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Acute kidney injury risk prediction score for critically-ill surgical patients

BACKGROUND: There has been a global increase in the incidence of acute kidney injury (AKI), including among critically-ill surgical patients. AKI prediction score provides an opportunity for early detection of patients who are at risk of AKI; however, most of the AKI prediction scores were derived f...

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Autores principales: Trongtrakul, Konlawij, Patumanond, Jayanton, Kongsayreepong, Suneerat, Morakul, Sunthiti, Pipanmekaporn, Tanyong, Akaraborworn, Osaree, Poopipatpab, Sujaree
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7271390/
https://www.ncbi.nlm.nih.gov/pubmed/32493268
http://dx.doi.org/10.1186/s12871-020-01046-2
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author Trongtrakul, Konlawij
Patumanond, Jayanton
Kongsayreepong, Suneerat
Morakul, Sunthiti
Pipanmekaporn, Tanyong
Akaraborworn, Osaree
Poopipatpab, Sujaree
author_facet Trongtrakul, Konlawij
Patumanond, Jayanton
Kongsayreepong, Suneerat
Morakul, Sunthiti
Pipanmekaporn, Tanyong
Akaraborworn, Osaree
Poopipatpab, Sujaree
author_sort Trongtrakul, Konlawij
collection PubMed
description BACKGROUND: There has been a global increase in the incidence of acute kidney injury (AKI), including among critically-ill surgical patients. AKI prediction score provides an opportunity for early detection of patients who are at risk of AKI; however, most of the AKI prediction scores were derived from cardiothoracic surgery. Therefore, we aimed to develop an AKI prediction score for major non-cardiothoracic surgery patients who were admitted to the intensive care unit (ICU). METHODS: The data of critically-ill patients from non-cardiothoracic operations in the Thai Surgical Intensive Care Unit (THAI-SICU) study were used to develop an AKI prediction score. Independent prognostic factors from regression analysis were included as predictors in the model. The outcome of interest was AKI within 7 days after the ICU admission. The AKI diagnosis was made according to the Kidney Disease Improving Global Outcomes (KDIGO)-2012 serum creatinine criteria. Diagnostic function of the model was determined by area under the Receiver Operating Curve (AuROC). Risk scores were categorized into four risk probability levels: low (0–2.5), moderate (3.0–8.5), high (9.0–11.5), and very high (12.0–16.5) risk. Risk of AKI was presented as likelihood ratios of positive (LH+). RESULTS: A total of 3474 critically-ill surgical patients were included in the model; 333 (9.6%) developed AKI. Using multivariable logistic regression analysis, older age, high Sequential Organ Failure Assessment (SOFA) non-renal score, emergency surgery, large volume of perioperative blood loss, less urine output, and sepsis were identified as independent predictors for AKI. Then AKI prediction score was created from these predictors. The summation of the score was 16.5 and had a discriminative ability for predicting AKI at AuROC = 0.839 (95% CI 0.825–0.852). LH+ for AKI were: low risk = 0.117 (0.063–0.200); moderate risk = 0.927 (0.745–1.148); high risk = 5.190 (3.881–6.910); and very high risk = 9.892 (6.230–15.695), respectively. CONCLUSIONS: The function of AKI prediction score to predict AKI among critically ill patients who underwent non-cardiothoracic surgery was good. It can aid in early recognition of critically-ill surgical patients who are at risk from ICU admission. The scores could guide decision making for aggressive strategies to prevent AKI during the perioperative period or at ICU admission. TRIAL REGISTRATION: TCTR20190408004, registered on April 4, 2019.
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spelling pubmed-72713902020-06-08 Acute kidney injury risk prediction score for critically-ill surgical patients Trongtrakul, Konlawij Patumanond, Jayanton Kongsayreepong, Suneerat Morakul, Sunthiti Pipanmekaporn, Tanyong Akaraborworn, Osaree Poopipatpab, Sujaree BMC Anesthesiol Research Article BACKGROUND: There has been a global increase in the incidence of acute kidney injury (AKI), including among critically-ill surgical patients. AKI prediction score provides an opportunity for early detection of patients who are at risk of AKI; however, most of the AKI prediction scores were derived from cardiothoracic surgery. Therefore, we aimed to develop an AKI prediction score for major non-cardiothoracic surgery patients who were admitted to the intensive care unit (ICU). METHODS: The data of critically-ill patients from non-cardiothoracic operations in the Thai Surgical Intensive Care Unit (THAI-SICU) study were used to develop an AKI prediction score. Independent prognostic factors from regression analysis were included as predictors in the model. The outcome of interest was AKI within 7 days after the ICU admission. The AKI diagnosis was made according to the Kidney Disease Improving Global Outcomes (KDIGO)-2012 serum creatinine criteria. Diagnostic function of the model was determined by area under the Receiver Operating Curve (AuROC). Risk scores were categorized into four risk probability levels: low (0–2.5), moderate (3.0–8.5), high (9.0–11.5), and very high (12.0–16.5) risk. Risk of AKI was presented as likelihood ratios of positive (LH+). RESULTS: A total of 3474 critically-ill surgical patients were included in the model; 333 (9.6%) developed AKI. Using multivariable logistic regression analysis, older age, high Sequential Organ Failure Assessment (SOFA) non-renal score, emergency surgery, large volume of perioperative blood loss, less urine output, and sepsis were identified as independent predictors for AKI. Then AKI prediction score was created from these predictors. The summation of the score was 16.5 and had a discriminative ability for predicting AKI at AuROC = 0.839 (95% CI 0.825–0.852). LH+ for AKI were: low risk = 0.117 (0.063–0.200); moderate risk = 0.927 (0.745–1.148); high risk = 5.190 (3.881–6.910); and very high risk = 9.892 (6.230–15.695), respectively. CONCLUSIONS: The function of AKI prediction score to predict AKI among critically ill patients who underwent non-cardiothoracic surgery was good. It can aid in early recognition of critically-ill surgical patients who are at risk from ICU admission. The scores could guide decision making for aggressive strategies to prevent AKI during the perioperative period or at ICU admission. TRIAL REGISTRATION: TCTR20190408004, registered on April 4, 2019. BioMed Central 2020-06-03 /pmc/articles/PMC7271390/ /pubmed/32493268 http://dx.doi.org/10.1186/s12871-020-01046-2 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Trongtrakul, Konlawij
Patumanond, Jayanton
Kongsayreepong, Suneerat
Morakul, Sunthiti
Pipanmekaporn, Tanyong
Akaraborworn, Osaree
Poopipatpab, Sujaree
Acute kidney injury risk prediction score for critically-ill surgical patients
title Acute kidney injury risk prediction score for critically-ill surgical patients
title_full Acute kidney injury risk prediction score for critically-ill surgical patients
title_fullStr Acute kidney injury risk prediction score for critically-ill surgical patients
title_full_unstemmed Acute kidney injury risk prediction score for critically-ill surgical patients
title_short Acute kidney injury risk prediction score for critically-ill surgical patients
title_sort acute kidney injury risk prediction score for critically-ill surgical patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7271390/
https://www.ncbi.nlm.nih.gov/pubmed/32493268
http://dx.doi.org/10.1186/s12871-020-01046-2
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