Cargando…
Maximal Glycemic Difference, the Possible Strongest Glycemic Variability Parameter to Predict Mortality in ICU Patients
BACKGROUND: This retrospective study aimed to determine the correlation of blood glucose and glycemic variability with mortality and to identify the strongest glycemic variability parameter for predicting mortality in critically ill patients. METHODS: A total of 528 patients admitted to the medical...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7463358/ https://www.ncbi.nlm.nih.gov/pubmed/32908696 http://dx.doi.org/10.1155/2020/5071509 |
_version_ | 1783577113478037504 |
---|---|
author | Issarawattana, Thanaphruet Bhurayanontachai, Rungsun |
author_facet | Issarawattana, Thanaphruet Bhurayanontachai, Rungsun |
author_sort | Issarawattana, Thanaphruet |
collection | PubMed |
description | BACKGROUND: This retrospective study aimed to determine the correlation of blood glucose and glycemic variability with mortality and to identify the strongest glycemic variability parameter for predicting mortality in critically ill patients. METHODS: A total of 528 patients admitted to the medical intensive care unit were included in this study. Blood glucose levels during the first 24 hours of admission were recorded and calculated to determine the glycemic variability. Significant glycemic variability parameters, including the standard deviation, coefficient of variation, maximal blood glucose difference, and J-index, were subsequently compared between intensive care unit survivors and nonsurvivors. A binary logistic regression was performed to identify independent factors associated with mortality. To determine the strongest glycemic variability parameter to predict mortality, the area under the receiver operating characteristic of each glycemic variability parameter was determined, and a pairwise comparison was performed. RESULTS: Among the 528 patients, 17.8% (96/528) were nonsurvivors. Both survivor and nonsurvivor groups were clinically comparable. However, nonsurvivors had significantly higher median APACHE-II scores (23 [21, 27] vs. 18 [14, 22]; p < 0.01) and a higher mechanical ventilator support rate (97.4% vs. 74.9%; p < 0.01). The mean blood glucose level and significant glycemic variability parameters were higher in nonsurvivors than in survivors. The maximal blood glucose difference yielded a similar power to the coefficient of variation (p = 0.21) but was significantly stronger than the standard deviation (p = 0.005) and J-index (p = 0.006). CONCLUSIONS: Glycemic variability was independently associated with intensive care unit mortality. Higher glycemic variability was identified in the nonsurvivor group regardless of preexisting diabetes mellitus. The maximal blood glucose difference and coefficient of variation of the blood glucose were the two strongest parameters for predicting intensive care unit mortality in this study. |
format | Online Article Text |
id | pubmed-7463358 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-74633582020-09-08 Maximal Glycemic Difference, the Possible Strongest Glycemic Variability Parameter to Predict Mortality in ICU Patients Issarawattana, Thanaphruet Bhurayanontachai, Rungsun Crit Care Res Pract Research Article BACKGROUND: This retrospective study aimed to determine the correlation of blood glucose and glycemic variability with mortality and to identify the strongest glycemic variability parameter for predicting mortality in critically ill patients. METHODS: A total of 528 patients admitted to the medical intensive care unit were included in this study. Blood glucose levels during the first 24 hours of admission were recorded and calculated to determine the glycemic variability. Significant glycemic variability parameters, including the standard deviation, coefficient of variation, maximal blood glucose difference, and J-index, were subsequently compared between intensive care unit survivors and nonsurvivors. A binary logistic regression was performed to identify independent factors associated with mortality. To determine the strongest glycemic variability parameter to predict mortality, the area under the receiver operating characteristic of each glycemic variability parameter was determined, and a pairwise comparison was performed. RESULTS: Among the 528 patients, 17.8% (96/528) were nonsurvivors. Both survivor and nonsurvivor groups were clinically comparable. However, nonsurvivors had significantly higher median APACHE-II scores (23 [21, 27] vs. 18 [14, 22]; p < 0.01) and a higher mechanical ventilator support rate (97.4% vs. 74.9%; p < 0.01). The mean blood glucose level and significant glycemic variability parameters were higher in nonsurvivors than in survivors. The maximal blood glucose difference yielded a similar power to the coefficient of variation (p = 0.21) but was significantly stronger than the standard deviation (p = 0.005) and J-index (p = 0.006). CONCLUSIONS: Glycemic variability was independently associated with intensive care unit mortality. Higher glycemic variability was identified in the nonsurvivor group regardless of preexisting diabetes mellitus. The maximal blood glucose difference and coefficient of variation of the blood glucose were the two strongest parameters for predicting intensive care unit mortality in this study. Hindawi 2020-08-24 /pmc/articles/PMC7463358/ /pubmed/32908696 http://dx.doi.org/10.1155/2020/5071509 Text en Copyright © 2020 Thanaphruet Issarawattana and Rungsun Bhurayanontachai. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Issarawattana, Thanaphruet Bhurayanontachai, Rungsun Maximal Glycemic Difference, the Possible Strongest Glycemic Variability Parameter to Predict Mortality in ICU Patients |
title | Maximal Glycemic Difference, the Possible Strongest Glycemic Variability Parameter to Predict Mortality in ICU Patients |
title_full | Maximal Glycemic Difference, the Possible Strongest Glycemic Variability Parameter to Predict Mortality in ICU Patients |
title_fullStr | Maximal Glycemic Difference, the Possible Strongest Glycemic Variability Parameter to Predict Mortality in ICU Patients |
title_full_unstemmed | Maximal Glycemic Difference, the Possible Strongest Glycemic Variability Parameter to Predict Mortality in ICU Patients |
title_short | Maximal Glycemic Difference, the Possible Strongest Glycemic Variability Parameter to Predict Mortality in ICU Patients |
title_sort | maximal glycemic difference, the possible strongest glycemic variability parameter to predict mortality in icu patients |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7463358/ https://www.ncbi.nlm.nih.gov/pubmed/32908696 http://dx.doi.org/10.1155/2020/5071509 |
work_keys_str_mv | AT issarawattanathanaphruet maximalglycemicdifferencethepossiblestrongestglycemicvariabilityparametertopredictmortalityinicupatients AT bhurayanontachairungsun maximalglycemicdifferencethepossiblestrongestglycemicvariabilityparametertopredictmortalityinicupatients |