.env

@@ -1,3 +1,6 @@
-FHIR_USERNAME=
-FHIR_PASSWORD=
+FHIR_SERVER_BASE_URL=http://pwebmedcit.services.brown.edu:9091/fhir
+FHIR_USERNAME=bcbifhir
+FHIR_PASSWORD=fancy-company-attraction-p3rson
 FHIR_PORT=5000
+R_HOME=/Library/Frameworks/R.framework/Resources  # Adjust this path based on your findings
+R_USER=/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library  # Adjust this path based on your R version and user library path

README.md

@@ -1,51 +1,62 @@
-# fhir-condition-finder
+# ASCVD Risk Calculator
 
-This is a FHIR web application written in Python and using Flask as the backend. It can only be used for synthea datasets.
+This ASCVD Risk calculator is used to study the risk prediction for cardiovascular disease (CVD).
 
-Following are the server port number and their respective datasets
+This calculator uses the Pooled Cohort risk prediction equations to predict 10-year atherosclerotic cardiovascular disease risk. More information about the predictor equation can be found here https://github.com/bcjaeger/PooledCohort/tree/master
+
+# Steps to run the ASCVD Risk Calculator
+
+## 1. Check if R and python are installed where you are running this app.
 
 ```
-9090 -> synthea10 (demo dataset)
-9091 -> synthea_ri_adult
-9092 -> synthea_ri_peds
+python3 --version
+R --version
 ```
 
-## 1. Dependencies
-This app depends on Python 3 and a few Python packages outlined in the `requirements.txt` file. 
-
 ## 2. Before running the app
 
-Change these parameters in the .env file
+Change these parameters in the .env file. Use the port number assigned to you to run the app for FHIR_PORT.
 
 ```
+FHIR_SERVER_BASE_URL= http://pwebmedcit.services.brown.edu:????/fhir
 FHIR_USERNAME = ???
 FHIR_PASSWORD = ???
-FHIR_PORT=5000
+FHIR_PORT=????
+R_HOME=???
+R_USER=????
 ```
 
-and change the port number according to the dataset in the app.py file 
-FHIR_SERVER_BASE_URL= "http://pwebmedcit.services.brown.edu:????/fhir"
-
-## 3. Running the App
-
-We begin by creating a Python virtual environment using the `venv` module. This is done by running the command below from the "root" of this repo. 
+Start R and run the R.home() and .libPaths() commands to get the directory names and update them in .env file
 
 ```
-python3 -m venv venv                 # create a virtual environment called venv
-
-source venv/bin/activate             # activate our virtual environment
-
-pip3 install -r requirements.txt     # install all our dependencies into the virtual environment
+> R.home()
+[1] "/Library/Frameworks/R.framework/Resources"
+> .libPaths()
+[1] "/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library"
 ```
 
+## 3. Clone the repo
+```
+git clone https://github.com/bcbi/ASCVD-Risk-Calculator.git
 
-After the above steps, we should be able to launch our app using the following command.
+cd ASCVD-Risk-Calculator
+```
+## 4. Run the setup script
+```
+./setup_environment.sh
+```
 
+## 5. Activate the virtual environment
 ```
-python3 src/app.py
+source venv/bin/activate
 ```
 
+## 6. Run the flask app
+```
+python src/app.py
+```
 
-This will start the app on port 5000. You can open your preferred browser and see the app running on `http://localhost:5000`
+This will start the app on port "FHIR_PORT". You can open your preferred browser and see the app running on `http://localhost:FHIR_PORT` replace the FHIR_PORT with the actual port number assigned to you. 
+The exact URL to the app can also be found on the terminal output after running the app.
 
