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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Gene signature for the prediction of the trajectories of sepsis-induced acute kidney injury
Zhongheng Zhang, Lin Chen, Huiheng Liu, et al.
Critical Care (2022) Vol. 26, Iss. 1
Open Access | Times Cited: 11

Showing 11 citing articles:

Current and novel biomarkers in cardiogenic shock
Victor Galusko, Florian A. Wenzl, Christophe Vandenbriele, et al.
European Journal of Heart Failure (2025)
Open Access | Times Cited: 2
Identifying septic shock subgroups to tailor fluid strategies through multi-omics integration
Zhongheng Zhang, Lin Chen, Bin Sun, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 6
Associations between life’s essential 8 and metabolic health among us adults: insights of NHANES from 2005 to 2018
Tongyue Yang, Jiayi Yi, Mingwei Shao, et al.
Acta Diabetologica (2024) Vol. 61, Iss. 8, pp. 963-974
Closed Access | Times Cited: 6
Exploring disease axes as an alternative to distinct clusters for characterizing sepsis heterogeneity
Zhongheng Zhang, Lin Chen, Xiaoli Liu, et al.
Intensive Care Medicine (2023) Vol. 49, Iss. 11, pp. 1349-1359
Closed Access | Times Cited: 12
Predictive models of sepsis-associated acute kidney injury based on machine learning: a scoping review
Jie Li, Manli Zhu, Yan Li
Renal Failure (2024) Vol. 46, Iss. 2
Open Access | Times Cited: 4
A Study on the Factors Influencing Mortality Risk in Sepsis-Induced Acute Kidney Injury Based on Analysis of the MIMIC Database
C.H. Ye, Chunyan Zhu, S. Hu, et al.
Research Square (Research Square) (2025)
Closed Access
Identification of Key Genes and Potential Therapeutic Targets in Sepsis-Associated Acute Kidney Injury Using Transformer and Machine Learning Approaches
Zhenya Zhai, Jianhao Peng, Wenjun Zhong, et al.
Bioengineering (2025) Vol. 12, Iss. 5, pp. 536-536
Open Access
Personalizing Care for Critically Ill Adults Using Omics: A Concise Review of Potential Clinical Applications
Kay Choong See
Cells (2023) Vol. 12, Iss. 4, pp. 541-541
Open Access | Times Cited: 6
Development of a nomogram model for the early prediction of sepsis-associated acute kidney injury in critically ill patients
Milin Peng, Fuxing Deng, Desheng Qi
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 3
YTHDF1 mitigates acute kidney injury via safeguarding m6A-methylated mRNAs in stress granules of renal tubules
Wenwen Yang, Mingchao Zhang, Jiacheng Li, et al.
Redox Biology (2023) Vol. 67, pp. 102921-102921
Open Access | Times Cited: 3
SOD1 is a novel prognostic biomarker of acute kidney injury following cardiothoracic surgery
Joseph H. Holthoff, Yanping Izak Harville, Christian Herzog, et al.
BMC Nephrology (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 2
Chest computed tomography for patients with sepsis in the emergency intensive care unit
Senjun Jin, Wenwei Cai, Qiang Shen, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access
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