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Objective: In patients with complex coronary artery disease (CAD) undergoing cardiac surgery, myocardial protection might be impaired due to microvascular obstruction, resulting in myocardial injury and subsequent biomarker release. Therefore, this study investigated the correlation between the complexity of CAD, reflected by the SYNTAX Score, and the release of cardiac biomarkers after CABG. Methods: In a consecutive series of 919 patients undergoing isolated CABG SYNTAX scores I and II were calculated to assess the complexity of CAD. Levels of high sensitivity cardiac troponin T (hs-cTnT) and creatine kinase-myocardial band (CK-MB) were routinely measured once before and serially after surgery. Patients were divided into tertiles according to their SYNTAX Scores I and II. Spearman correlations and regression models were performed to measure the degree of association between the release of hs-cTnT and CK-MB and the SYNTAX Scores. Results: Patients with a higher SYNTAX Score I had more comorbidities reflected in a higher EuroSCORE II. Preoperatively, higher levels of cardiac biomarkers were found in patients with higher SYNTAX Score II. No correlation was observed between hs-cTnT, CK-MB and SYNTAX Score I or II. Regression models did not show any association between cardiac biomarkers and the complexity of CAD. Conclusion: The complexity of CAD is not associated with the release of cardiac biomarkers after CABG. Factors influencing postoperative biomarker release need to be elucidated in future trials to include postoperative biomarker release into risk stratification models predicting outcome after cardiac surgery.
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OBJECTIVES: Myocardial hypertrophy results in increased levels of cardiac biomarkers in healthy individuals and in patients suffering from acute myocardial infarction. The influence of cardiac mass on postoperative cardiac biomarkers release remains unclear. This study investigated the correlation between myocardial mass and the release of high-sensitivity cardiac Troponin T (hs-cTnT) and creatine kinase-myocardial band (CK-MB) after isolated aortic valve replacement (AVR) or bypass surgery. METHODS: Myocardial mass of a consecutive retrospective series of patients was measured automatically using preoperative computer tomography scans (636 patients, AVR = 251; bypass surgery = 385). Levels of cardiac biomarkers were measured before and serially after surgery. Spearman and Pearson correlation and a multivariate regression model was performed to measure the degree of association between myocardial mass and the release of hs-cTnT and CK-MB. RESULTS: Patients were divided into 3 tertiles according to their myocardial mass index. Higher biomarker levels were measured preoperatively in the upper tertile of patients undergoing AVR (P = 0.004) or bypass surgery (P < 0.001). Patients with different heart sizes showed no differences in postoperative biomarker release neither after AVR nor bypass surgery. No statistical significant correlation was observed between myocardial mass index and postoperative release of hs-cTnT or CK-MB in any subgroup (ρ maximum 0.106). CONCLUSIONS: Postoperative biomarker release is not correlated with myocardial mass. Patient factors leading to increased postoperative biomarker levels need to be elucidated in future studies.
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Cellular response to insults may result in the initiation of different cell death processes. For many cases the cell death process will result in an acute release of cellular material that in some circumstances provides valuable information about the process (i.e. may represent a biomarker). The characteristics of the biomarker release is often informative and plays critical roles in clinical practice and toxicology research. The aim of this study is to develop a general, semi-mechanistic model to describe cell turnover and biomarker release by injured tissue that can be used for estimation in pharmacokinetic and (toxicokinetic)-pharmacodynamic studies. The model included three components: (1) natural tissue turnover, (2) biomarker release from cell death and its movement from the cell through the tissue into the blood, (3) different target insult mechanisms of cell death. We applied the general model to biomarker release profiles for four different cell insult causes. Our model simulations showed good agreements with reported data under both delayed release and rapid release cases. Additionally, we illustrate the use of the model to provide different biomarker profiles. We also provided details on interpreting parameters and their values for other researchers to customize its use. In conclusion, our general model provides a basic structure to study the kinetic behaviour of biomarker release and disposition after cellular insult.
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Muerte Celular/fisiología , Modelos Biológicos , Acetaminofén/envenenamiento , Adulto , Anciano , Anciano de 80 o más Años , Alanina Transaminasa/metabolismo , Animales , Aspartato Aminotransferasas/metabolismo , Biomarcadores/metabolismo , Muerte Celular/efectos de los fármacos , Línea Celular , Senescencia Celular/efectos de los fármacos , Enfermedad Hepática Inducida por Sustancias y Drogas/etiología , Enfermedad Hepática Inducida por Sustancias y Drogas/patología , Niño , Simulación por Computador , Creatina Quinasa/metabolismo , Venenos de Crotálidos/toxicidad , Evaluación Preclínica de Medicamentos/métodos , Femenino , Humanos , Masculino , Ratones , Persona de Mediana Edad , Infarto del Miocardio/patología , Daño por Reperfusión Miocárdica/patología , Toxicología/métodosRESUMEN
The aim of the study was to evaluate the influence of hypoxia on galactomannan and (1,3)-ß-d-glucan release of clinically relevant Aspergilli in vitro. Hypoxia decreased biomass and consequently led to lower biomarker release. However, when normalized to biomass, hypoxia led to increased levels of biomarkers at early growth stages (24 h). Antifungals (amphotericin B and voriconazole) decreased the galactomannan amount of A. fumigatus, even more prominently in hypoxia.