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Performance of APACHE IV in Medical Intensive Care Unit Patients: Comparisons with APACHE II, SAPS 3, and MPM(0) III

BACKGROUND: In this study, we analyze the performance of the Acute Physiology and Chronic Health Evaluation (APACHE) II, APACHE IV, Simplified Acute Physiology Score (SAPS) 3, and Mortality Probability Model (MPM)(0) III in order to determine which system best implements data related to the severity...

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Autores principales: Ko, Mihye, Shim, Miyoung, Lee, Sang-Min, Kim, Yujin, Yoon, Soyoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Critical Care Medicine 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6849024/
https://www.ncbi.nlm.nih.gov/pubmed/31723888
http://dx.doi.org/10.4266/acc.2018.00178
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author Ko, Mihye
Shim, Miyoung
Lee, Sang-Min
Kim, Yujin
Yoon, Soyoung
author_facet Ko, Mihye
Shim, Miyoung
Lee, Sang-Min
Kim, Yujin
Yoon, Soyoung
author_sort Ko, Mihye
collection PubMed
description BACKGROUND: In this study, we analyze the performance of the Acute Physiology and Chronic Health Evaluation (APACHE) II, APACHE IV, Simplified Acute Physiology Score (SAPS) 3, and Mortality Probability Model (MPM)(0) III in order to determine which system best implements data related to the severity of medical intensive care unit (ICU) patients. METHODS: The present study was a retrospective investigation analyzing the discrimination and calibration of APACHE II, APACHE IV, SAPS 3, and MPM(0) III when used to evaluate medical ICU patients. Data were collected for 788 patients admitted to the ICU from January 1, 2015 to December 31, 2015. All patients were aged 18 years or older with ICU stays of at least 24 hours. The discrimination abilities of the three systems were evaluated using c-statistics, while calibration was evaluated by the Hosmer-Lemeshow test. A severity correction model was created using logistics regression analysis. RESULTS: For the APACHE IV, SAPS 3, MPM(0) III, and APACHE II systems, the area under the receiver operating characteristic curves was 0.745 for APACHE IV, resulting in the highest discrimination among all four scoring systems. The value was 0.729 for APACHE II, 0.700 for SAP 3, and 0.670 for MPM(0) III. All severity scoring systems showed good calibrations: APACHE II (chi-square, 12.540; P=0.129), APACHE IV (chi-square, 6.959; P=0.541), SAPS 3 (chi-square, 9.290; P=0.318), and MPM(0) III (chi-square, 11.128; P=0.133). CONCLUSIONS: APACHE IV provided the best discrimination and calibration abilities and was useful for quality assessment and predicting mortality in medical ICU patients.
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spelling pubmed-68490242019-11-13 Performance of APACHE IV in Medical Intensive Care Unit Patients: Comparisons with APACHE II, SAPS 3, and MPM(0) III Ko, Mihye Shim, Miyoung Lee, Sang-Min Kim, Yujin Yoon, Soyoung Acute Crit Care Original Article BACKGROUND: In this study, we analyze the performance of the Acute Physiology and Chronic Health Evaluation (APACHE) II, APACHE IV, Simplified Acute Physiology Score (SAPS) 3, and Mortality Probability Model (MPM)(0) III in order to determine which system best implements data related to the severity of medical intensive care unit (ICU) patients. METHODS: The present study was a retrospective investigation analyzing the discrimination and calibration of APACHE II, APACHE IV, SAPS 3, and MPM(0) III when used to evaluate medical ICU patients. Data were collected for 788 patients admitted to the ICU from January 1, 2015 to December 31, 2015. All patients were aged 18 years or older with ICU stays of at least 24 hours. The discrimination abilities of the three systems were evaluated using c-statistics, while calibration was evaluated by the Hosmer-Lemeshow test. A severity correction model was created using logistics regression analysis. RESULTS: For the APACHE IV, SAPS 3, MPM(0) III, and APACHE II systems, the area under the receiver operating characteristic curves was 0.745 for APACHE IV, resulting in the highest discrimination among all four scoring systems. The value was 0.729 for APACHE II, 0.700 for SAP 3, and 0.670 for MPM(0) III. All severity scoring systems showed good calibrations: APACHE II (chi-square, 12.540; P=0.129), APACHE IV (chi-square, 6.959; P=0.541), SAPS 3 (chi-square, 9.290; P=0.318), and MPM(0) III (chi-square, 11.128; P=0.133). CONCLUSIONS: APACHE IV provided the best discrimination and calibration abilities and was useful for quality assessment and predicting mortality in medical ICU patients. Korean Society of Critical Care Medicine 2018-11 2018-11-21 /pmc/articles/PMC6849024/ /pubmed/31723888 http://dx.doi.org/10.4266/acc.2018.00178 Text en Copyright © 2018 The Korean Society of Critical Care Medicine This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Ko, Mihye
Shim, Miyoung
Lee, Sang-Min
Kim, Yujin
Yoon, Soyoung
Performance of APACHE IV in Medical Intensive Care Unit Patients: Comparisons with APACHE II, SAPS 3, and MPM(0) III
title Performance of APACHE IV in Medical Intensive Care Unit Patients: Comparisons with APACHE II, SAPS 3, and MPM(0) III
title_full Performance of APACHE IV in Medical Intensive Care Unit Patients: Comparisons with APACHE II, SAPS 3, and MPM(0) III
title_fullStr Performance of APACHE IV in Medical Intensive Care Unit Patients: Comparisons with APACHE II, SAPS 3, and MPM(0) III
title_full_unstemmed Performance of APACHE IV in Medical Intensive Care Unit Patients: Comparisons with APACHE II, SAPS 3, and MPM(0) III
title_short Performance of APACHE IV in Medical Intensive Care Unit Patients: Comparisons with APACHE II, SAPS 3, and MPM(0) III
title_sort performance of apache iv in medical intensive care unit patients: comparisons with apache ii, saps 3, and mpm(0) iii
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6849024/
https://www.ncbi.nlm.nih.gov/pubmed/31723888
http://dx.doi.org/10.4266/acc.2018.00178
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