BUG: `Series` slicing can fail for extension array `Index`

[jrbourbeau]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd

s = pd.Series(range(5), index=pd.Index(range(5), dtype=int))
print(s.loc[4:5])  # works

# Fails with both `numpy`- and `pyarrow`-backed extension arrays for the index
s = pd.Series(range(5), index=pd.Index(range(5), dtype="Int64"))
print(s.loc[4:5])  # fails

s = pd.Series(range(5), index=pd.Index(range(5), dtype="int64[pyarrow]"))
print(s.loc[4:5])  # fails

Issue Description

I ran into an issue where slicing a series (via .loc) works for when using an index with dtype=int, but fails when I cast the index to use either numpy- or pyarrow-backed extension arrays.

Expected Behavior

I think these are all valid .loc calls that should return the corresponding selection

Installed Versions

INSTALLED VERSIONS
------------------
commit           : 8dab54d6573f7186ff0c3b6364d5e4dd635ff3e7
python           : 3.9.15.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 21.6.0
Version          : Darwin Kernel Version 21.6.0: Thu Sep 29 20:12:57 PDT 2022; root:xnu-8020.240.7~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.5.2
numpy            : 1.23.5
pytz             : 2022.6
dateutil         : 2.8.2
setuptools       : 59.8.0
pip              : 22.3.1
Cython           : None
pytest           : 7.2.0
hypothesis       : None
sphinx           : 4.5.0
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 3.1.2
IPython          : 8.7.0
pandas_datareader: None
bs4              : 4.11.1
bottleneck       : None
brotli           :
fastparquet      : 2022.11.0
fsspec           : 2022.11.0
gcsfs            : None
matplotlib       : None
numba            : None
numexpr          : 2.8.3
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 10.0.1
pyreadstat       : None
pyxlsb           : None
s3fs             : 2022.11.0
scipy            : 1.9.3
snappy           :
sqlalchemy       : 1.4.44
tables           : 3.7.0
tabulate         : None
xarray           : 2022.11.0
xlrd             : None
xlwt             : None
zstandard        : None
tzdata           : None

[jrbourbeau]

I should also note that it seems important that the reproducer in slicing at the end of the series. Things work if one slices in the beginning or middle of the series

In [6]: s = pd.Series(range(5), index=pd.Index(range(5), dtype="int64[pyarrow]"))

In [7]: s[2:3]
Out[7]:
2    2
dtype: int64

In [8]: s[:3]
Out[8]:
0    0
1    1
2    2
dtype: int64