Evidence map›Paper›PMID 40613009›Full record

ArticleKidney medicine2025

Temporal Trends in Acute Kidney Injury in Hospitalizations From 2009-2018 in Alberta: A Retrospective Population-Based Cohort Study.

Anita Dahiya, Natasha Wiebe, Tyrone G Harrison, Matthew T James, Neesh Pannu, Alberta Kidney Disease Network

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Article in Kidney medicine, 2025. 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Anita DahiyaDepartment of Medicine, University of Alberta, Edmonton, Alberta, Canada.
Natasha WiebeDepartment of Medicine, University of Alberta, Edmonton, Alberta, Canada.
Tyrone G HarrisonDepartment of Medicine, University of Calgary, Calgary, Alberta, Canada.
Matthew T JamesDepartment of Medicine, University of Calgary, Calgary, Alberta, Canada.
Neesh PannuDepartment of Medicine, University of Alberta, Edmonton, Alberta, Canada.
Alberta Kidney Disease Network

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rationale & Objective: Studies have reported an increase in acute kidney injury (AKI) incidence; however, they are limited by administrative codes. We aimed to identify trends in AKI incidence, severity, and mortality using Kidney Disease: Improving Global Outcomes (KDIGO)-based definitions. Study Design: This is a retrospective, population-based cohort study. Setting & Population: Hospitalized adult patients in Alberta, Canada from 2009-2018. Exposures: AKI episodes were identified using validated KDIGO definitions. Outcomes: We assessed in-hospital and 90-day all-cause mortality. Analytical Approach: Generalized linear models with a Gaussian family were used to determine absolute rates of AKI and mortality. Rates of AKI and mortality were adjusted for patient demographics and comorbid conditions. Results: There were 339,986 hospitalizations with an episode of AKI (12.7%, 2,668,954 hospitalizations) with a median age of 70 years (56, 82) and 152,115 (44.7%) women. AKI rates increased by an unadjusted relative increase of 5.5% (95% confidence interval [CI], 4.2-6.9). When fully adjusted, a relative decrease of 11.2% (95% CI, 9.2-13.2) was seen in rates of AKI. Stage 1 AKI was most common (unadjusted mean rate, 659 per 100,000 person-years [95% CI, 655-662]). In-hospital mortality decreased across all stages of AKI with the greatest decrease noted in stage 3 AKI requiring kidney replacement therapy (unadjusted relative decrease 29.9% [95% CI, 20-38.6]). Similar trends were identified in 90-day mortality. Limitations: The primary strength of this paper is that it involves a large cohort of patients from a diverse population. The use of KDIGO definition of AKI is limited by the reliance on serum creatinine values. Conclusions: Although rates of AKI appear to be increasing, this seems to be largely driven by patient comorbid condition with the highest rates seen in stage 1 AKI. Furthermore, there was an overall increase in rates of AKI in patients aged younger than 60 and a decrease in the most elderly of patients in both the crude and adjusted data, suggesting potential changes in practice patterns and patient characteristics. Despite this increase, there was an overall decrease in mortality, especially in severe forms of AKI.

Indexed as

Acute kidney injurycohort studymortalitytemporal trends

Identifiers

PMID40613009
PMCPMC12221727

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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.