Literature DB >> 29693474

Acute Kidney Injury in Critically Ill Patients with Sepsis: Clinical Characteristics and Outcomes.

De-Yuan Zhi1, Jin Lin1, Hai-Zhou Zhuang1, Lei Dong1, Xiao-Jun Ji1, Dong-Cheng Guo1, Xiao-Wei Yang1, Shuai Liu1, Zu Yue2, Shu-Jing Yu3, Mei-Li Duan1.   

Abstract

Objective: The objectives of this study were to examine the clinical profile of critically ill patients with septic acute kidney injury (AKI) and to investigate clinical characteristics associated with the outcome of patients.
Methods: Data from 582 critically ill patients were collected and retrospectively reviewed. Patients were divided into two groups: without AKI development and with AKI development. Baseline characteristics, laboratory, and other clinical data were compared between these two groups, and correlations between the characteristics and AKI development were examined. Patients with AKI development were further divided into two groups according to the survival outcome, and variables associated with the outcome were determined.
Results: AKI was developed in 54.12% (n = 315) of patients, and these patients had blood pressure, SOFA score, APACHE II score, GCS, and various blood chemistry and hematology characteristics significantly different from the patients without AKI. Demographic characteristics (e.g. age and weight) were comparable between the two groups of patients. Among the 315 patients with AKI, 136 of them died during the study period. Multivariate logistic regression analysis revealed that the outcome of patients was associated with lung infection, coagulation system dysfunction, staphylococcus aureus infection, and use of various treatments (epinephrine, norepinephrine, and the use of mechanical ventilation) after AKI development.
Conclusion: AKI occurred in approximately half of the critically ill patients admitted to ICU. The site and type of infections, as well as the use of vasopressor agents, were associated with the outcome.

Entities:  

Keywords:  acute kidney injury; clinical characteristics; critically ill; mortality; risk factors; sepsis

Mesh:

Substances:

Year:  2018        PMID: 29693474     DOI: 10.1080/08941939.2018.1453891

Source DB:  PubMed          Journal:  J Invest Surg        ISSN: 0894-1939            Impact factor:   2.533


  7 in total

1.  Machine learning for the prediction of acute kidney injury in patients with sepsis.

Authors:  Suru Yue; Shasha Li; Xueying Huang; Jie Liu; Xuefei Hou; Yumei Zhao; Dongdong Niu; Yufeng Wang; Wenkai Tan; Jiayuan Wu
Journal:  J Transl Med       Date:  2022-05-13       Impact factor: 8.440

2.  A novel risk-predicted nomogram for sepsis associated-acute kidney injury among critically ill patients.

Authors:  Shanglin Yang; Tingting Su; Lina Huang; Lu-Huai Feng; Tianbao Liao
Journal:  BMC Nephrol       Date:  2021-05-10       Impact factor: 2.388

3.  Construction and Validation of a Risk Prediction Model for Acute Kidney Injury in Patients Suffering from Septic Shock.

Authors:  Suru Yue; Shasha Li; Xueying Huang; Jie Liu; Xuefei Hou; Yufeng Wang; Jiayuan Wu
Journal:  Dis Markers       Date:  2022-01-06       Impact factor: 3.434

4.  A Predictive Model Based on Inflammatory and Coagulation Indicators for Sepsis-Induced Acute Kidney Injury.

Authors:  Qi Xin; Tonghui Xie; Rui Chen; Xing Zhang; Yingmu Tong; Hai Wang; Shufeng Wang; Chang Liu; Jingyao Zhang
Journal:  J Inflamm Res       Date:  2022-08-11

5.  Rates, predictors, and mortality of sepsis-associated acute kidney injury: a systematic review and meta-analysis.

Authors:  Jiefeng Liu; Hebin Xie; Ziwei Ye; Fen Li; Lesan Wang
Journal:  BMC Nephrol       Date:  2020-07-31       Impact factor: 2.388

6.  The Value of Thromboelastography in the Diagnosis of Sepsis-Induced Coagulopathy.

Authors:  Cuizhu Luo; Hongbin Hu; Jian Gong; Yun Zhou; Zhongqing Chen; Shumin Cai
Journal:  Clin Appl Thromb Hemost       Date:  2020 Jan-Dec       Impact factor: 2.389

7.  Effect of clinical decision support systems on clinical outcome for acute kidney injury: a systematic review and meta-analysis.

Authors:  Youlu Zhao; Xizi Zheng; Jinwei Wang; Damin Xu; Shuangling Li; Jicheng Lv; Li Yang
Journal:  BMC Nephrol       Date:  2021-08-04       Impact factor: 2.388

  7 in total

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