Certain assumptions are implicit, and not always obvious, in all of the methods for predicting future growth. Some were mentioned in the sections describing the methods, and others are mentioned here.
The validity and accuracy of these methods depend on the validity of the assumptions on which they are based. The surgeon about to perform leg length surgery should be aware of how these assumptions might apply to the method he is using and to the patient under consideration. It is reasonable to question the assumptions.
Does our growth data reflect normal growth?
It is a common finding that comparing our patients to the Boston Growth Study data results in more patients appearing to be of tall growth percentiles than of short when one would expect equal numbers above and below the mean. More than expected actually fall more than two standard deviations above the mean.
This may be due to the fact that those data are based, to some extent, on x-rays of the longer leg of polio patients. It is likely that in may of those patients the longer leg was also affected by the disease and thus was shorter than normal. If that was the case it would result in a bias of their data and the findings noted above.
In any case, even if their data describe a population with shorter legs than normal, it will not lead to errors in the context of leg length discrepancy as long as the pattern of growth (the proportion of adult length achieved relative to skeletal maturation) is normal.
Do all children share the same pattern of growth?
The Boston Growth Study documents the relationship between leg length and skeletal age. It was performed on the patient population of one hospital in Boston without regard to racial or other differences.
Others may be more interested in the relationship between chronological growth and height; and others in that between skeletal and chronological ages.
It is possible that patients of different races, or even different genetic stock within the same race, have patterns of growth different from that described by that study. If that is the case, then errors might be anticipated in the prediction of growth based on that study.
It is common practice, however, to use the data from the Boston Growth Study irrespective of race, and there have been no reports of errors due to race or other population characteristics.
Is skeletal age assessment reliable?
The assessment of skeletal age is the weak link in the prediction of future growth because our measurement methodology is so crude. There is even another concern, however, and that is with respect to the validity of the method. The various authors who have developed methods for the assessment of skeletal age have done so with somewhat different goals and with different methodology. Which method is most appropriate in the context of leg length prediction is unclear. We can take some comfort, however, from the fact that if we use the Greulich and Pyle method we are at least using the method that the Boston Growth Study used in correlating leg length with skeletal age.
We tend to think of skeletal age as an attribute of a patient. It is probably more useful to think of it as the result of a method applied to his x-rays, something like the result of a laboratory test.
We also know that ossification of the cartilage models of bones, and therefore skeletal age, depends on the health, nutrition and medication of the patient. These are variables that change with time, sometimes under our control and sometimes not. Growth in length of the long bones may also be affected, but perhaps not be affected in the same way, and therefore apparent skeletal age may not be a good indicator in patients with active disease, nutritional deficiencies, or who are taking medication. Patients with hypothyroidism, for example, can be greatly delayed in apparent skeletal age, and may advance very rapidly under replacement medication.
Is growth inhibition constant?
Predicting future growth and the future of leg length discrepancy depends on knowing what the growth inhibition will be in the future. One study has shown that in a sample of patients with varying diagnoses the relative growth of the two legs was constant with a linear regression coefficient of greater than 0.995 in every case. This means that we can be fairly confident that growth inhibition remains constant throughout growth. We can also safely assume that the inhibition in the future will be the same as that in the past.
Are measurements of leg length accurate?
The accuracy and validity of all analyses of leg length, including that performed by Pedipod/LLD, depend upon the accuracy of leg length data. Such data are subject to variations in x-ray technique and errors in interpretation of the x-rays.
Whatever x-ray technique is used, it should be consistent. Mixing x-rays with a magnification factor with those without will give erroneous ideas about the pattern of growth.
In addition to measurements of length, Pedipod/LLD depends, in certain circumstances, on the measurement of the amount of lengthening achieved by a surgical procedure. This measurement is subject to magnification and poorly defined landmarks, and can be a source of error.
Do we know the pre-operative status?
Pedipod/LLD needs to know the leg lengths immediately prior to surgery, otherwise it has no starting point to predict the effects of that surgery. It is always wise, in clinical practice, to measure leg lengths and skeletal age accurately before surgery.
Pedipod/LLD assumes that the data entered for the last assessment prior to the surgery represents the situation at the time of surgery, regardless of the relative dates. A warning or comment will be given if the date of that assessment precedes the surgery by more than thirty days. This assumption is important for the Straight Line Graph, but plays no part in the Menelaus method which is only used prior to surgery in the timing of epiphysiodesis.
Pedipod/LLD pays almost no other attention to calendar dates since it is skeletal time and not calendar time that is important in this context.