Merge pull request #363 from noharm-ai/develop

v3.26-beta

mobile.py

@@ -116,7 +116,7 @@
 
 @app.route("/version", methods=["GET"])
 def getVersion():
-    return {"status": "success", "data": "v3.25-beta"}, status.HTTP_200_OK
+    return {"status": "success", "data": "v3.26-beta"}, status.HTTP_200_OK
 
 
 if __name__ == "__main__":

requirements-prod.txt

@@ -5,7 +5,7 @@ SQLAlchemy==2.0.29
 Flask-SQLAlchemy==3.1.1
 troposphere
 zappa
-flask-cors==4.0.0
+flask-cors==4.0.1
 psycopg2-binary
 pandas==1.3.4
 scipy==1.10.0

requirements.txt

@@ -5,7 +5,7 @@ Flask-SQLAlchemy==3.1.1
 lambda-packages
 troposphere
 zappa
-flask-cors==4.0.0
+flask-cors==4.0.1
 psycopg2-binary
 pytest==5.4.1
 pytest-flask

services/outlier_service.py

@@ -14,7 +14,7 @@
 from services.admin import drug_service, integration_status_service
 from services import data_authorization_service, permission_service
 
-FOLD_SIZE = 15
+FOLD_SIZE = 10
 
 
 def prepare(id_drug, id_segment, user):
@@ -69,8 +69,9 @@ def add_history_and_validate():
     return refresh_outliers(id_drug=id_drug, id_segment=id_segment, user=user)
 
 
-def generate(id_drug, id_segment, fold, user):
+def generate(id_drug, id_segment, fold, user: User):
     # call prepare before generate score (only for wizard)
+    start_date = datetime.now()
 
     if fold != None:
         if not permission_service.has_maintainer_permission(user):
@@ -92,6 +93,9 @@ def generate(id_drug, id_segment, fold, user):
     csv_buffer = _get_csv_buffer(
         id_segment=id_segment, schema=user.schema, id_drug=id_drug, fold=fold
     )
+    _log_perf(start_date, "GENERATE CSV BUFFER")
+
+    start_date = datetime.now()
 
     manager = Manager()
     drugs = pandas.read_csv(csv_buffer)
@@ -102,6 +106,10 @@ def generate(id_drug, id_segment, fold, user):
         .all()
     )
 
+    _log_perf(start_date, "GET OUTLIERS LIST")
+
+    start_date = datetime.now()
+
     with Manager() as manager:
         poolDict = manager.dict()
 
@@ -130,19 +138,53 @@ def generate(id_drug, id_segment, fold, user):
         for drug in poolDict:
             new_os = new_os.append(poolDict[drug])
 
+    _log_perf(start_date, "PROCESS SCORES")
+
+    start_date = datetime.now()
+
+    updates = []
     for o in outliers:
         no = new_os[
             (new_os["medication"] == o.idDrug)
             & (new_os["dose"] == o.dose)
             & (new_os["frequency"] == o.frequency)
         ]
         if len(no) > 0:
-            o.score = no["score"].values[0]
-            o.countNum = int(no["count"].values[0])
-            o.update = datetime.today()
-            o.user = user.id
+            updates.append(
+                _to_update_row(
+                    {
+                        "id": o.id,
+                        "score": no["score"].values[0],
+                        "countNum": int(no["count"].values[0]),
+                    },
+                    user,
+                )
+            )
 
-            db.session.flush()
+    if len(updates) > 0:
+        update_stmt = f"""
+            with scores as (
+                select * from (values {",".join(updates)}) AS t (idoutlier, score, countnum, update_at, update_by)
+            )
+            update {user.schema}.outlier o
+            set 
+                contagem = s.countnum,
+                escore = s.score,
+                update_at = s.update_at,
+                update_by = s.update_by
+            from
+                scores s
+            where 
+                s.idoutlier = o.idoutlier
+        """
+
+        db.session.execute(text(update_stmt))
+
+        _log_perf(start_date, "UPDATE SCORES")
+
+
+def _to_update_row(update: dict, user: User):
+    return f"""({update["id"]}, {update["score"]}, {update["countNum"]}, '{datetime.today().isoformat()}'::timestamp, {user.id})"""
 
 
 def refresh_outliers(id_segment, user, id_drug=None):
@@ -225,6 +267,14 @@ def _get_csv_buffer(id_segment, schema, id_drug=None, fold=None):
     return csv_buffer
 
 
+def _log_perf(start_date, section):
+    end_date = datetime.now()
+    logging.basicConfig()
+    logger = logging.getLogger("noharm.backend")
+
+    logger.debug(f"PERF {section}: {(end_date-start_date).total_seconds()}")
+
+
 def _compute_outlier(idDrug, drugsItem, poolDict, fold):
     print("Starting...", fold, idDrug)
     poolDict[idDrug] = add_score(drugsItem)

services/prescription_agg_service.py

@@ -30,7 +30,9 @@ def create_agg_prescription_by_prescription(
     if p.idSegment is None:
         return
 
-    if not force and not _has_new_itens(id_prescription):
+    processed_status = _get_processed_status(id_prescription=id_prescription)
+
+    if not force and processed_status == "PROCESSED":
         return
 
     resultPresc, stat = getPrescription(idPrescription=id_prescription)
@@ -103,7 +105,8 @@ def create_agg_prescription_by_prescription(
                         prescription=pAgg, user=prescalc_user, extra={"prescalc": True}
                     )
 
