diff --git a/icees_api/features/sql.py b/icees_api/features/sql.py
index 5746468..5fe6c7f 100644
--- a/icees_api/features/sql.py
+++ b/icees_api/features/sql.py
@@ -798,10 +798,10 @@ def select_feature_count_all_values(
     for value in value_to_be_added:
         # only append value to levels when value is not in levels and level_op_val is empty or
         # value does not satisfy the operations encoded in the level_op_val
-        if not level_op_val or \
-                ('<' in level_op_val and int(value) >= level_op_val['<']) or \
-                ('>' in level_op_val and int(value) <= level_op_val['>']):
-            levels.append(value)
+        if value:
+            if not level_op_val or ('<' in level_op_val and int(value) >= level_op_val['<']) \
+                    or ('>' in level_op_val and int(value) <= level_op_val['>']):
+                levels.append(value)
     feat_qualifiers = [{
         "operator": "=",
         "value": level
@@ -818,21 +818,20 @@ def select_feature_count_all_values(
             } for k, v in level_op_val.items()])
         greater_value_sum = less_value_sum = 0
         for value in value_to_be_added:
-            int_val = int(value)
-            if '<' in level_op_val and int_val < level_op_val['<']:
-                less_value_sum += values[value]
-            if '>' in level_op_val and int_val > level_op_val['>']:
-                greater_value_sum += values[value]
-        if greater_value_sum > 0:
-            feat_matrix.append({
-                "frequency": greater_value_sum,
-                "percentage": div(greater_value_sum, total)
-            })
-        if less_value_sum > 0:
-            feat_matrix.append({
-                "frequency": less_value_sum,
-                "percentage": div(less_value_sum, total)
-            })
+            if value:
+                int_val = int(value)
+                if '<' in level_op_val and int_val < level_op_val['<']:
+                    less_value_sum += values[value]
+                if '>' in level_op_val and int_val > level_op_val['>']:
+                    greater_value_sum += values[value]
+        feat_matrix.append({
+            "frequency": greater_value_sum,
+            "percentage": div(greater_value_sum, total)
+        })
+        feat_matrix.append({
+            "frequency": less_value_sum,
+            "percentage": div(less_value_sum, total)
+        })
     feature_a_norm_with_biolink_class = {
         "feature_name": feature_name,
         "feature_qualifiers": feat_qualifiers,
@@ -1039,25 +1038,19 @@ def get_operator_and_value(input_levels, feat_name, append_feature_variable=Fals
     """
     fqs = []
     for input_level in input_levels:
-        # checking if feature variable name contains Age is a stop-gap solution, which will be removed after
-        # Age-related variable binning is removed in FHIR PIT and dataset is updated
-        if 'Age' in feat_name:
+        non_op_idx = 0
+        if isinstance(input_level, str):
+            for lev in input_level:
+                if lev in ['<', '>']:
+                    non_op_idx += 1
+                else:
+                    break
+        if non_op_idx == 0:
             op = '='
             op_val = input_level
         else:
-            non_op_idx = 0
-            if isinstance(input_level, str):
-                for lev in input_level:
-                    if lev in ['<', '>']:
-                        non_op_idx += 1
-                    else:
-                        break
-            if non_op_idx == 0:
-                op = '='
-                op_val = input_level
-            else:
-                op = input_level[:non_op_idx]
-                op_val = input_level[non_op_idx:]
+            op = input_level[:non_op_idx]
+            op_val = input_level[non_op_idx:]
         if append_feature_variable:
             fqs.append({feat_name: {"operator": op, "value": op_val}})
         else: