This is how I think the CRP result was calculated. The median (supposedly the centre of the range) is 0.99/2=0.495. 3.20 differs by 3.2-0.495=2.705. When this is divided by the high value or the range we get 2.705/0.99=2.732, which is 273.2%.
If we do the same with the other reading we get a median of 75 (midway between 70 and 80) and a deviation of 168-75=93. If we divide by the range 80-70=10, we get 9.30 which is 930% (not 980%).
However, if we measure the deviation from the low value of 70, we get 168-70=98, divided by the range 10 gives us 9.8=980%.
Could this be the answer to your question?
One more observation: the mean is the average value (the actual centre of the range) but the median is something different: it’s the central value in a dataset, so, in a large dataset of blood samples, the mean (average) could be the same as the median, and often is, but in many cases the median could be different. So if there is a preponderance of data around a certain value, the median could be displaced from the mean. In the first test, the results of population blood tests could have established that the value of 70 (or thereabouts) was more common than the mean 75, even though the spread of the data made the average 75 (called a positive skew distribution). I believe this to be the case, and that’s why they give the percentage deviation from the median rather than from the mean.