Influência das Variáveis Antropométricas na Proteína C Reactiva

Introdução: A obesidade é um problema generalizado e crescente, assim como um dos componentes da Síndrome Metabólica (SM). Em populações saudáveis, a proteína C reactiva (PCR)correlaciona-se com medições de obesidade. Objectivos: Analisar numa populações de doentes com doença cardíaca, se se mantém a correlação entre a PCR e as variáveis de SM, assim como a relação entre a PCR e a doença arterial coronária (DAC). Material e Métodos: Estudo de 1231 doente admitidos para procedimento cardíaco invasivo electivo. Obtiveram-se dados antropométricos, valores de PCR, assim como identificação das variáveis componentes de SM. Comparámos os grupos distribuídos de acordo com o Índice de Massa Corporal (IMC) e correlacionámos com PCR e outras variáveis. Resultados: A frequência global de SM foi de 59%. A PCR foi significativamente mais elevada em doentes obesos, comparada com doentes com peso normal ou excesso de peso. A PCR correlacionou-se significativamente com todos os factores de risco. As melhores correlações foram obtidas com o perímetro abdominal, índice de massa corporal e número de componentes de SM. O melhor limiar da PCR para predizer SM foi de 0,38 mg/dL. Os factores de risco,incluindo as medidas de obesidade explicam apenas 3,3 – 3,5% da variância da PCR. O sexo foi o factor que melhor se correlacionou, seguido pelo colesterol-HDL. Das variáveis antropométricas, apenas o Índice de Massa Corporal contribuiu para a variância. Não se detectou nenhuma associação entre a PCR, SM e a presença de DAC. Conclusões: Em doentes com doença cardíaca, encontrámos uma associação significativa entre a PCR, variáveis antropométricas e SM, contudo não tão significativas como o previamente descrito em populações saudáveis. O número de componentes de SM é também um factor importante para influenciar a PCR.

Upper Arm Measurements of Healthy Neonates Comparing Ultrasonography and Anthropometric Methods

Objective: To compare measurements of the upper arm cross-sectional areas (total arm area,arm muscle area, and arm fat area of healthy neonates) as calculated using anthropometry with the values obtained by ultrasonography. Materials and methods: This study was performed on 60 consecutively born healthy neonates: gestational age (mean6SD) 39.661.2 weeks, birth weight 3287.16307.7 g, 27 males (45%) and 33 females (55%). Mid-arm circumference and tricipital skinfold thickness measurements were taken on the left upper mid-arm according to the conventional anthropometric method to calculate total arm area, arm muscle area and arm fat area. The ultrasound evaluation was performed at the same arm location using a Toshiba sonolayer SSA-250AÒ, which allows the calculation of the total arm area, arm muscle area and arm fat area by the number of pixels enclosed in the plotted areas. Statistical analysis: whenever appropriate, parametric and non-parametric tests were used in order to compare measurements of paired samples and of groups of samples. Results: No significant differences between males and females were found in any evaluated measurements, estimated either by anthropometry or by ultrasound. Also the median of total arm area did not differ significantly with either method (P50.337). Although there is evidence of concordance of the total arm area measurements (r50.68, 95% CI: 0.55–0.77) the two methods of measurement differed for arm muscle area and arm fat area. The estimated median of measurements by ultrasound for arm muscle area were significantly lower than those estimated by the anthropometric method, which differed by as much as 111% (P,0.001). The estimated median ultrasound measurement of the arm fat was higher than the anthropometric arm fat area by as much as 31% (P,0.001). Conclusion: Compared with ultrasound measurements using skinfold measurements and mid-arm circumference without further correction may lead to overestimation of the cross-sectional area of muscle and underestimation of the cross-sectional fat area. The correlation between the two methods could be interpreted as an indication for further search of correction factors in the equations.

Predictive Variables Affecting Transfusion Requirements in Orthotopic Liver Transplantation

INTRODUCTION AND AIMS: Adult orthotopic liver transplantation (OLT) is associated with considerable blood product requirements. The aim of this study was to assess the ability of preoperative information to predict intraoperative red blood cell (RBC) transfusion requirements among adult liver recipients. METHODS: Preoperative variables with previously demonstrated relationships to intraoperative RBC transfusion were identified from the literature: sex, age, pathology, prothrombin time (PT), factor V, hemoglobin (Hb), and platelet count (plt). These variables were then retrospectively collected from 758 consecutive adult patients undergoing OLT from 1997 to 2007. Relationships between these variables and intraoperative blood transfusion requirements were examined by both univariate analysis and multiple linear regression analysis. RESULTS: Univariate analysis confirmed significant associations between RBC transfusion and PT, factor V, Hb, Plt, pathology, and age (P values all < .001). However, stepwise backward multivariate analysis excluded variables Plt and factor V from the multiple regression linear model. The variables included in the final predictive model were PT, Hb, age, and pathology. Patients suffering from liver carcinoma required more blood products than those suffering from other pathologies. Yet, the overall predictive power of the final model was limited (R(2) = .308; adjusted R(2) = .30). CONCLUSION: Preoperative variables have limited predictive power for intraoperative RBC transfusion requirements even when significant statistical associations exist, identifying only a small portion of the observed total transfusion variability. Preoperative PT, Hb, age, and liver pathology seem to be the most significant predictive factors but other factors like severity of liver disease, surgical technique, medical experience in liver transplantation, and other noncontrollable human variables may play important roles to determine the final transfusion requirements.

Hopelessness and Related Variables among Cancer Patients in the Southern European Psycho-Oncology Study (SEPOS).

BACKGROUND: Although hopelessness has been studied in cancer, no data are available in non-English-speaking countries. OBJECTIVE: The authors sought to amass data from Southern European countries (Italy, Portugal, Spain, and Switzerland) in order to fill this void. METHOD: A group of 312 cancer patients completed the Mini-MAC Hopelessness subscale, the Hospital Anxiety and Depression Scale (HADS), the Cancer Worry Inventory (CWI), and a six-item Visual Analog scale (VAS) to measure intensity of physical symptoms, general well-being, difficulty in coping with cancer, intensity of social support from close relationships, leisure activity, and support from religious beliefs. RESULTS: Regression analysis indicated that HADS-Depression, VAS Maladaptive Coping and Well-Being, and the CWI explained 42% of the variance. CONCLUSION: Hopelessness in cancer patients seems not exclusively to correspond to depression, but is related to various other psychosocial factors, such as maladaptive coping, as well.