![]() ![]() Recent published guidance has recommended the use of the Haycock formula, but there is a strong argument that for a valid comparison the same BSA formula should be used as in the original reference study which was used to compute the Z-scores. Many formulas have been used to calculate body surface area including those of Boyd, Dubois and Dubois and Haycock, and it should be noted that there is considerable discrepancy in the values derived by each formula, particularly at low body size. For most measurements, the recommendation has been to calculate Z-scores with respect to patient body surface area rather than height or weight alone. The question of which patient factors should be used to reflect overall body size has been addressed in recent published guidelines. WHICH PATIENT FACTORS SHOULD BE CONSIDERED? In other words, structures do not tend to obey the relationship y = ax + b (where y is the measured structure, x is the marker of total body size, a is the scaling coefficient and b is a constant). body surface area or weight) is rarely a simple linear one. heart valve) and surrogate marker of total body size (e.g. The determination of the ‘best-fit’ relationship relies upon finding the best mathematical fit for the data, and it has long been recognised that the correlation between size of body structure (e.g. These values have been derived in many separate studies, of varying sample sizes, and the word ‘allometry’ has been used since 1936 to describe the “relationship between changes in shape and overall size”. Therefore, in order to calculate a Z-score one must define the mean for each body size point, and the corresponding standard deviation. For example, where the mean size of the aortic valve is 20mm, with a defined standard deviation of 3 mm, the Z-score of an aortic valve with annulus 14 mm is: The Z-score value conveys the magnitude of deviation from the mean. Thus, Z-scores above the population mean have a positive value and those below the population mean have a negative value. Where χ is the observed measurement, μ is the expected measurement (population mean) and σ is the standard deviation of the population. The use of Z-scores facilitates the detection of pathological increases in left ventricular dimensions, over and above that expected due to normal growth, by showing an increased Z-score over time. However, if a patient with chronic aortic or mitral valve regurgitation is being followed through serial assessment then clearly it is an abnormal and inappropriate dilation of the left ventricle that must be excluded. As an example, the left ventricle will become larger in all children as they grow. ![]() This approach has major attractions in paediatric cardiology and is increasingly being adopted. The Z-score describes how many standard deviations above or below a size or age-specific population mean a given measurement lies. In addition, if a measurement deviates from normality it is necessary for the clinician to gauge the magnitude of such deviation.Īn approach to the description of clinical and echocardiographic variables is to describe the measurement in terms of a Z-score. Therefore, the interpretation of these measurements during childhood presents a unique challenge, in determining whether a given measurement is within the expected range. In adult practice, ultrasound measurements are often reported with respect to a single “normal range” but this approach is impossible in growing children because the normal range of measurements will be impacted by patient growth and / or patient age. Echocardiographic assessment is integral to patient assessment in the majority of children and decisions with respect to surgery or catheter intervention are frequently based on echocardiographic findings. At the most basic level this typically includes measurement of the child's weight, height and blood pressure at clinic visits. Measurements are an important part of clinical assessment in the practice of paediatric cardiology.
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