Acute kidney injury in different time windows: a retrospective study of hospitalized elderly patients

Abstract Background To compare the differences between the Kidney Disease Improving Global Outcomes (KDIGO) criteria of the 48-hour window (early acute kidney injury [AKI], 3–5 day window [middle AKI], and 6–7 day window [late AKI]) in the diagnosis of AKI, as well as the relationship between the diagnosis time windows and 90-day mortality. Methods We conducted a retrospective cohort study. All elderly patients admitted to the Geriatric Department of the Chinese PLA General Hospital between 2007 and 2018 were evaluated for AKI during their hospital stay. Patients with AKI were divided into early, middle, and late AKI groups according to the time of diagnosis. Statistical analyses were performed using SPSS 21.0 statistical software. Continuous parametric variables are expressed as the means ± standard deviations (SDs), and continuous nonparametric variables are presented as the medians with interquartile ranges (25th and 75th percentiles). Categorical variables are presented as numbers (n) or percentages (%). Group comparisons were conducted using one-way analysis of variance or the Kruskal-Wallis H test for continuous variables and Pearson’s chi-square or Fisher’s exact test for categorical variables. Logistic regression analyses and a forward stepwise selection method were used to identify risk factors associated with AKI diagnosis time windows and 90-day mortality. Results During the follow-up period, 1847 patients were enrolled. Overall, 22.4% of the patients (413/1847) developed early AKI, 7.3% (134/1847) developed middle AKI, and 10.7% (197/1847) developed late AKI. Risk factors for early AKI included age, hypoalbuminemia, low prealbumin level, and the need for mechanical ventilation; middle AKI was significantly associated with age, low prealbumin, low hemoglobin, and the need for mechanical ventilation, whereas late AKI was closely associated with age, low baseline estimated glomerular filtration rate, low prealbumin, and low hemoglobin. In the multivariable-adjusted analysis, AKI time windows (early AKI, odds ratio [OR]: 6.069; P < 0.001; middle AKI, OR: 5.000; P < 0.001) and late AKI (OR: 2.847; P < 0.001) were more strongly associated with higher 90-day mortality than non-AKI. Conclusion Clinical differences and risk factors for AKI in elderly patients depend on the definition used. A better understanding of how AKI develops during different diagnostic windows may lead to improved outcomes.

Authors

Institutions

Publication Details

Journal
Emergency and Critical Care Medicine
Published
2024-10-18
DOI
https://doi.org/10.1097/ec9.0000000000000128
Citations
2
Primary Topic
Acute Kidney Injury Research
Type
article
Field-Weighted Citation Impact
0.68
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Acute kidney injury in different time windows: a retrospective study of hospitalized elderly patients

Guanggang Li, Feihu Zhou, Dawei Li, Yan Chen et al.
2 citations
Emergency and Critical Care Medicine
Acute Kidney Injury Research
0.68
article

Acute kidney injury in different time windows: a retrospective study of hospitalized elderly patients

Guanggang Li, Feihu Zhou, Dawei Li, Yan Chen, Qinglin Li
article en
2 citations

Abstract

Abstract Background To compare the differences between the Kidney Disease Improving Global Outcomes (KDIGO) criteria of the 48-hour window (early acute kidney injury [AKI], 3–5 day window [middle AKI], and 6–7 day window [late AKI]) in the diagnosis of AKI, as well as the relationship between the diagnosis time windows and 90-day mortality. Methods We conducted a retrospective cohort study. All elderly patients admitted to the Geriatric Department of the Chinese PLA General Hospital between 2007 and 2018 were evaluated for AKI during their hospital stay. Patients with AKI were divided into early, middle, and late AKI groups according to the time of diagnosis. Statistical analyses were performed using SPSS 21.0 statistical software. Continuous parametric variables are expressed as the means ± standard deviations (SDs), and continuous nonparametric variables are presented as the medians with interquartile ranges (25th and 75th percentiles). Categorical variables are presented as numbers (n) or percentages (%). Group comparisons were conducted using one-way analysis of variance or the Kruskal-Wallis H test for continuous variables and Pearson’s chi-square or Fisher’s exact test for categorical variables. Logistic regression analyses and a forward stepwise selection method were used to identify risk factors associated with AKI diagnosis time windows and 90-day mortality. Results During the follow-up period, 1847 patients were enrolled. Overall, 22.4% of the patients (413/1847) developed early AKI, 7.3% (134/1847) developed middle AKI, and 10.7% (197/1847) developed late AKI. Risk factors for early AKI included age, hypoalbuminemia, low prealbumin level, and the need for mechanical ventilation; middle AKI was significantly associated with age, low prealbumin, low hemoglobin, and the need for mechanical ventilation, whereas late AKI was closely associated with age, low baseline estimated glomerular filtration rate, low prealbumin, and low hemoglobin. In the multivariable-adjusted analysis, AKI time windows (early AKI, odds ratio [OR]: 6.069; P < 0.001; middle AKI, OR: 5.000; P < 0.001) and late AKI (OR: 2.847; P < 0.001) were more strongly associated with higher 90-day mortality than non-AKI. Conclusion Clinical differences and risk factors for AKI in elderly patients depend on the definition used. A better understanding of how AKI develops during different diagnostic windows may lead to improved outcomes.

Emergency and Critical Care MedicineVol. 5(1)
State Administration of Traditional Chinese Medicine of the People's Republic of China (CN), Chinese PLA General Hospital (CN)
Openalex Percentile: Top 26%
Acute Kidney Injury Research
0.68
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.