Biomarkers to Predict Multiorgan Distress Syndrome and Acute Kidney Injury in Critically Ill Surgical Patients

Author:

Shin In Sik1ORCID,Kim Da Kyung2ORCID,An Sanghyun34ORCID,Gong Sung Chan5ORCID,Kim Moo Hyun1,Rahman Md Habibur6,Kim Cheol-Su6ORCID,Sohn Joon Hyeong7,Kim Kwangmin8ORCID,Ryu Hoon5

Affiliation:

1. Division of Acute Care Surgery, Department of Surgery, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea

2. Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea

3. Division of Colorectal Surgery, Department of Surgery, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea

4. Center of Evidence Based Medicine, Institute of Convergence Science, Yonsei University, Seoul 03722, Republic of Korea

5. Division of Esophago-Gastrointestinal Surgery, Department of Surgery, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea

6. Department of Convergence Medicine, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea

7. Central Research Laboratory, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea

8. Department of Surgery, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of Korea

Abstract

Background and Objectives: Critically ill surgical patients are susceptible to various postoperative complications, including acute kidney injury (AKI) and multiorgan distress syndrome (MODS). These complications intensify patient suffering and significantly increase morbidity and mortality rates. This study aimed to identify the biomarkers for predicting AKI and MODS in critically ill surgical patients. Materials and Methods: We prospectively enrolled critically ill surgical patients admitted to the intensive care unit via the emergency department between July 2022 and July 2023. A total of 83 patients were recruited, and their data were used to analyze MODS. Three patients who showed decreased creatinine clearance at the initial presentation were excluded from the analysis for AKI. Patient characteristics and laboratory parameters including white blood cell (WBC) count, neutrophil count, delta neutrophil index, urine and serum β2-microglobulin, and urine serum mitochondrial DNA copy number (mtDNAcn) were analyzed to determine the reliable biomarker to predict AKI and MODS. Results: The following parameters were independently correlated with MODS: systolic blood pressure (SBP), initial neutrophil count, and platelet count, according to a logistic regression model. The optimal cut-off values for SBP, initial neutrophil count, and platelet count were 113 mmHg (sensitivity 66.7%; specificity 73.9%), 8.65 (X3) (109/L) (sensitivity 72.2%; specificity 64.6%), and 195.0 (X3) (109/L) (sensitivity 66.7%; specificity 81.5%), respectively. According to the logistic regression model, diastolic blood pressure (DBP) and initial urine mtDNAcn were independently correlated with AKI. The optimal cut-off value for DBP and initial urine mtDNAcn were 68.5 mmHg (sensitivity 61.1%; specificity 79.5%) and 1225.6 copies/μL (sensitivity 55.6%; specificity 95.5%), respectively. Conclusions: SBP, initial neutrophil count, and platelet count were independent predictors of MODS in critically ill patients undergoing surgery. DBP and initial urine mtDNAcn levels were independent predictors of AKI in critically ill surgical patients. Large-scale multicenter prospective studies are needed to confirm our results.

Funder

Ministry of Education

Publisher

MDPI AG

Subject

General Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3