PERF: improve StringArray.isna
See https://github.com/pandas-dev/pandas/issues/57431#issuecomment-1978293416 for context.

- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.
- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.


Speed-up is around 2x for this case (extracted from one of our ASVs):

```python
dtype = "string"
N = 10**6
data = np.array([str(i) * 5 for i in range(N)], dtype=object)
na_value = pd.NA
ser = pd.Series(data, dtype=dtype)

%timeit ser.isna()
# 11.3 ms ± 47.4 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)    <-- main
# 5.01 ms ± 55.2 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)    <-- PR
```

Not entirely sure it is worth the extra code, but so it definitely gives a decent speedup for a common operation.
This pull request is stale because it has been open for thirty days with no activity. Please [update](https://pandas.pydata.org/pandas-docs/stable/development/contributing.html#updating-your-pull-request) and respond to this comment if you're still interested in working on this. needs rebase, otherwise LGTM