TIMP1 and MMP9 are predictors of mortality in septic patients in the emergency department and intensive care unit unlike MMP9/TIMP1 ratio: Multivariate model.
INTRODUCTION:Matrix metalloproteinases and tissue inhibitors of metalloproteinases could be promising biomarkers for establishing prognosis during the development of sepsis. It is necessary to clarify the relationship between matrix metalloproteinases and their tissue inhibitors. We conducted a coho...
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2017-01-01
|
| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC5305237?pdf=render |
| _version_ | 1819136510283218944 |
|---|---|
| author | Maria Eugenia Niño Sergio Eduardo Serrano Daniela Camila Niño Diana Margarita McCosham Maria Eugenia Cardenas Vivian Poleth Villareal Marcos Lopez Antonio Pazin-Filho Fabian Alberto Jaimes Fernando Cunha Richard Schulz Diego Torres-Dueñas |
| author_facet | Maria Eugenia Niño Sergio Eduardo Serrano Daniela Camila Niño Diana Margarita McCosham Maria Eugenia Cardenas Vivian Poleth Villareal Marcos Lopez Antonio Pazin-Filho Fabian Alberto Jaimes Fernando Cunha Richard Schulz Diego Torres-Dueñas |
| author_sort | Maria Eugenia Niño |
| collection | DOAJ |
| description | INTRODUCTION:Matrix metalloproteinases and tissue inhibitors of metalloproteinases could be promising biomarkers for establishing prognosis during the development of sepsis. It is necessary to clarify the relationship between matrix metalloproteinases and their tissue inhibitors. We conducted a cohort study with 563 septic patients, in order to elucidate the biological role and significance of these inflammatory biomarkers and their relationship to the severity and mortality of patients with sepsis. MATERIALS AND METHODS:A multicentric prospective cohort was performed. The sample was composed of patients who had sepsis as defined by the International Conference 2001. Serum procalcitonin, creatinine, urea nitrogen, C-Reactive protein, TIMP1, TIMP2, MMP2 and MMP9 were quantified; each patient was followed until death or up to 30 days. A descriptive analysis was performed by calculating the mean and the 95% confidence interval for continuous variables and proportions for categorical variables. A multivariate logistic regression model was constructed by the method of intentional selection of covariates with mortality at 30 days as dependent variable and all the other variables as predictors. RESULTS:Of the 563 patients, 68 patients (12.1%) died within the first 30 days of hospitalization in the ICU. The mean values for TIMP1, TIMP2 and MMP2 were lower in survivors, MMP9 was higher in survivors. Multivariate logistic regression showed that age, SOFA and Charlson scores, along with TIMP1 concentration, were statistically associated with mortality at 30 days of septic patients; serum MMP9 was not statistically associated with mortality of patients, but was a confounder of the TIMP1 variable. CONCLUSION:It could be argued that plasma levels of TIMP1 should be considered as a promising prognostic biomarker in the setting of sepsis. Additionally, this study, like other studies with large numbers of septic patients does not support the predictive value of TIMP1 / MMP9. |
| first_indexed | 2024-12-22T10:36:07Z |
| format | Article |
| id | doaj.art-7d5c4ff6c2774217ae059ebe19b8d6d6 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-22T10:36:07Z |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-7d5c4ff6c2774217ae059ebe19b8d6d62022-12-21T18:29:10ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01122e017119110.1371/journal.pone.0171191TIMP1 and MMP9 are predictors of mortality in septic patients in the emergency department and intensive care unit unlike MMP9/TIMP1 ratio: Multivariate model.Maria Eugenia NiñoSergio Eduardo SerranoDaniela Camila NiñoDiana Margarita McCoshamMaria Eugenia CardenasVivian Poleth VillarealMarcos LopezAntonio Pazin-FilhoFabian Alberto JaimesFernando CunhaRichard SchulzDiego Torres-DueñasINTRODUCTION:Matrix metalloproteinases and tissue inhibitors of metalloproteinases could be promising biomarkers for establishing prognosis during the development of sepsis. It is necessary to clarify the relationship between matrix metalloproteinases and their tissue inhibitors. We conducted a cohort study with 563 septic patients, in order to elucidate the biological role and significance of these inflammatory biomarkers and their relationship to the severity and mortality of patients with sepsis. MATERIALS AND METHODS:A multicentric prospective cohort was performed. The sample was composed of patients who had sepsis as defined by the International Conference 2001. Serum procalcitonin, creatinine, urea nitrogen, C-Reactive