Usefulness of the N-Terminal Fraction of Brain Natriuretic Peptide for Deciding When to Refer Patients With Sleep Apnea-Hypopnea Syndrome to the Cardiologist

Introduction and objectiveWhen sleep apnea-hypopnea syndrome (SAHS) and cardiovascular disease occur concurrently, prognosis is affected. Echocardiography can detect structural cardiac abnormalities but using this technique in all patients would place a heavy burden on resources. The objective of this study was to investigate whether the N-terminal fraction of brain natriuretic peptide (NT-proBNP) can be used as a marker for silent heart disease.Patients and methodsNT-proBNP concentration was measured in the 114 consecutive patients with SAHS who underwent echocardiography before starting treatment. Left and right ventricular systolic and diastolic function, as well as structural abnormalities, were studied. Correlations between NT-proBNP concentration and the abnormalities detected were investigated. A receiver operating characteristics (ROC) curve was plotted for NT-proBNP concentration and cardiac abnormalities.ResultsData for 98 patients were finally analyzed. NT-proBNP concentration was significantly correlated with ventricular septal thickness (r=0.63), posterior wall thickness (r=0.45), and left ventricular enddiastolic diameter (r=0.51) (P<.0001 for all correlations). The area under the ROC curve was significant (0.870; 95% confidence interval, 0.801-0.939; P<.0001). Assuming that specificity would be more useful for clinical practice, we calculated that NT-proBNP concentrations below 100 and 200 pg/mL could rule out structural abnormalities with a reliability of 90% and 100%, respectively.ConclusionsNT-proBNP concentration was strongly correlated with echocardiographic abnormalities and so could be a useful tool for identifying patients who should be referred to the cardiologist.     

Multivariate modelling of responses to conditional items: New possibilities for latent class analysis

Questionnaire data may contain missing values because certain questions do not apply to all respondents. For instance, questions addressing particular attributes of a symptom, such as frequency, triggers or seasonality, are only applicable to those who have experienced the symptom, while for those who have not, responses to these items will be missing. This missing information does not fall into the category ‘missing by design’, rather the features of interest do not exist and cannot be measured regardless of survey design. Analysis of responses to such conditional items is therefore typically restricted to the subpopulation in which they apply. This article is concerned with joint multivariate modelling of responses to both unconditional and conditional items without restricting the analysis to this subpopulation. Such an approach is of interest when the distributions of both types of responses are thought to be determined by common parameters affecting the whole population. By integrating the conditional item structure into the model, inference can be based both on unconditional data from the entire population and on conditional data from subjects for whom they exist. This approach opens new possibilities for multivariate analysis of such data. We apply this approach to latent class modelling and provide an example using data on respiratory symptoms (wheeze and cough) in children. Conditional data structures such as that considered here are common in medical research settings and, although our focus is on latent class models, the approach can be applied to other multivariate models. Copyright © 2009 John Wiley & Sons, Ltd.     

Treatment of the Breast’s Lateral Pole: Adjuvant Maneuver to Pitanguy’s Technique

Surgical procedures for the mammary region currently are assuming an important role in body-contouring surgery. Enhancement of results is a constant challenge to the plastic surgeon. A simple and efficient maneuver for resection of the breast’s lateral pole based on the mammoplasty technique of Professor Ivo Pitanguy is described. This study realized at the Private Clinic Sérgio Carreir?o, Rio de Janeiro, RJ, Brazil.