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Artigo em Inglês, Espanhol | MEDLINE | ID: mdl-31767290


INTRODUCTION AND OBJECTIVES: In infective endocarditis (IE), decisions on surgical interventions are challenging and a high percentage of patients with surgical indication do not undergo these procedures. This study aimed to evaluate the short- and long-term prognosis of patients with surgical indication, comparing those who underwent surgery with those who did not. METHODS: We included 271 patients with left-sided IE treated at our institution from 2003 to 2018 and with an indication for surgery. There were 83 (31%) surgery-indicated not undergoing surgery patients with left-sided infective endocarditis (SINUS-LSIE). The primary outcome was all-cause death by day 60 and the secondary outcome was all-cause death from day 61 to 3 years of follow-up. Multivariable Cox regression and propensity score matching were used for the analysis. RESULTS: At the 60-day follow-up, 40 (21.3%) surgically-treated patients and 53 (63.9%) SINUS-LSIE patients died (P <.001). Risk of 60-day mortality was higher in SINUS-LSIE patients (HR, 3.59; 95%CI, 2.16-5.96; P <.001). Other independent predictors of the primary endpoint were unknown etiology, heart failure, atrioventricular block, and shock. From day 61 to the 3-year follow-up, there were no significant differences in the risk of death between surgically-treated and SINUS-LSIE patients (HR, 1.89; 95%CI, 0.68-5.19; P=.220). Results were consistent after propensity score matching. Independent variables associated with the secondary endpoint were previous IE, diabetes mellitus, and Charlson index. CONCLUSIONS: Two-thirds of SINUS-LSIE patients died within 60 days. Among survivors, the long-term mortality depends more on host conditions than on the treatment received during admission.

Biomarkers ; 24(4): 334-340, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-30632403


Background: In asymptomatic severe aortic stenosis (ASAS), treatment decisions are made on an individual basis, and case management presents a clinical conundrum. Methods: We prospectively phenotyped consecutive patients with ASAS using echocardiography, exercise echocardiography, cardiac MRI and biomarkers (NT-proBNP, high-sensitivity troponin T (hs-TnT) and ST2) (n = 58). The primary endpoint was a composite of cardiovascular death, new-onset symptoms, cardiac hospitalization, guideline-driven indication for valve replacement and cardiovascular death at 12 months. Results: During the first year, 46.6% patients met primary endpoint. In multivariable analysis, aortic regurgitation ≥2 (p = 0.01) and hs-TnT (p = 0.007) were the only independent predictors of the primary endpoint. The best cutoff value was identified as hs-TnT >10ng/L, which was associated with a ∼10-fold greater risk of the primary endpoint (HR, 9.62; 95% CI, 2.27-40.8; p = 0.002). A baseline predictive model including age, sex and variables showing p < 0.10 in univariable analyses showed an area under the curve (AUC) of 0.79(0.66-0.91). Incorporation of hs-TnT into this model increased the AUC to 0.90(0.81-0.98) (p = 0.03). Patient reclassification with the model including hs-TnT yielded an NRI of 1.28(0.46-1.78), corresponding to 43% adequately reclassified patients. Conclusions: In patients with ASAS, hs-TnT >10ng/L was associated with high risk of events within 12 months. Including hs-TnT in routine ASAS management markedly improved prediction metrics.

Insuficiência da Valva Aórtica/sangue , Estenose da Valva Aórtica/sangue , Troponina T/sangue , Idoso , Idoso de 80 Anos ou mais , Insuficiência da Valva Aórtica/diagnóstico por imagem , Insuficiência da Valva Aórtica/etiologia , Insuficiência da Valva Aórtica/mortalidade , Estenose da Valva Aórtica/complicações , Estenose da Valva Aórtica/diagnóstico por imagem , Estenose da Valva Aórtica/mortalidade , Área Sob a Curva , Doenças Assintomáticas , Biomarcadores/sangue , Ecocardiografia , Feminino , Humanos , Proteína 1 Semelhante a Receptor de Interleucina-1/sangue , Imagem por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Peptídeo Natriurético Encefálico/sangue , Fragmentos de Peptídeos/sangue , Prognóstico , Estudos Prospectivos , Medição de Risco , Índice de Gravidade de Doença , Análise de Sobrevida
Comput Biol Med ; 99: 209-220, 2018 08 01.
Artigo em Inglês | MEDLINE | ID: mdl-29957378


BACKGROUND AND OBJECTIVE: Currently, many orthopedic operations are planned by analyzing X-rays. The exact position of the focus is needed to calculate the real size of an object that is represented in conical projection, although in practice, this position is difficult to determine using current X-ray commercial systems. In this paper, a new geometric model is proposed in order to determine accurately, practically, and economically the location of the emitting source of commercial imaging systems using a single standard X-ray image. METHOD: The method requires a specific reference locator object to be positioned in the visual field of radiographic image. Because this object cannot implement ideal geometric points, but instead works with small spheres, it was necessary to experimentally validate the proposed methodology. The implemented software that was developed to validate the model was used in four series of tests. In these tests, we studied the influence on the final result of: 1. the selection of a specific set of markers in radiography, 2. the focus position variation in relation to radiograph and 3. the possible rotated angle of locator object about Z axis. RESULTS: The results for 164 tests that were performed with this software showed that the expected error for 99.5% of values ranges with maximum error of [-0.35%, +0.39%], which shows that the model is independent of the design of locator object and its position and orientation in the radiographic field. The software used to validate the proposed model has been found useful to verify its reliability, effectiveness, ease of implementation, and accuracy. CONCLUSIONS: This model is effective to calculate the precise position of the X-ray focus of any standard radiographic system accurately.

Algoritmos , Modelos Teóricos , Tomografia Computadorizada por Raios X , Humanos , Raios X