pandas read_sql missing dtype on empty result
#### Code Sample, a copy-pastable example if possible

con = some sqlalchemy engine
query = "select * from table"
result = pd.read_sql(query, con)

#### Problem description

Assume table have two columns, user (str) and id (int).
Previously, even if the result has 0 rows, the columns would have dtype in consistent with the table column.

result.dtypes
user    object
**id       int64**
dtype: object

In pandas 0.23, if the result is empty, then all the columns dtypes in result are object.

result.dtypes
user    object
**id      object**
dtype: object


#### Expected Output
user    object
id       int64
dtype: object

#### Output of ``pd.show_versions()``


<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.5.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 62 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.23.0
pytest: 3.5.1
pip: 10.0.1
setuptools: 39.1.0
Cython: 0.28.2
numpy: 1.14.3
scipy: 1.1.0
pyarrow: 0.9.0
xarray: 0.10.4
IPython: 6.4.0
sphinx: None
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.1
tables: None
numexpr: 2.6.5
feather: 0.4.0
matplotlib: 2.2.2
openpyxl: 2.5.3
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.4
lxml: 4.2.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.7
pymysql: 0.8.1
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
