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The Lund and Browder chart is a tool useful in the management of burns for estimating the total body surface area affected. It was created by Dr. Charles Lund, Senior Surgeon at Boston City Hospital, and Dr. Newton Browder, based on their experiences in treating over 300 burn victims injured at the Cocoanut Grove fire in Boston in 1942.
The original Baux score was the addition of two factors, the first being the total body surface area affected by burning (usually estimated using the Wallace rule of nines, or calculated using a Lund and Browder chart) and the second being the age of the patient. The score is expressed as:
For children and infants, the Lund and Browder chart is used to assess the burned body surface area. Different percentages are used because the ratio of the combined surface area of the head and neck to the surface area of the limbs is typically larger in children than that of an adult. [2]
The Wallace rule of nines is a tool used in pre-hospital and emergency medicine to estimate the total body surface area (BSA) affected by a burn.In addition to determining burn severity, the measurement of burn surface area is important for estimating patients' fluid requirements and determining hospital admission criteria.
It also uses a sophisticated toggling system to control the visualization of data rows across many months or years. It is designed to be flexible, but still standardizes some parts of the chart. This template should be transcluded in other templates, NOT in article pages.
Template:Bar chart/styles.css This template can be used to create a horizontal bar chart, scrolling down a page, in a format which can be parsed by text-based web browsers. The data items can be simple numbers, or the result of calculations based on template parameters.
The normal distribution is NOT assumed nor required in the calculation of control limits. Thus making the IndX/mR chart a very robust tool. Thus making the IndX/mR chart a very robust tool. This is demonstrated by Wheeler using real-world data [ 4 ] , [ 5 ] and for a number of highly non-normal probability distributions.
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