Stratified mortality prediction of patients with acute kidney injury in critical care

Zhenxing Xu; Yuan Luo; Prakash Adekkanattu; Jessica S. Ancker; Guoqian Jiang; Richard C. Kiefer; Jennifer A. Pacheco; Luke V. Rasmussen; Jyotishman Pathak; Fei Wang

doi:10.3233/SHTI190264

Stratified mortality prediction of patients with acute kidney injury in critical care

Zhenxing Xu, Yuan Luo, Prakash Adekkanattu, Jessica S. Ancker, Guoqian Jiang, Richard C. Kiefer, Jennifer A. Pacheco, Luke V. Rasmussen, Jyotishman Pathak, Fei Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

Acute Kidney Injury (AKI) is the most common cause of organ dysfunction in critically ill adults and prior studies have shown AKI is associated with a significant increase of the mortality risk. Early prediction of the mortality risk for AKI patients can help clinical decision makers better understand the patient condition in time and take appropriate actions. However, AKI is a heterogeneous disease and its cause is complex, which makes such predictions a challenging task. In this paper, we investigate machine learning models for predicting the mortality risk of AKI patients who are stratified according to their AKI stages. With this setup we demonstrate the stratified mortality prediction performance of patients with AKI is better than the results obtained on the mixed population.

Original language	English (US)
Title of host publication	MEDINFO 2019
Subtitle of host publication	Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics
Editors	Brigitte Seroussi, Lucila Ohno-Machado, Lucila Ohno-Machado, Brigitte Seroussi
Publisher	IOS Press
Pages	462-466
Number of pages	5
ISBN (Electronic)	9781643680026
DOIs	https://doi.org/10.3233/SHTI190264
State	Published - Aug 21 2019
Event	17th World Congress on Medical and Health Informatics, MEDINFO 2019 - Lyon, France Duration: Aug 25 2019 → Aug 30 2019

Publication series

Name	Studies in Health Technology and Informatics
Volume	264
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Conference

Conference	17th World Congress on Medical and Health Informatics, MEDINFO 2019
Country/Territory	France
City	Lyon
Period	8/25/19 → 8/30/19

Keywords

Acute Kidney Injury
Critical Care
Forecasting

ASJC Scopus subject areas

Biomedical Engineering
Health Informatics
Health Information Management

Access to Document

10.3233/SHTI190264

Cite this

Xu, Z., Luo, Y., Adekkanattu, P., Ancker, J. S., Jiang, G., Kiefer, R. C., Pacheco, J. A., Rasmussen, L. V., Pathak, J., & Wang, F. (2019). Stratified mortality prediction of patients with acute kidney injury in critical care. In B. Seroussi, L. Ohno-Machado, L. Ohno-Machado, & B. Seroussi (Eds.), MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics (pp. 462-466). (Studies in Health Technology and Informatics; Vol. 264). IOS Press. https://doi.org/10.3233/SHTI190264

Stratified mortality prediction of patients with acute kidney injury in critical care. / Xu, Zhenxing; Luo, Yuan; Adekkanattu, Prakash et al.
MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. ed. / Brigitte Seroussi; Lucila Ohno-Machado; Lucila Ohno-Machado; Brigitte Seroussi. IOS Press, 2019. p. 462-466 (Studies in Health Technology and Informatics; Vol. 264).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Xu, Z, Luo, Y, Adekkanattu, P, Ancker, JS, Jiang, G, Kiefer, RC, Pacheco, JA, Rasmussen, LV, Pathak, J & Wang, F 2019, Stratified mortality prediction of patients with acute kidney injury in critical care. in B Seroussi, L Ohno-Machado, L Ohno-Machado & B Seroussi (eds), MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. Studies in Health Technology and Informatics, vol. 264, IOS Press, pp. 462-466, 17th World Congress on Medical and Health Informatics, MEDINFO 2019, Lyon, France, 8/25/19. https://doi.org/10.3233/SHTI190264

Xu Z, Luo Y, Adekkanattu P, Ancker JS, Jiang G, Kiefer RC et al. Stratified mortality prediction of patients with acute kidney injury in critical care. In Seroussi B, Ohno-Machado L, Ohno-Machado L, Seroussi B, editors, MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. IOS Press. 2019. p. 462-466. (Studies in Health Technology and Informatics). doi: 10.3233/SHTI190264

Xu, Zhenxing ; Luo, Yuan ; Adekkanattu, Prakash et al. / Stratified mortality prediction of patients with acute kidney injury in critical care. MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. editor / Brigitte Seroussi ; Lucila Ohno-Machado ; Lucila Ohno-Machado ; Brigitte Seroussi. IOS Press, 2019. pp. 462-466 (Studies in Health Technology and Informatics).

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Stratified mortality prediction of patients with acute kidney injury in critical care

Abstract

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Conference

Keywords

ASJC Scopus subject areas

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