دورية أكاديمية
أعرض في EDS

Intraoperative Renal Resistive Index as an Acute Kidney Injury Biomarker: Development and Validation of an Automated Analysis Algorithm.

التفاصيل البيبلوغرافية
العنوان: Intraoperative Renal Resistive Index as an Acute Kidney Injury Biomarker: Development and Validation of an Automated Analysis Algorithm.
المؤلفون: Andrew BY; Department of Anesthesiology, Duke University Medical Center, Durham, NC; Clinical Research Training Program, Duke University School of Medicine, Durham, NC., Andrew EY; Department of Electrical and Computer Engineering, School of Engineering and Applied Sciences, The George Washington University, Washington, DC., Cherry AD; Department of Anesthesiology, Duke University Medical Center, Durham, NC., Hauck JN; Department of Anesthesiology, Duke University Medical Center, Durham, NC., Nicoara A; Department of Anesthesiology, Duke University Medical Center, Durham, NC., Pieper CF; Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC., Stafford-Smith M; Department of Anesthesiology, Duke University Medical Center, Durham, NC. Electronic address: mark.staffordsmit@dm.duke.edu.
المصدر: Journal of cardiothoracic and vascular anesthesia [J Cardiothorac Vasc Anesth] 2018 Oct; Vol. 32 (5), pp. 2203-2209. Date of Electronic Publication: 2018 Apr 04.
نوع المنشور: Journal Article; Validation Study
اللغة: English
بيانات الدورية: Publisher: W.B. Saunders Country of Publication: United States NLM ID: 9110208 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1532-8422 (Electronic) Linking ISSN: 10530770 NLM ISO Abbreviation: J Cardiothorac Vasc Anesth Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Philadelphia, PA : W.B. Saunders, c1991-
مواضيع طبية MeSH: Acute Kidney Injury/*physiopathology , Cardiac Surgical Procedures/*adverse effects , Monitoring, Intraoperative/*methods , Postoperative Complications/*diagnosis , Renal Circulation/*physiology, Acute Kidney Injury/diagnosis ; Acute Kidney Injury/etiology ; Aged ; Algorithms ; Biomarkers/blood ; Creatinine/blood ; Echocardiography, Transesophageal/methods ; Female ; Follow-Up Studies ; Humans ; Kidney/diagnostic imaging ; Male ; Middle Aged ; Postoperative Complications/physiopathology ; Predictive Value of Tests ; Reproducibility of Results ; Retrospective Studies ; Risk Factors
مستخلص: Objective: Intraoperative Doppler-determined renal resistive index (RRI) is a promising early acute kidney injury (AKI) biomarker. As RRI continues to be studied, its clinical usefulness and robustness in research settings will be linked to the ease, efficiency, and precision with which it can be interpreted. Therefore, the authors assessed the usefulness of computer vision technology as an approach to developing an automated RRI-estimating algorithm with equivalent reliability and reproducibility to human experts.
Design: Retrospective.
Setting: Single-center, university hospital.
Participants: Adult cardiac surgery patients from 7/1/2013 to 7/10/2014 with intraoperative transesophageal echocardiography-determined renal blood flow measurements.
Interventions: None.
Measurements and Main Results: Renal Doppler waveforms were obtained retrospectively and assessed by blinded human expert raters. Images (430) were divided evenly into development and validation cohorts. An algorithm for automated RRI analysis was built using computer vision techniques and tuned for alignment with experts using bootstrap resampling in the development cohort. This algorithm then was applied to the validation cohort for an unbiased assessment of agreement with human experts. Waveform analysis time per image averaged 0.144 seconds. Agreement was excellent by intraclass correlation coefficient (0.939; 95% confidence interval [CI] 0.921 to 0.953) and in Bland-Altman analysis (mean difference [human-algorithm] -0.0015; 95% CI -0.0054 to 0.0024), without evidence of systematic bias.
Conclusion: The authors confirmed the value of computer vision technology to develop an algorithm for RRI estimation from automatically processed intraoperative renal Doppler waveforms. This simple-to-use and efficient tool further adds to the clinical and research value of RRI, already the "earliest" among several early AKI biomarkers being assessed.
(Copyright © 2018 Elsevier Inc. All rights reserved.)
References: J Cardiothorac Vasc Anesth. 2013 Oct;27(5):890-6. (PMID: 23731713)
J Ultrasound Med. 2000 May;19(5):303-14. (PMID: 10811403)
Eur J Heart Fail. 2014 Feb;16(2):210-6. (PMID: 24464953)
Intensive Care Med Exp. 2014 Dec;2(1):26. (PMID: 26266923)
Am J Cardiol. 2013 Jul 15;112(2):156-61. (PMID: 23587278)
Eur J Anaesthesiol. 2015 Jan;32(1):37-43. (PMID: 25014511)
Int J Cardiovasc Imaging. 2017 Aug;33(8):1135-1148. (PMID: 28220275)
J Am Soc Echocardiogr. 2012 Jan;25(1):56-65. (PMID: 22105057)
Ann Thorac Surg. 2016 Nov;102(5):1482-1489. (PMID: 27319985)
IEEE Trans Med Imaging. 2014 May;33(5):1071-82. (PMID: 24770912)
Transplantation. 2010 Jan 15;89(1):40-6. (PMID: 20061917)
Psychol Bull. 1979 Mar;86(2):420-8. (PMID: 18839484)
Ann Thorac Surg. 2017 Nov;104(5):1583-1589. (PMID: 28619541)
Anesth Analg. 2013 Mar;116(3):549-54. (PMID: 23400979)
J Nephrol. 2017 Apr;30(2):243-253. (PMID: 26995003)
Cardiorenal Med. 2016 Nov;7(1):42-49. (PMID: 27994601)
Br J Anaesth. 2011 Dec;107(6):891-8. (PMID: 21940396)
Ultrasound Med Biol. 2010 Sep;36(9):1513-24. (PMID: 20800178)
Nephrol Dial Transplant. 2011 Dec;26(12):3908-13. (PMID: 21421591)
Hypertension. 2015 Aug;66(2):382-8. (PMID: 26077569)
Ann Thorac Surg. 2018 Jul;106(1):107-114. (PMID: 29427619)
Ultrasound Obstet Gynecol. 2017 Jul 17;:null. (PMID: 28715153)
معلومات مُعتمدة: T32 GM008600 United States GM NIGMS NIH HHS; TL1 TR001116 United States TR NCATS NIH HHS
فهرسة مساهمة: Keywords: Doppler echocardiography; acute kidney injury; algorithms; cardiac surgery; computer vision; image processing
المشرفين على المادة: 0 (Biomarkers)
AYI8EX34EU (Creatinine)
تواريخ الأحداث: Date Created: 20180514 Date Completed: 20190123 Latest Revision: 20191210
رمز التحديث: 20221213
مُعرف محوري في PubMed: PMC6153038
DOI: 10.1053/j.jvca.2018.04.014
PMID: 29753670
قاعدة البيانات: MEDLINE
الوصف
تدمد:1532-8422
DOI:10.1053/j.jvca.2018.04.014