustrates the incidence of acute kidney injury-associated mortality among hospitalized children across various countries

Fig. 7.

Fig. 7

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The forest plot depicting the incidence of post-discharge mortality among hospitalized children with acute kidney injury

Discussion

This meta-analysis, encompassing 60 studies and 133,876 hospitalized children with AKI, reveals a substantial global burden of mortality. The pooled in-hospital mortality rate was 18.27% (95% CI: 14.89, 21.65) among studies with at least 100 AKI patients, increasing from 8.19% in stage 1 to 27.78% in stage 3. Subgroup analyses showed no significant differences across geographical regions, income levels, or AKI definition criteria. Meta-regression analyses found no significant associations between AKI-associated mortality and factors such as GDP, healthcare expenditure, or maternal mortality ratio. The pooled post-discharge mortality rate was 6.84% (95% CI: 5.86, 7.82) in a 1–9-year follow-up period. These findings provide crucial insights into the global impact of pediatric AKI mortality and set the stage for discussing potential interventions and policy implications.

To our knowledge, this meta-analysis represents the most comprehensive systematic evaluation of AKI-associated mortality in the pediatric population to date. Our literature review revealed two prior meta-analyses. Notably, Susantitaphong et al.‘s study [109], which searched the Medline database for 2004–2012, included 11 studies employing a KDIGO-equivalent definition of AKI and found a pooled all-cause mortality rate of 13.8% (95% CI, 8.8 to 21.0). However, that analysis lacked studies from low and lower-middle-income countries, limiting its global generalizability. Our study addresses these limitations, providing a more inclusive and globally representative analysis of pediatric AKI mortality.

The second meta-analysis by Meena et al. [1] searched Medline, Embase, and Web of Sciences from March 2012 to January 2022. Analyzing 60 studies using KDIGO criteria and excluding neonates, they found a pooled AKI-associated all-cause hospital mortality of 11% (95% CI: 9–13). Like our study, they restricted analysis to studies with over 100 patients. However, their analysis was limited to studies using KDIGO criteria and excluded neonate patients, potentially limiting its scope and generalizability.

Our systematic review and meta-analysis demonstrate several key methodological strengths that address limitations of previous studies. First, the study rigorously addresses potential confounding factors by exclusively including studies that demonstrated an independent association between AKI and mortality through multivariate analysis. To mitigate the small study effect, the analysis focused on studies with over 100 patients. The comprehensive approach to assessing different AKI criteria, coupled with subgroup analyses, ensured the inclusion of all relevant studies and facilitated valuable comparisons. Notably, the inclusion of neonates and the subsequent age-based subgroup analysis allowed for a nuanced comparison of mortality incidence between neonates and older children, filling an important gap in the literature.

Our analysis demonstrates a clear association between AKI severity and mortality risk. The mortality rates increased progressively from stage 1 AKI to stage 3 AKI, highlighting the critical importance of early intervention to prevent AKI progression. This observation aligns with previous studies that have shown a correlation between AKI severity and adverse outcomes in both adult and pediatric populations [1, 106, 109, 110]. However, our findings highlight the limited availability of data on the utilization of renal replacement therapy (RRT) for severe AKI in pediatric populations. For example, the ASPIRE study reported a mortality rate of 32.1% in children with severe dialysis-dependent AKI, primarily treated with peritoneal dialysis [65]. Unfortunately, such data remain sparse, leaving a significant gap in understanding the specific role of RRT modalities in pediatric AKI mortality.

Our study found neonatal AKI-associated mortality of 21.81% (16.84 to 20.75%), lower than the 30% (27 to 33%) reported in Meena et al.‘s meta-analysis of neonates [111]. Both rates exceed those for pediatric patients older than one month. However, our meta-regression couldn’t establish a statistically significant difference in mortality between neonates and older pediatric patients. The high mortality in neonates with AKI likely reflects their vulnerability to severe illnesses and complications [111].

Our subgroup analyses showed no significant differences in mortality rates across geographical regions or income levels, contrasting with previous reports suggesting worse outcomes in low and middle-income countries [1, 112]. This indicates that AKI-associated mortality in children is a global challenge transcending economic boundaries, emphasizing the need for universal strategies. However, caution is warranted when interpreting results from low-income countries, as reliable epidemiological data on childhood AKI is scarce in these regions [112], and the population samples may be subject to selection bias.

