Evidence map›Paper›PMID 40355901›Full record

SynthesisCritical care (London, England)2025

The influence of electronic AKI alert on prognosis of adult hospitalized patients: a systematic review and meta-analysis.

Han Wang, Lingling Deng, Ting Li, Kang Liu, Huijuan Mao, Buyun Wu

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in Critical care (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Han WangDepartment of Nephrology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China.
Lingling DengDepartment of Nephrology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China.
Ting LiDepartment of Nephrology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China.
Kang LiuDepartment of Nephrology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China.
Huijuan MaoDepartment of Nephrology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China. huijuanmao@126.com.ORCID http://orcid.org/0000-0001-7410-1486
Buyun WuDepartment of Nephrology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China. wubuyun@njmu.edu.cn.ORCID http://orcid.org/0000-0002-4874-9171

Funding

General Project of the National Natural Science Foundation of China 82151320Jiangsu Provincial Medical Key Discipline (Laboratory) Cultivation Unit JSDW202206Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions (CN) 81970639
6 · The paper itself

Abstract

backgroundAcute kidney injury (AKI) is a critical yet frequently under diagnosed condition in hospitalized patients, impacting morbidity and mortality. Electronic alerts for AKI aimed to assist physicians in early diagnosis and intervention, though evidence for their effectiveness is inconsistent. MATERIALS AND

methodsA systematic search was conducted in PubMed, the Cochrane Central Register of Controlled Trials, Cochrane Library, and Web of Science from inception to November 2024. Eligible studies included randomized controlled trials (RCTs), before-and-after analyses, and stepped-wedge designs involving hospitalized patients. The primary outcomes were mortality and renal replacement therapy (RRT) rates, Secondary outcomes included hospital length of stay (LoS), AKI progression and recovery. Care-centered outcomes encompassed nephrologist consultation, nephrotoxic medication discontinuation and medication review. Subgroup analysis examined the impact of response intensity, hospital type and geographic region on these outcomes.

resultsTwenty-two studies involving 170,696 participants were included: 8 RCTs (n = 21,710) and 14 non-RCTs or observational studies (n = 148,986). RCTs showed no effect on mortality (RR 1.02; 95% CI 0.97-1.07) or LoS (mean difference 0.04; 95% CI - 0.13 to 0.22) but a significant increase in RRT use (RR 1.13; 95% CI 1.02-1.26) with AKI alert systems. Non-RCTs, however, reported reduced mortality (RR 0.92; 95% CI 0.88-0.96), less AKI progression (RR 0.85; 95% CI 0.77-0.94), enhanced kidney recovery (RR 1.65; 95% CI 1.56-1.75), increased nephrotoxic drug discontinuation (RR 1.20; 95% CI 1.13-1.28), and higher drug review rates (RR 1.19; 95% CI 1.17-1.21), with no impact on RRT use (RR 1.08; 95% CI 0.87-1.36). Subgroup analysis revealed an increased in-hospital mortality in low response intensity (RR 1.15; 95% CI 1.00-1.32), reduced mortality in moderate response intensity (RR 0.93; 95% CI 0.89-0.97), and unclear effects in high response intensity (RR 0.88; 95% CI 0.70-1.09). AKI alert was also favored in teaching hospitals and in several regions (Europe, North America and South America).

conclusionThe efficacy of AKI alerts remains inconclusive. Current evidence do not support or refute their effectiveness. Variability in response intensity, hospital type and geographic region may help explaining discrepancies, underscoring the need for further research to optimize AKI alert systems with more effective action in clinical practice.

Indexed as

Acute Kidney InjuryAdultHospitalizationHumansPrognosisRenal Replacement TherapyAcute kidney injuryAlert response intensityCare bundleElectronic alert

Identifiers

PMID40355901
PMCPMC12070640

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.