diff --git a/tests/test_processing.py b/tests/test_processing.py
index 0f371660..35d87961 100644
--- a/tests/test_processing.py
+++ b/tests/test_processing.py
@@ -199,3 +199,41 @@ def test_xqrs(self):
 
         assert comparitor.sensitivity > 0.99
         assert comparitor.positive_predictivity > 0.99
+
+    pass
+
+
+# Module-level tests for empty-annotation edge cases (pytest collects these
+# directly, unlike the lowercase class above which is skipped by default).
+
+def test_compare_annotations_empty_ref():
+    """When reference annotations are empty, sensitivity should be NaN."""
+    import math
+
+    comparitor = processing.compare_annotations(
+        np.array([]), np.array([10, 20, 30]), 5
+    )
+    assert math.isnan(comparitor.sensitivity)
+    assert comparitor.positive_predictivity == 0.0
+
+
+def test_compare_annotations_empty_test():
+    """When test annotations are empty, PPV should be NaN."""
+    import math
+
+    comparitor = processing.compare_annotations(
+        np.array([10, 20, 30]), np.array([]), 5
+    )
+    assert comparitor.sensitivity == 0.0
+    assert math.isnan(comparitor.positive_predictivity)
+
+
+def test_compare_annotations_both_empty():
+    """When both annotation arrays are empty, both metrics should be NaN."""
+    import math
+
+    comparitor = processing.compare_annotations(
+        np.array([]), np.array([]), 5
+    )
+    assert math.isnan(comparitor.sensitivity)
+    assert math.isnan(comparitor.positive_predictivity)
diff --git a/wfdb/processing/evaluate.py b/wfdb/processing/evaluate.py
index 3e960286..78a8c695 100644
--- a/wfdb/processing/evaluate.py
+++ b/wfdb/processing/evaluate.py
@@ -123,8 +123,11 @@ def _calc_stats(self):
         self.fn = self.n_ref - self.tp
         # No tn attribute
 
-        self.sensitivity = float(self.tp) / float(self.tp + self.fn)
-        self.positive_predictivity = float(self.tp) / self.n_test
+        denom_sens = self.tp + self.fn
+        self.sensitivity = float(self.tp) / denom_sens if denom_sens > 0 else float("nan")
+        self.positive_predictivity = (
+            float(self.tp) / self.n_test if self.n_test > 0 else float("nan")
+        )
 
     def compare(self):
         """