BACKGROUND: Risk assessments of patients should be based on objective variables, such as biological markers that can be measured routinely. The acute response to stress causes the release of catecholamines from the adrenal medulla accompanied by chromogranin A (CGA). To date, no study has evaluated the prognostic value of CGA in critically ill intensive care unit patients. METHODS: We conducted a prospective study of intensive care unit patients by measuring serum procalcitonin (PCT), C-reactive protein (CRP), and CGA at the time of admission. Univariate and multivariate analyses were performed to evaluate the ability of these biomarkers to predict mortality. RESULTS: In 120 consecutive patients, we found positive correlations between CGA and the following: CRP (r(2) = 0.216; P = 0.02), PCT (r(2) = 0.396; P < 0.001), Simplified Acute Physiologic Score II (SAPS II) (r(2) = 0.438; P < 0.001), and the Logistic Organ Dysfunction System (LODS) score (r(2) = 0.374; P < 0.001). Nonsurvivors had significantly higher CGA and PCT concentrations than survivors [median (interquartile range): 293.0 microg/L (163.5-699.5 microg/L) vs 86.0 microg/L (53.8-175.3 microg/L) for CGA, and 6.78 microg/L (2.39-22.92 microg/L) vs 0.54 microg/L (0.16-6.28 microg/L) for PCT; P < 0.001 for both comparisons]. In a multivariable linear regression analysis, creatinine (P < 0.001), age (P < 0.001), and SAPS II (P = 0.002) were the only significant independent variables predicting CGA concentration (r(2) = 0.352). A multivariate Cox regression analysis identified 3 independent factors predicting death: log-normalized CGA concentration [hazard ratio (HR), 7.248; 95% confidence interval (CI), 3.004-17.487], SAPS II (HR, 1.046; 95% CI, 1.026-1.067), and cardiogenic shock (HR, 3.920; 95% CI, 1.731-8.880). CONCLUSIONS: CGA is a strong and independent indicator of prognosis in critically ill nonsurgical patients.
BACKGROUND: Risk assessments of patients should be based on objective variables, such as biological markers that can be measured routinely. The acute response to stress causes the release of catecholamines from the adrenal medulla accompanied by chromogranin A (CGA). To date, no study has evaluated the prognostic value of CGA in critically ill intensive care unit patients. METHODS: We conducted a prospective study of intensive care unit patients by measuring serum procalcitonin (PCT), C-reactive protein (CRP), and CGA at the time of admission. Univariate and multivariate analyses were performed to evaluate the ability of these biomarkers to predict mortality. RESULTS: In 120 consecutive patients, we found positive correlations between CGA and the following: CRP (r(2) = 0.216; P = 0.02), PCT (r(2) = 0.396; P < 0.001), Simplified Acute Physiologic Score II (SAPS II) (r(2) = 0.438; P < 0.001), and the Logistic Organ Dysfunction System (LODS) score (r(2) = 0.374; P < 0.001). Nonsurvivors had significantly higher CGA and PCT concentrations than survivors [median (interquartile range): 293.0 microg/L (163.5-699.5 microg/L) vs 86.0 microg/L (53.8-175.3 microg/L) for CGA, and 6.78 microg/L (2.39-22.92 microg/L) vs 0.54 microg/L (0.16-6.28 microg/L) for PCT; P < 0.001 for both comparisons]. In a multivariable linear regression analysis, creatinine (P < 0.001), age (P < 0.001), and SAPS II (P = 0.002) were the only significant independent variables predicting CGA concentration (r(2) = 0.352). A multivariate Cox regression analysis identified 3 independent factors predicting death: log-normalized CGA concentration [hazard ratio (HR), 7.248; 95% confidence interval (CI), 3.004-17.487], SAPS II (HR, 1.046; 95% CI, 1.026-1.067), and cardiogenic shock (HR, 3.920; 95% CI, 1.731-8.880). CONCLUSIONS:CGA is a strong and independent indicator of prognosis in critically ill nonsurgical patients.
Authors: Chih-Hsin Hsu; Luis F Reyes; Carlos J Orihuela; Ricardo Buitrago; Antonio Anzueto; Nilam J Soni; Stephanie Levine; Jay Peters; Cecilia A Hinojosa; Stefano Aliberti; Oriol Sibila; Alejandro Rodriguez; James D Chalmers; Ignacio Martin-Loeches; Jose Bordon; Jose Blanquer; Francisco Sanz; Pedro J Marcos; Jordi Rello; Jordi Solé-Violán; Marcos I Restrepo Journal: Biomarkers Date: 2015-07-08 Impact factor: 2.658
Authors: Francis Schneider; Charlotte Bach; Hélène Chung; Luca Crippa; Thomas Lavaux; Pierre-Edouard Bollaert; Michel Wolff; Angelo Corti; Anne Launoy; Xavier Delabranche; Thierry Lavigne; Nicolas Meyer; Patrick Garnero; Marie-Hélène Metz-Boutigue Journal: Intensive Care Med Date: 2012-06-16 Impact factor: 17.440
Authors: Nagendu B Dev; Saiful A Mir; Jiaur R Gayen; Jawed A Siddiqui; Maja Mustapic; Sucheta M Vaingankar Journal: J Cardiovasc Transl Res Date: 2014-05-13 Impact factor: 4.132