The criteria for defining AKI have evolved from RIFLE to pRIFLE, AKIN, KDIGO, and mKDIGO (neonates). The main differences between these criteria lie in their measurement methods (creatinine, estimated clearance, or GFR), time frames (48 h or 7 days), and use of absolute or relative changes. While these differences can affect the detection of mild AKI cases, the criteria generally align well in identifying more severe cases [61, 106, 113]. Our analysis of different AKI classification systems (KDIGO/mKDIGO vs. pRIFLE/RIFLE/nRIFLE) showed no significant difference in reported mortality rates, supporting the comparability of these widely used classification systems in pediatric populations.

The similar mortality rates observed between studies using only serum creatinine-based AKI definitions (18.19%), and those incorporating both urine output and serum creatinine criteria (17.31%) suggest that serum creatinine alone may be a sufficient marker for identifying high-risk AKI cases in children.

Furthermore, our findings of a 6.84% (95% CI: 5.86, 7.82) post-discharge mortality rate align with Knappett et al.‘s meta-analysis, which reported a 4.4% (95% CI: 3.5–5.4%) six-month post-discharge mortality risk in low and low-middle Sociodemographic index (SDI) countries [114]. These results underscore the importance of long-term follow-up for children who have experienced AKI during hospitalization.

Limitations

This study has several limitations that should be considered when interpreting the results. Firstly, despite comprehensive subgroup analyses and meta-regressions, significant variability persisted among the included studies. This heterogeneity likely reflects differences in study populations, clinical settings, AKI definitions, and healthcare systems across countries. Secondly, limited data on post-discharge mortality restricted our ability to perform subgroup analyses and meta-regressions for this outcome, hindering a deeper understanding of long-term effects. Thirdly, our funnel plot analysis revealed asymmetry around the axis, raising potential concerns about publication bias. However, evidence suggests that conventional funnel plots may not accurately assess publication bias in proportional meta-analyses, as asymmetry can occur even in the absence of true bias [115, 116].

Additionally, by including only studies that reported an independent association between AKI and mortality, our analysis may have been biased toward studies involving higher mortality rates and/or sicker AKI cases. Our intention with this selection criteria was to ensure robust findings by focusing on studies that controlled for confounding variables, strengthening the causal interpretation of AKI-associated mortality. However, we acknowledge that this approach might inflate pooled estimates. Furthermore, while our study incorporated data from multiple countries, some regions—particularly low- and low-middle-income countries—were underrepresented. This underrepresentation limits the global generalizability of our findings and is particularly concerning given that mortality rates in these regions are likely higher.

Lastly, the inclusion of studies that demonstrated a statistical association between AKI and mortality, while methodologically robust, may have introduced selection bias toward studies with higher mortality rates or severe AKI cases. This approach ensures a focus on AKI-specific mortality but may not fully capture the broader spectrum of AKI-associated mortality. Future studies should address this gap by including a wider range of studies, regardless of statistical association, to provide a more comprehensive understanding of AKI-related mortality. Additionally, the heterogeneity in AKI etiologies, which often depend on the child’s or neonate’s age, adds complexity to interpreting the results. Future studies should aim to address these gaps by including diverse populations and systematically reporting long-term outcomes and regional disparities.

Conclusion

This comprehensive systematic review and meta-analysis provides valuable insights into the global incidence of acute kidney injury (AKI)-associated mortality in hospitalized children. Our findings demonstrate that AKI is independently associated with a substantial mortality rate of 18.27% among hospitalized children, with higher mortality rates observed in more severe stages of AKI. This underscores the critical nature of AKI as a significant health concern in pediatric populations worldwide and the crucial need for early detection and intervention strategies. Future research should focus on developing and validating risk prediction models, implementing targeted prevention strategies, and exploring long-term outcomes in pediatric AKI survivors.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1 (5.8MB, docx)

Acknowledgements

Not applicable.

Author contributions

Study design and conceptualization: MY, MH, NA. Data gathering: HZ, AA, AA, AR, HT, SRD, NS, AD. Data analysis: HZ, MY. Interpretation of the results: HZ, AA, MY. Drafting the manuscript: HZ, AA. Revising, editing, and confirming the final version: All authors.

Funding

This research was funded by Tehran University of Medical Sciences (Grant number: 99-1-231-48274).

Data availability

The dataset generated and analyzed during the current study is available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Mostafa Hosseini, Email: mhossein110@yahoo.com.

Mahmoud Yousefifard, Email: yousefifard20@gmail.com.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1 (5.8MB, docx)

Data Availability Statement

The dataset generated and analyzed during the current study is available from the corresponding author upon reasonable request.

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