BUG: 
### 

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

- [X] I have confirmed this bug exists on the master branch of pandas.


### Reproducible Example

```python
import pandas as pd

# regular integer works
s = pd.Series([1, 3, "45345"])
s.astype("int64")

# nullable integer fails with exception
s = pd.Series([1, 3, "45345"])
s.astype("Int64")
```


### Issue Description

Conversion of strings with valid integer numeric content to nullable integer fails with "TypeError: cannot safely cast non-equivalent object to int64".

Exception raised pandas/core/arrays/integer.py", line 136, in safe_cast


### Expected Behavior

IMHO conversion of valid strings to nullable integer should succeed, to be consistent with regular integers.



### Installed Versions

Besides the versions used below (python3.9 from Ubuntu repo and pandas master branch from Github), it also fails with python3.7 (self compiled), python3.8 and 3.9 (from Ubuntu repo) and python3.10 (self compiled) with pandas installed from pypi (version 1.3.4).

<details>

INSTALLED VERSIONS
------------------
commit           : 057c6f81b464c6bbb667d326e203ad0dbd17cbde
python           : 3.9.5.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.11.0-38-generic
Version          : #42~20.04.1-Ubuntu SMP Tue Sep 28 20:41:07 UTC 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.4.0.dev0+1053.g057c6f81b4
numpy            : 1.21.4
pytz             : 2021.3
dateutil         : 2.8.2
pip              : 20.0.2
setuptools       : 44.0.0
Cython           : 0.29.24
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