protein, TIMP1, TIMP2, MMP2 and MMP9 were quantified; each patient was followed until death or up to 30 days. A descriptive analysis was performed by calculating the mean and the 95% confidence interval for continuous variables and proportions for categorical variables. A multivariate logistic regression model was constructed by the method of intentional selection of covariates with mortality at 30 days as dependent variable and all the other variables as predictors. RESULTS:Of the 563 patients, 68 patients (12.1%) died within the first 30 days of hospitalization in the ICU. The mean values for TIMP1, TIMP2 and MMP2 were lower in survivors, MMP9 was higher in survivors. Multivariate logistic regression showed that age, SOFA and Charlson scores, along with TIMP1 concentration, were statistically associated with mortality at 30 days of septic patients; serum MMP9 was not statistically associated with mortality of patients, but was a confounder of the TIMP1 variable. CONCLUSION:It could be argued that plasma levels of TIMP1 should be considered as a promising prognostic biomarker in the setting of sepsis. Additionally, this study, like other studies with large numbers of septic patients does not support the predictive value of TIMP1 / MMP9.http://europepmc.org/articles/PMC5305237?pdf=render |
| spellingShingle | Maria Eugenia Niño Sergio Eduardo Serrano Daniela Camila Niño Diana Margarita McCosham Maria Eugenia Cardenas Vivian Poleth Villareal Marcos Lopez Antonio Pazin-Filho Fabian Alberto Jaimes Fernando Cunha Richard Schulz Diego Torres-Dueñas TIMP1 and MMP9 are predictors of mortality in septic patients in the emergency department and intensive care unit unlike MMP9/TIMP1 ratio: Multivariate model. PLoS ONE |
| title | TIMP1 and MMP9 are predictors of mortality in septic patients in the emergency department and intensive care unit unlike MMP9/TIMP1 ratio: Multivariate model. |
| title_full | TIMP1 and MMP9 are predictors of mortality in septic patients in the emergency department and intensive care unit unlike MMP9/TIMP1 ratio: Multivariate model. |
| title_fullStr | TIMP1 and MMP9 are predictors of mortality in septic patients in the emergency department and intensive care unit unlike MMP9/TIMP1 ratio: Multivariate model. |
| title_full_unstemmed | TIMP1 and MMP9 are predictors of mortality in septic patients in the emergency department and intensive care unit unlike MMP9/TIMP1 ratio: Multivariate model. |
| title_short | TIMP1 and MMP9 are predictors of mortality in septic patients in the emergency department and intensive care unit unlike MMP9/TIMP1 ratio: Multivariate model. |
| title_sort | timp1 and mmp9 are predictors of mortality in septic patients in the emergency department and intensive care unit unlike mmp9 timp1 ratio multivariate model |
| url | http://europepmc.org/articles/PMC5305237?pdf=render |
| work_keys_str_mv | AT mariaeugenianino timp1andmmp9arepredictorsofmortalityinsepticpatientsintheemergencydepartmentandintensivecareunitunlikemmp9timp1ratiomultivariatemodel AT sergioeduardoserrano timp1andmmp9arepredictorsofmortalityinsepticpatientsintheemergencydepartmentandintensivecareunitunlikemmp9timp1ratiomultivariatemodel AT danielacamilanino timp1andmmp9arepredictorsofmortalityinsepticpatientsintheemergencydepartmentandintensivecareunitunlikemmp9timp1ratiomultivariatemodel AT dianamargaritamccosham timp1andmmp9arepredictorsofmortalityinsepticpatientsintheemergencydepartmentandintensivecareunitunlikemmp9timp1ratiomultivariatemodel AT mariaeugeniacardenas timp1andmmp9arepredictorsofmortalityinsepticpatientsintheemergencydepartmentandintensivecareunitunlikemmp9timp1ratiomultivariatemodel AT vivianpolethvillareal timp1andmmp9arepredictorsofmortalityinsepticpatientsintheemergencydepartmentandintensivecareunitunlikemmp9timp1ratiomultivariatemodel AT marcoslopez timp1andmmp9arepredictorsofmortalityinsepticpatientsintheemergencydepartmentandintensivecareunitunlikemmp9timp1ratiomultivariatemodel AT antoniopazinfilho timp1andmmp9arepredictorsofmortalityinsepticpatientsintheemergencydepartmentandintensivecareunitunlikemmp9timp1ratiomultivariatemodel AT fabianalbertojaimes timp1andmmp9arepredictorsofmortalityinsepticpatientsintheemergencydepartmentandintensivecareunitunlikemmp9timp1ratiomultivariatemodel AT fernandocunha timp1andmmp9arepredictorsofmortalityinsepticpatientsintheemergencydepartmentandintensivecareunitunlikemmp9timp1ratiomultivariatemodel AT richardschulz timp1andmmp9arepredictorsofmortalityinsepticpatientsintheemergencydepartmentandintensivecareunitunlikemmp9timp1ratiomultivariatemodel AT diegotorresduenas timp1andmmp9arepredictorsofmortalityinsepticpatientsintheemergencydepartmentandintensivecareunitunlikemmp9timp1ratiomultivariatemodel |