Objectives: Sonographic thoracic B-lines and N-terminal pro-brain-type natriuretic peptide (NT-ProBNP) have been shown to help differentiate between congestive heart failure (CHF) and chronic obstructive pulmonary disease (COPD). The authors hypothesized that ultrasound (US) could be used to predict CHF and that it would provide additional predictive information when combined with NT-ProBNP. They also sought to determine optimal two-and eight-zone scanning protocols when different thresholds for a positive scan were used.Methods: This was a prospective, observational study of a convenience sample of adult patients presenting to the emergency department (ED) with shortness of breath. Each patient had an eight-zone thoracic US performed by one of five sonographers, and serum NT-ProBNP levels were measured. Chart review by two physicians blinded to the US results served as the criterion standard. The operating characteristics of two-and eight-zone thoracic US alone, compared to, and combined with NT-ProBNP test results for predicting CHF were calculated using both dichotomous and interval likelihood ratios (LRs).Results: One-hundred patients were enrolled. Six were excluded because of incomplete data. Results of 94 patients were analyzed. A positive eight-zone US, defined as at least two positive zones on each side, had a positive likelihood ratio (LR+) of 3.88 (99% confidence interval [CI] = 1.55 to 9.73) and a negative likelihood ratio (LR)) of 0.5 (95% CI = 0.30 to 0.82), while the NT-ProBNP demonstrated a LR+ of 2.3 (95% CI = 1.41 to 3.76) and LR) of 0.24 (95% CI = 0.09 to 0.66). Using interval LRs for the eight-zone US test alone, the LR for a totally positive test (all eight zones positive) was infinite and for a totally negative test (no zones positive) was 0.22 (95% CI = 0.06 to 0.80). For two-zone US, interval LRs were 4.73 (95% CI = 2.10 to 10.63) when inferior lateral zones were positive bilaterally and 0.3 (95% CI = 0.13 to 0.71) when these were negative. These changed to 8.04 (95% CI = 1.76 to 37.33) and 0.11 (95% CI = 0.02 to 0.69), respectively, when congruent with NT-ProBNP.Conclusions: Bedside thoracic US for B-lines can be a useful test for diagnosing CHF. Predictive accuracy is greatly improved when studies are totally positive or totally negative. A two-zone protocol performs similarly to an eight-zone protocol. Thoracic US can be used alone or can provide additional predictive power to NT-ProBNP in the immediate evaluation of dyspneic patients presenting to the ED.

Background: Measurements of the optic nerve sheath diameter (ONSD) using bedside ultrasound (US) have been shown to correlate with clinical and radiologic signs and symptoms of increased intracranial pressure (ICP).

Nuclear magnetic relaxation rates are measured for whole blood, blood plasma, whole blood clots, and plasma clots in vitro. Relaxation rates are linear in the hematocrit and transverse relaxation rates are significantly greater than longitudinal relaxation rates. Longitudinal relaxation rates measured from 0.01 to 42 MHz for proton Larmor frequencies are found to decline monotonically with increasing magnetic field strength; however, the dispersion curves do not follow a simple Lorentzian behavior, which is anticipated in a suspension of particles in a solution of proteins having a distribution of molecular weights. The transverse relaxation rate is a function of the acquisition parameters, in particular, the choice of TE in either Hahn echo experiments or in echo-train experiments. The origin of this dependence of T2 on TE or the interpulse spacing in an echo train is identified with the exchange of water from inside the red blood cell to the outside and is only an important relaxation mechanism in the case where the blood cell membrane is intact and the cell contains deoxygenated hemoglobin. The dependence of the apparent transverse relaxation rate on the interpulse spacing in a Meiboom-Gill-Carr-Purcell pulse sequence provides the estimate that the mean residence time of water inside the blood cell is about 10 ms. These data provide a sound basis for understanding the dependence of magnetic images on magnetic field strength and the choices of the image acquisition parameters, TE and TR.

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The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Build-ing on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.