Evidence map›Paper›PMID 42022250›Full record

ArticleKidney medicine2026

Shifts in Acute Kidney Injury Trends Post-Alert System Implementation: A Retrospective Observational Cohort Study.

Jinyeong Yi, Jiwon Ryu, Tran Tuan Tu, Seokwoo Park, Jong Cheol Jeong, Ho Jun Chin, Keonhwa Kim, Sejoong Kim

Abstract read
In one paragraph

Article in Kidney medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

8 authors.

Jinyeong YiCenter for Artificial Intelligence in Healthcare, Seoul National University Bundang Hospital, Republic of Korea.
Jiwon RyuDepartment of Internal Medicine, Seoul National University College of Medicine, Republic of Korea.
Tran Tuan TuDepartment of Internal Medicine, Thai Nguyen University of Medicine and Pharmacy, Thai Nguyen, Vietnam.
Seokwoo ParkDepartment of Internal Medicine, Seoul National University Bundang Hospital, Republic of Korea.
Jong Cheol JeongDepartment of Internal Medicine, Seoul National University College of Medicine, Republic of Korea.
Ho Jun ChinDepartment of Internal Medicine, Seoul National University College of Medicine, Republic of Korea.
Keonhwa KimDepartment of Internal Medicine, Seoul National University Bundang Hospital, Republic of Korea.
Sejoong KimCenter for Artificial Intelligence in Healthcare, Seoul National University Bundang Hospital, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rationale & Objective: Acute kidney injury (AKI), a complex syndrome involving multiple organ systems, requires timely intervention to prevent adverse outcomes. Despite the promise of AKI alert systems in improving early detection and management, their long-term effectiveness remains unevaluated. This study aimed to investigate the sustained impact of an AKI alert system over a decade of implementation. Study Design: Retrospective observational cohort study. Setting & Participants: Conducted at a Korean tertiary hospital, analyzing 13,301 adult patients with AKI, from 246,650 admissions (2013-2023). Exposure: Introduction of an automated AKI alert system (implemented June 2014). Outcomes: Primary outcomes included 14-day AKI recovery, stage progression, dialysis onset, and mortality. Process outcomes comprised early nephrology consultation, overlooked AKI cases, and discontinuation of nephrotoxic medications. Long-term outcome was assessed as ≥35% estimated glomerular filtration rate (eGFR) decline within 3 years. Analytical Approach: Outcomes were compared across pre-alert (January 2013-May 2014), alert implementation (June 2014-December 2019), and pandemic (January 2020-December 2023) phases, using adjusted multivariable logistic analyses calculating unadjusted and covariate-adjusted odds ratios (ORs). Interrupted time series analysis evaluated temporal trends. Results: AKI recovery rates increased substantially in both alert implementation and pandemic phases (adjusted OR 2.40 [95% confidence interval (CI) 2.16-2.66] and 2.19 [1.94-2.47], respectively). Early nephrology consultation improved significantly (adjusted OR 3.33 [2.81-3.95] and 2.65 [2.20-3.19]), and overlooked AKI cases decreased (adjusted OR 0.49 [0.43-0.55] and 0.43 [0.36-0.51]). Long-term renal outcomes showed lower risk of significant eGFR decline during the implementation phase (adjusted OR 0.86 [0.76-0.99]). Interrupted time series analysis showed immediate improvements in recovery rates, early consultation rates, and overlooked AKI cases following alert implementation. Limitations: Single-center, retrospective design limits generalizability. Patient characteristic changes may confound results. Conclusions: The AKI alert system achieved sustained improvements in AKI recovery, early nephrology consultation, and AKI monitoring, over a decade, demonstrating long-term effectiveness despite evolving patient populations and health care environments.

Indexed as

Acute kidney injury (AKI)Alert Systemelectronic health records (EHRs)nephrotoxic medicationstime series analysis

Identifiers

PMID42022250
PMCPMC13098425

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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.