Abstract Background Malnutrition can affect the clinical course of hospitalized patients, increasing hospital stay, infections, mortality, and hospital costs. Among heart disease patients, the malnutrition prevalence ranges from 25 to 51.9%. Objective To assess the prevalence of malnutrition and its association with clinical complications in cardiac patients admitted to a cardiology hospital. Method Retrospective cohort study with patients evaluated within 48 hours of admission to the ward of a referral center for cardiology in Porto Alegre, Brazil. Patients were aged 18 years or older. Malnutrition was assessed by Subjective Global Assessment. Length of hospital stay, transfer to the intensive care unit (ICU), hospital discharge and in-hospital death were collected from medical records. Statistical analysis was performed using the SPSS 22.0 program. Comparisons between groups with and without malnutrition were made by unpaired Student's t-test and chi-square test with adjusted residuals, and multivariate Poisson regression used for analysis of outcomes. The significance level considered was 5%. Results We evaluated 130 patients aged 63 ± 13 years, 63% were male, and the most frequent cause of hospitalization was angina (25%). The prevalence of malnutrition was 27% and, after statistical adjustment for age, malnutrition was positively associated with ICU transfer and length of hospital stay longer than seven days. Conclusion The prevalence of malnutrition found in this sample was 27% and this nutritional diagnosis was positively associated with ICU transfer and length of hospital stay longer than seven days. (Int J Cardiovasc Sci. 2020; [online].ahead print, PP.0-0)

Abstract Objective: To analyze the dual interference between cardiac implantable electronic devices (CIEDs) and bioelectrical impedance analysis (BIA). Methods: Forty-three individuals admitted for CIEDs implantation were submitted to a tetrapolar BIA with an alternating current at 800 microA and 50 kHz frequency before and after the devices’ implantation. During BIA assessment, continuous telemetry was maintained between the device programmer and the CIEDs in order to look for evidence of possible electric interference in the intracavitary signal of the device. Results: BIA in patients with CIEDs was safe and not associated with any device malfunction or electrical interference in the intracardiac electrogram of any electrode. After the implantation of the devices, there were significant reductions in BIA measurements of resistance, reactance, and measurements adjusted for height resistance and reactance, reflecting an increase (+ 1 kg; P<0.05) in results of total body water and extracellular water in liter and, consequently, increases in fat-free mass (FFM) and extracellular mass in kg. Because of changes in the hydration status and FFM values, without changes in weight, fat mass was significantly lower (-1.2 kg; P<0.05). Conclusion: BIA assessment in patients with CIEDs was safe and not associated with any device malfunction. The differences in BIA parameters might have occurred because of modifications on the patients’ body composition, associated to their hydration status, and not to the CIEDs.

FUNDAMENTO: A maioria dos estudos relatando o paradoxo da obesidade utiliza índice de massa corporal (IMC) para classificar obesidade. Dados avaliando o valor prognóstico de outras medidas indiretas de composição corporal são pouco explorados na insuficiência cardíaca (IC). OBJETIVO: Avaliar a associação entre IMC e outras medidas de composição corporal indiretas com risco de morte por todas as causas na IC. MÉTODOS: Parâmetros antropométricos de composição corporal foram avaliados em 344 pacientes ambulatoriais com fração de ejeção do ventrículo esquerdo (FEVE) < 50%, de uma coorte prospectiva seguida durante 30 ± 8,2 meses. A sobrevida foi avaliada por curvas de Kaplan-Meier e análise de regressão de risco proporcional de Cox. RESULTADOS: Os pacientes eram predominantemente do sexo masculino, de etiologia não-isquêmica e com disfunção sistólica do VE moderada a grave (FEVE média de 32 ± 9%). Prega cutânea tricipital (PCT) foi o único parâmetro antropométrico associado com prognóstico, com valores significativamente menores nos pacientes que morreram (p = 0,047). Uma PCT > 20 mm estava presente em 9% dos pacientes que morreram e em 22% dos vivos (p = 0,027). Na análise univariada, creatinina sérica, FEVE e classe funcional foram associadas ao risco de morte. Na regressão de Cox, PCT > 20 mm foi o preditor independente mais forte de mortalidade por qualquer causa (hazard ratio: 0,36; IC 95%: 0,13-0,97; p = 0,03). CONCLUSÃO: Embora IMC seja o parâmetro antropométrico mais utilizado na prática clínica, nossos resultados sugerem que PCT pode ser um melhor preditor de mortalidade em pacientes ambulatoriais com IC.

BACKGROUND: Most reports regarding the obesity paradox have focused on body mass index (BMI) to classify obesity and the prognostic values of other indirect measurements of body composition remain poorly examined in heart failure (HF). Objective: To evaluate the association between BMI and other indirect, but easily accessible, body composition measurements associated with the risk of all-cause mortality in HF. METHODS: Anthropometric parameters of body composition were assessed in 344 outpatients with a left ventricular ejection fraction (LVEF) of <50% from a prospective HF cohort that was followed-up for 30 ± 8.2 months. Survival was evaluated using the Kaplan-Meier method and Cox proportional hazard regression analysis. RESULTS: HF patients were predominantly male, of non-ischemic etiology, and had moderate to severe LV systolic dysfunction (mean LVEF = 32 ± 9%). Triceps skinfold (TSF) was the only anthropometric index that was associated with HF prognosis and had significantly lower values in patients who died (p = 0.047). A TSF > 20 mm was present in 9% of patients that died and 22% of those who survived (p = 0.027). Univariate analysis showed that serum creatinine level, LVEF, and NYHA class were associated with the risk of death, while Cox proportional hazard regression analysis showed that TSF > 20 was a strong independent predictor of all-cause mortality (hazard ratio = 0.36; 95% confidence interval = 0.13-0.97, p = 0.03). CONCLUSION: Although BMI is the most widely used anthropometric parameter in clinical practice, our results suggested that TSF is a better predictive marker of mortality in HF outpatients.