diff --git a/pandas/core/dtypes/cast.py b/pandas/core/dtypes/cast.py
index 408e58e23aaed..db3d764fb97a2 100644
--- a/pandas/core/dtypes/cast.py
+++ b/pandas/core/dtypes/cast.py
@@ -910,9 +910,9 @@ def maybe_upcast(
     """
     new_dtype, fill_value = maybe_promote(values.dtype, fill_value)
     # We get a copy in all cases _except_ (values.dtype == new_dtype and not copy)
-    values = values.astype(new_dtype, copy=copy)
+    upcast_values = values.astype(new_dtype, copy=copy)
 
-    return values, fill_value
+    return upcast_values, fill_value  # type: ignore[return-value]
 
 
 def invalidate_string_dtypes(dtype_set: set[DtypeObj]):
diff --git a/pandas/tests/indexes/test_engines.py b/pandas/tests/indexes/test_engines.py
index 663ba7332c864..02d8c5b2a6a22 100644
--- a/pandas/tests/indexes/test_engines.py
+++ b/pandas/tests/indexes/test_engines.py
@@ -57,13 +57,7 @@ class TestTimedeltaEngine:
     @pytest.mark.parametrize(
         "scalar",
         [
-            # error: Argument 1 to "Timestamp" has incompatible type "timedelta64";
-            # expected "Union[integer[Any], float, str, date, datetime64]"
-            pd.Timestamp(
-                pd.Timedelta(days=42).asm8.view(
-                    "datetime64[ns]"
-                )  # type: ignore[arg-type]
-            ),
+            pd.Timestamp(pd.Timedelta(days=42).asm8.view("datetime64[ns]")),
             pd.Timedelta(days=42).value,
             pd.Timedelta(days=42).to_pytimedelta(),
             pd.Timedelta(days=42).to_timedelta64(),