The data for all patients are held in the same database that is compatible with Microsoft Access. Although the tables can be manipulated using that program this is not recommended since links can be inadvertently lost rendering the data unreliable. If you modify the database directly from Microsoft Access you risk making your data permanently inaccessible to Pedipod/LLD. If you plan to use the database in this way, backup first, and use a copy of the database, not the original.
One can only lose data entered since the last backup!
The database should be backed up frequently to avoid losing data through computer malfunction. This can be done with a simple menu command.


A growth segment is a series of leg length assessments uninterrupted by surgery.
In order to perform its analysis Pedipod/LLD divides all available growth data into growth segments. Available data are divided into growth segments by surgical procedures that change length or growth rate. Each segment is then analyzed separately by performing linear regression analysis on the data in that segment.
Accuracy in individual growth segments increases with the duration of that segment, the number of assessments it contains, and, of course, the accuracy of that data. If there is only one assessment in a growth segment Pedipod/LLD cannot plot the growth line. If there was a lengthening immediately preceding that point it may use the amount of the lengthening, but, if it does so, the accuracy of that segment depends on the accuracy of the value entered.
Accuracy in a single growth segment is of clinical importance only if that segment is being used to predict the future. In other words, only the data for the last surgical procedure, the assessment immediately preceding it, and those assessments following it are used in predicting future growth and the effects of further surgery.


Pedipod/LLD cannot check for incorrect reading of x-ray measurements.
Pedipod/LLD does its best to check the data for validity every time a Straight Line Graph Assessment is performed. If suspicious data are detected appropriate comments and warnings are provided. This enables the user to review the data to ensure that it has been properly entered, and, perhaps, to enter further data.
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