RESUMO
BACKGROUND: Major surgery comes with a high risk for postoperative inflammatory complications. Preoperative risk scores predict mortality risk but fail to identify patients at risk for complications following cardiovascular surgery. We therefore assessed the value of preoperative red cell distribution width (RDW) as a predictor for pneumonia and sepsis after cardiovascular surgery and studied the relation of RDW with hematopoietic tissue activity. METHODS: RDW is an easily accessible, yet seldomly used parameter from routine haematology measurements. RDW was extracted from the Utrecht Patient Orientated Database (UPOD) for preoperative measurements in patients undergoing open abdominal aortic anuerysm repair (AAA)(N = 136) or coronary artery bypass grafting (CABG)(N = 2193). The cohorts were stratified in tertiles to assess effects over the different groups. Generalized Linear Models were used to determine associations between RDW and postoperative inflammatory complications. Hematopoietic tissue activity was scored using fluor-18-(18F)-deoxyglucose positron emission tomography and associated with RDW using linear regression models. RESULTS: In total, 43(31.6%) and 73 patients (3.3%) suffered from inflammatory complications after AAA-repair or CABG, respectively; the majority being pneumonia in both cohorts. Postoperative inflammatory outcome incidence increased from 19.6% in the lowest to 48.9% in the highest RDW tertile with a corresponding risk ratio (RR) of 2.35 ([95%CI:1.08-5.14] P = 0.032) in AAA patients. In the CABG cohort, the incidence of postoperative inflammatory outcomes increased from 1.8% to 5.3% with an adjusted RR of 1.95 ([95%CI:1.02-3.75] P = 0.044) for the highest RDW tertile compared with the lowest RDW tertile. FDG-PET scans showed associations of RDW with tissue activity in the spleen (B = 0.517 [P = 0.001]) and the lumbar bone marrow (B = 0.480 [P = 0.004]). CONCLUSION: Elevated RDW associates with increased risk for postoperative inflammatory complications and hematopoietic tissue activity. RDW likely reflects chronic low-grade inflammation and should be considered to identify patients at risk for postoperative inflammatory complications following cardiovascular surgery.
Assuntos
Aneurisma da Aorta Abdominal/cirurgia , Ponte de Artéria Coronária/efeitos adversos , Pneumonia/diagnóstico , Sepse/diagnóstico , Idoso , Aneurisma da Aorta Abdominal/sangue , Biomarcadores/metabolismo , Índices de Eritrócitos/fisiologia , Feminino , Fluordesoxiglucose F18 , Humanos , Masculino , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Complicações Pós-Operatórias/diagnóstico , Valor Preditivo dos Testes , Cuidados Pré-Operatórios/métodos , Compostos Radiofarmacêuticos , Estudos RetrospectivosRESUMO
High-sensitivity troponin I (hsTnI) and N-terminal pro-brain natriuretic peptide (NT-pro-BNP) are predictors of coronary artery disease. Recently, routine hematological parameters emerged as mortality predictors. We examined the predictive value of hematological parameters (from the Utrecht Patient Oriented Database) and hsTnI and NT-pro-BNP for mortality in a coronary angiography population (Utrecht Coronary Biobank n = 1913). Using Cox regression, receiver operating characteristics, integrated discrimination improvement (IDI), and continuous net reclassification improvement (cNRI) analysis, we compared the predictive properties of hematological parameters with hsTnI and NT-pro-BNP for mortality. During a median follow-up duration of 1.8 years, 77 deaths occurred. A panel of 7 hematological parameters (leukocyte count, reticulocyte mean corpuscular hemoglobin concentration, red blood cell [RBC] green (FL1) fluorescence, %neutrophils, %large [>120 fL] RBCs, %monocytes, and coefficient of variation of neutrophil complexity) was highly predictive. Added to clinical characteristics, hematological parameters (area under the curve [AUC]: 0.855, P < .001; IDI: 0.04, P = .02; cNRI: 0.41, P < .001) were better predictors than hsTnI (AUC: 0.818) or NT-pro-BNP (AUC: 0.834) alone or combined (AUC: 0.834). Hematological parameters may provide mortality risk information following coronary angiography and may be superior to hsTnI and/or NT-pro-BNP.
Assuntos
Angiografia Coronária , Doença da Artéria Coronariana/sangue , Doença da Artéria Coronariana/mortalidade , Peptídeo Natriurético Encefálico/sangue , Fragmentos de Peptídeos/sangue , Troponina I/sangue , Idoso , Idoso de 80 Anos ou mais , Biomarcadores/sangue , Doença da Artéria Coronariana/diagnóstico por imagem , Feminino , Seguimentos , Humanos , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Modelos de Riscos Proporcionais , Curva ROC , Fatores de Risco , Taxa de SobrevidaRESUMO
Prediction of primary cardiovascular events has been thoroughly investigated since the landmark Framingham risk score was introduced. However, prediction of secondary events after initial events of coronary artery disease (CAD) poses a new challenge. In a cohort of coronary angiography patients (nâ=â1760), we examined readily available hematological parameters from the UPOD (Utrecht Patient Oriented Database) and their addition to prediction of secondary cardiovascular events. Backward stepwise multivariable Cox regression analysis was used to test their ability to predict death and major adverse cardiovascular events (MACE). Continuous net reclassification improvement (cNRI) and integrated discrimination improvement (IDI) measures were calculated for the hematological parameters on top of traditional risk factors to assess prediction improvement. Panels of 3 to 8 hematological parameters significantly improved prediction of death and adverse events. The IDIs ranged from 0.02 to 0.07 (all Pâ<â0.001) among outcome measures and the cNRIs from 0.11 to 0.40 (Pâ<â0.001 in 5 of 6 outcome measures). In the hematological panels red cell distribution width (RDW) appeared most often. The multivariable adjusted hazard ratio of RDW per 1 standard deviation (SD) increase for MACE was 1.19 [1.08-1.32], Pâ<â0.001. Routinely measured hematological parameters significantly improved prediction of mortality and adverse events in coronary angiography patients. Accurately indicating high-risk patients is of paramount importance in clinical decision-making.