ArticleClinical kidney journal2023
Epidemiology of childhood acute kidney injury in England using e-alerts.
Article in Clinical kidney journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Incidence of acute kidney injury-associated mortality in hospitalized children: a systematic review and meta-analysis.BMC nephrology · 2025Pooled it
- Using health systems evidence to study and predict long-term outcomes of childhood acute kidney injury.Pediatric nephrology (Berlin, Germany) · 2026Article
- Identifying acute kidney injury in children: comparing electronic alerts with health record data.BMC nephrology · 2025Article
- Consistency of alerts generated by, and implementation of, the NHS England acute kidney injury detection algorithm in English laboratories.Journal of nephrology · 2024Article
- Acute Kidney Injury in Children: A Focus for the General Pediatrician.Children (Basel, Switzerland) · 2024Review
- Editorial on the Special Issue "Advances in Pediatric Acute Kidney Injury".Children (Basel, Switzerland) · 2024Article
- Predicting acute kidney injury with an artificial intelligence-driven model in a pediatric cardiac intensive care unit.Journal of anesthesia, analgesia and critical care · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Few studies describe the epidemiology of childhood acute kidney injury (AKI) nationally. Laboratories in England are required to issue electronic (e-)alerts for AKI based on serum creatinine changes. This study describes a national cohort of children who received an AKI alert and their clinical course. Methods: A cross-section of AKI episodes from 2017 are described. Hospital record linkage enabled description of AKI-associated hospitalizations including length of stay (LOS) and critical care requirement. Risk associations with critical care (hospitalized cohort) and 30-day mortality (total cohort) were examined using multivariable logistic regression. Results: In 2017, 7788 children (52% male, median age 4.4 years, interquartile range 0.9-11.5 years) experienced 8927 AKI episodes; 8% occurred during birth admissions. Of 5582 children with hospitalized AKI, 25% required critical care. In children experiencing an AKI episode unrelated to their birth admission, Asian ethnicity, young (<1 year) or old (16-<18 years) age (reference 1-<5 years), and high peak AKI stage had higher odds of critical care. LOS was higher with peak AKI stage, irrespective of critical care admission. Overall, 30-day mortality rate was 3% ( Conclusions: Risk associations for adverse AKI outcomes differed among children according to AKI type and whether hospitalization was related to birth. Understanding the factors driving AKI development and progression may help inform interventions to minimize morbidity.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.