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Prediction of mortality among patients with chronic kidney disease: A systematic review

BACKGROUND: Chronic kidney disease (CKD) is a common medical condition that is increasing in prevalence. Existing published evidence has revealed through regression analyses that several clinical characteristics are associated with mortality in CKD patients. However, the predictive accuracies of the...

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Autores principales: Hansrivijit, Panupong, Chen, Yi-Ju, Lnu, Kriti, Trongtorsak, Angkawipa, Puthenpura, Max M, Thongprayoon, Charat, Bathini, Tarun, Mao, Michael A, Cheungpasitporn, Wisit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8353601/
https://www.ncbi.nlm.nih.gov/pubmed/34430385
http://dx.doi.org/10.5527/wjn.v10.i4.59
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author Hansrivijit, Panupong
Chen, Yi-Ju
Lnu, Kriti
Trongtorsak, Angkawipa
Puthenpura, Max M
Thongprayoon, Charat
Bathini, Tarun
Mao, Michael A
Cheungpasitporn, Wisit
author_facet Hansrivijit, Panupong
Chen, Yi-Ju
Lnu, Kriti
Trongtorsak, Angkawipa
Puthenpura, Max M
Thongprayoon, Charat
Bathini, Tarun
Mao, Michael A
Cheungpasitporn, Wisit
author_sort Hansrivijit, Panupong
collection PubMed
description BACKGROUND: Chronic kidney disease (CKD) is a common medical condition that is increasing in prevalence. Existing published evidence has revealed through regression analyses that several clinical characteristics are associated with mortality in CKD patients. However, the predictive accuracies of these risk factors for mortality have not been clearly demonstrated. AIM: To demonstrate the accuracy of mortality predictive factors in CKD patients by utilizing the area under the receiver operating characteristic (ROC) curve (AUC) analysis. METHODS: We searched Ovid MEDLINE, EMBASE, and the Cochrane Library for eligible articles through January 2021. Studies were included based on the following criteria: (1) Study nature was observational or conference abstract; (2) Study populations involved patients with non-transplant CKD at any CKD stage severity; and (3) Predictive factors for mortality were presented with AUC analysis and its associated 95% confidence interval (CI). AUC of 0.70-0.79 is considered acceptable, 0.80-0.89 is considered excellent, and more than 0.90 is considered outstanding. RESULTS: Of 1759 citations, a total of 18 studies (n = 14579) were included in this systematic review. Eight hundred thirty two patients had non-dialysis CKD, and 13747 patients had dialysis-dependent CKD (2160 patients on hemodialysis, 370 patients on peritoneal dialysis, and 11217 patients on non-differentiated dialysis modality). Of 24 mortality predictive factors, none were deemed outstanding for mortality prediction. A total of seven predictive factors [N-terminal pro-brain natriuretic peptide (NT-proBNP), BNP, soluble urokinase plasminogen activator receptor (suPAR), augmentation index, left atrial reservoir strain, C-reactive protein, and systolic pulmonary artery pressure] were identified as excellent. Seventeen predictive factors were in the acceptable range, which we classified into the following subgroups: predictors for the non-dialysis population, echocardiographic factors, comorbidities, and miscellaneous. CONCLUSION: Several factors were found to predict mortality in CKD patients. Echocardiography is an important tool for mortality prognostication in CKD patients by evaluating left atrial reservoir strain, systolic pulmonary artery pressure, diastolic function, and left ventricular mass index.
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spelling pubmed-83536012021-08-23 Prediction of mortality among patients with chronic kidney disease: A systematic review Hansrivijit, Panupong Chen, Yi-Ju Lnu, Kriti Trongtorsak, Angkawipa Puthenpura, Max M Thongprayoon, Charat Bathini, Tarun Mao, Michael A Cheungpasitporn, Wisit World J Nephrol Systematic Reviews BACKGROUND: Chronic kidney disease (CKD) is a common medical condition that is increasing in prevalence. Existing published evidence has revealed through regression analyses that several clinical characteristics are associated with mortality in CKD patients. However, the predictive accuracies of these risk factors for mortality have not been clearly demonstrated. AIM: To demonstrate the accuracy of mortality predictive factors in CKD patients by utilizing the area under the receiver operating characteristic (ROC) curve (AUC) analysis. METHODS: We searched Ovid MEDLINE, EMBASE, and the Cochrane Library for eligible articles through January 2021. Studies were included based on the following criteria: (1) Study nature was observational or conference abstract; (2) Study populations involved patients with non-transplant CKD at any CKD stage severity; and (3) Predictive factors for mortality were presented with AUC analysis and its associated 95% confidence interval (CI). AUC of 0.70-0.79 is considered acceptable, 0.80-0.89 is considered excellent, and more than 0.90 is considered outstanding. RESULTS: Of 1759 citations, a total of 18 studies (n = 14579) were included in this systematic review. Eight hundred thirty two patients had non-dialysis CKD, and 13747 patients had dialysis-dependent CKD (2160 patients on hemodialysis, 370 patients on peritoneal dialysis, and 11217 patients on non-differentiated dialysis modality). Of 24 mortality predictive factors, none were deemed outstanding for mortality prediction. A total of seven predictive factors [N-terminal pro-brain natriuretic peptide (NT-proBNP), BNP, soluble urokinase plasminogen activator receptor (suPAR), augmentation index, left atrial reservoir strain, C-reactive protein, and systolic pulmonary artery pressure] were identified as excellent. Seventeen predictive factors were in the acceptable range, which we classified into the following subgroups: predictors for the non-dialysis population, echocardiographic factors, comorbidities, and miscellaneous. CONCLUSION: Several factors were found to predict mortality in CKD patients. Echocardiography is an important tool for mortality prognostication in CKD patients by evaluating left atrial reservoir strain, systolic pulmonary artery pressure, diastolic function, and left ventricular mass index. Baishideng Publishing Group Inc 2021-07-25 2021-07-25 /pmc/articles/PMC8353601/ /pubmed/34430385 http://dx.doi.org/10.5527/wjn.v10.i4.59 Text en ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
spellingShingle Systematic Reviews
Hansrivijit, Panupong
Chen, Yi-Ju
Lnu, Kriti
Trongtorsak, Angkawipa
Puthenpura, Max M
Thongprayoon, Charat
Bathini, Tarun
Mao, Michael A
Cheungpasitporn, Wisit
Prediction of mortality among patients with chronic kidney disease: A systematic review
title Prediction of mortality among patients with chronic kidney disease: A systematic review
title_full Prediction of mortality among patients with chronic kidney disease: A systematic review
title_fullStr Prediction of mortality among patients with chronic kidney disease: A systematic review
title_full_unstemmed Prediction of mortality among patients with chronic kidney disease: A systematic review
title_short Prediction of mortality among patients with chronic kidney disease: A systematic review
title_sort prediction of mortality among patients with chronic kidney disease: a systematic review
topic Systematic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8353601/
https://www.ncbi.nlm.nih.gov/pubmed/34430385
http://dx.doi.org/10.5527/wjn.v10.i4.59
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