Medical scientists love p-values and in a publication, I found the following patient statistics table. I stumbled over the *Number of patients* line. 

[![enter image description here](https://i.stack.imgur.com/eriBO.png)](https://i.stack.imgur.com/eriBO.png)

They divided their subject group into two subgroups [TAV](https://en.wikipedia.org/wiki/Tricuspid_valve) and [BAV](https://en.wikipedia.org/wiki/Bicuspid_aortic_valve) and I asked how they calculated the p-value, because you only have one characteristic BAV/TAV. If you look for instance at the *Male* row, you see that you can use a 2x2 contingency table consisting of 2 characteristics BAV/TAV and Male/Female and make e.g. a Fisher test.

What was done in the *Number of patients* row was to *fake* a 2x2 contingency table repeating and reversing the numbers:

$$\begin{array}{c|c}
347&32\\\hline
32&347
\end{array}
$$

From the viewpoint that they want to express how similar the number of patients are in the BAV and TAV group, this kind of makes sense because it gives a p-value of 1 (two tailed Fisher) when BAV and TAV have the same number of patients. However, I have never seen this and I cannot find any reference to such an approach.

**Question:** Can someone tell me whether it is correct what they did?