-                if p.status == "s":
+                # if it was checked before this process, keep it
+                if p.status == "s" and processed_status == "NEW_ITENS":
                     p.update = datetime.today()
                     p.user = None
                     p.status = 0
@@ -282,9 +285,11 @@ def get_date_range(p):
     return [start_date + timedelta(days=x) for x in range((end_date - start_date).days)]
 
 
-def _has_new_itens(id_prescription: int):
+def _get_processed_status(id_prescription: int):
     query = (
-        select(PrescriptionDrug.id, func.count(PrescriptionDrugAudit.id))
+        select(
+            PrescriptionDrug.id, func.count(PrescriptionDrugAudit.id).label("p_count")
+        )
         .select_from(PrescriptionDrug)
         .outerjoin(
             PrescriptionDrugAudit,
@@ -296,12 +301,19 @@ def _has_new_itens(id_prescription: int):
         )
         .where(PrescriptionDrug.idPrescription == id_prescription)
         .group_by(PrescriptionDrug.id)
-        .having(func.count(PrescriptionDrugAudit.id) == 0)
     )
 
     results = db.session.execute(query).all()
 
-    if len(results) > 0:
-        return True
+    not_processed_count = 0
+    for r in results:
+        if r.p_count == 0:
+            not_processed_count += 1
+
+    if not_processed_count == len(results):
+        return "NEW_PRESCRIPTION"
+
+    if not_processed_count > 0:
+        return "NEW_ITENS"
 
-    return False
+    return "PROCESSED"

tests/test_alerts.py

@@ -483,7 +483,85 @@ def test_allergy():
 
     assert stats.get("allergy", 0) == 2
 
-    ## _alert_ira    ---- NAO FIZ , DIFICIL -- dose_total[idDrugAgg]
+# simple ira alert test, single condition
+def test_ira():
+    """IRA alerts:  Test for the presence of an alert type equal to 'ira' - Insuficiência Renal Aguda"""
+
+    drugs =[]
+    drugs.append(
+       _get_mock_row(id_prescription_drug=61,dose=10, frequency=10,drug_name = "xxx vancoyyy")
+    )
+
+    exams = {'ckd' : {'value' : 1.}, 'weight': 80 }
+
+    alerts = alert_service.find_alerts(
+        drug_list=drugs,
+        exams=exams,
+        dialisys= None,
+        pregnant=None,
+        lactating=None,
+        schedules_fasting= None,
+    )
+
+    stats = alerts.get("stats")
+    alert1 = alerts.get("alerts").get("61", [])
+
+    assert len(alert1) == 1
+
+    assert alert1[0].get("type", None) == "ira"
+    assert alert1[0].get("level", None) == "high"
+
+    assert stats.get("ira", 0) == 1   
+
+###  TESTS FOR ALERT IRA CONDITIONS - MULTIPLE SCENARIOS
+# input data 
+# dose, ckd, weight, dialysis = test_input
+@pytest.mark.parametrize("test_input,expected_alert", [
+    ((3000, 40, 70, None), True),  # Should trigger alert (baseline case)
+    ((2000, 50, 70, None), False),  # Should not trigger alert (below threshold)
+    ((4000, 30, 60, None), True),  # Should trigger alert (high dose, low CKD)
+    ((3000, 40, 70, 'c'), False),  # Should not trigger alert (patient on dialysis)
+    ((3000, 0, 70, None), False),  # Should not trigger alert (CKD is 0)
+    ((3000, 40, 0, None), False),  # Should not trigger alert (weight is 0)
+    ((1000, 20, 50, None), True),  # Should trigger alert (low dose, very low CKD)
+])
+def test_ira_alert_conditions(test_input, expected_alert):
+    """IRA alerts: Test various conditions for triggering or not triggering the IRA alert"""
+    dose, ckd, weight, dialysis = test_input
+
+    drugs = []
+    drugs.append(
+        _get_mock_row(
+            id_prescription_drug=61,
+            dose=dose,
+            frequency=1,
+            drug_name="Vancomicina"
+        )
+    )
+
+    exams = {'ckd': {'value': ckd}, 'weight': weight}
+
+    alerts = alert_service.find_alerts(
+        drug_list=drugs,
+        exams=exams,
+        dialisys=dialysis,
+        pregnant=None,
+        lactating=None,
+        schedules_fasting=None,
+    )
+
+    alert1 = alerts.get("alerts", {}).get("61", [])
+
+    if expected_alert:
+        assert len(alert1) == 1, f"Expected 1 alert, but got {len(alert1)}"
+        assert alert1[0].get("type") == "ira", f"Expected alert type 'ira', but got {alert1[0].get('type')}"
+        assert alert1[0].get("level") == "high", f"Expected alert level 'high', but got {alert1[0].get('level')}"
+        assert alerts.get("stats", {}).get("ira", 0) == 1, f"Expected 1 IRA alert in stats, but got {alerts.get('stats', {}).get('ira', 0)}"
+        assert "Risco de desenvolvimento de Insuficiência Renal Aguda (IRA)" in alert1[0].get("text", ""), "Expected IRA risk message in alert text"
+    else:
+        assert len(alert1) == 0, f"Expected no alerts, but got {len(alert1)}"
+        assert alerts.get("stats", {}).get("ira", 0) == 0, f"Expected 0 IRA alerts in stats, but got {alerts.get('stats', {}).get('ira', 0)}"
+
 
 
 def test_pregnant():