 

requirements.txt

@@ -13,3 +13,4 @@ requests==2.32.2
 urllib3==2.0.5
 Werkzeug==2.3.7
 zipp==3.17.0
+rpy2==3.4.5

setup_environment.sh

@@ -0,0 +1,11 @@
+#!/bin/bash
+
+python3 -m venv venv
+source venv/bin/activate
+
+# install python packages
+pip install -r requirements.txt
+
+# install R pacakges
+Rscript -e "install.packages('devtools', repos='http://cran.rstudio.com/')"
+Rscript -e "devtools::install_github('bcjaeger/PooledCohort')"

src/app.py

@@ -1,67 +1,167 @@
-import requests
 import os
-from flask import Flask, request, render_template
-from dotenv import load_dotenv
 
+
+
+import requests
+import rpy2.robjects as ro
+from rpy2.robjects.packages import importr
+from rpy2.robjects.vectors import FloatVector, StrVector
+from flask import Flask, request, render_template, redirect, url_for
+from dotenv import load_dotenv
+from datetime import datetime
 
 app = Flask(__name__)
 
-FHIR_SERVER_BASE_URL="http://pwebmedcit.services.brown.edu:9091/fhir"
+# Import the PooledCohort package in R
+pooled_cohort = importr("PooledCohort")
 
+# Load environment variables
 load_dotenv()
 
+FHIR_SERVER_BASE_URL = os.getenv("FHIR_SERVER_BASE_URL")
 username = os.getenv("FHIR_USERNAME")
 password = os.getenv("FHIR_PASSWORD")
 
-
-def request_patient(patient_id, credentials):
-
-    req = requests.get(FHIR_SERVER_BASE_URL + "/Patient/" + str(patient_id), auth = credentials)
-
-    print(f"Requests status: {req.status_code}")
-
-    response = req.json()
-    print(response.keys())
-
-    return response
-
-def search_patients_by_condition(condition_id, credentials):
-    # Search for patients with a specific condition
-    search_url = f"{FHIR_SERVER_BASE_URL}/Condition?code={condition_id}"
-    req = requests.get(search_url, auth=credentials)
-
-    if req.status_code == 200:
-        conditions = req.json()['entry']
-        patient_ids = [entry['resource']['subject']['reference'].split('/')[-1] for entry in conditions]
-        patients = [request_patient(patient_id, credentials) for patient_id in patient_ids]
-         # Convert patient details into set of tuples to ensure uniqueness
-        unique_patients = set((patient['id'], patient['name'][0]['given'][0], patient['name'][0]['family'], patient['gender'], patient['birthDate']) for patient in patients)
-
-        total_patients = len(unique_patients)
-        return {'unique_patients': unique_patients, 'total_patients': total_patients}
+# Set environment variables for R from .env
+os.environ['R_HOME'] = os.getenv('R_HOME')
+os.environ['R_USER'] = os.getenv('R_USER') 
+
+observation_codes = {
+    "Systolic Blood Pressure": "8480-6",
+    "Diastolic Blood Pressure": "8462-4",
+    "Total Cholesterol": "2093-3",
+    "HDL Cholesterol": "2085-9",
+    "LDL Cholesterol": "18262-6"
+}
+
+race_mapping = {
+    "American Indian or Alaska Native": "white",
+    "Asian": "white",
+    "Black or African American": "black",
+    "Native Hawaiian or Other Pacific Islander": "white",
+    "White": "white"
+}
+
+def get_observation_value(entry):
+    if 'valueQuantity' in entry['resource']:
+        return entry['resource']['valueQuantity']['value']
+    elif 'valueString' in entry['resource']:
+        return entry['resource']['valueString']
     else:
-        return None
-
-
-
-
+        return 'Not Found'
+
+def get_latest_observation(entries):
+    if not entries:
+        return 'Not Found'
+    latest_entry = max(entries, key=lambda e: e['resource']['effectiveDateTime'])
+    return get_observation_value(latest_entry)
+
+def calculate_age(birth_date):
+    birth_date = datetime.strptime(birth_date, '%Y-%m-%d')
+    today = datetime.today()
+    return today.year - birth_date.year - ((today.month, today.day) < (birth_date.month, birth_date.day))
+
+def get_patient_demographics(patient_id, credentials):
+    response = requests.get(FHIR_SERVER_BASE_URL + f"/Patient/{patient_id}", auth=credentials)
+    if response.status_code == 200:
+        patient = response.json()
+        birth_date = patient['birthDate']
+        age = calculate_age(birth_date)
+        sex = patient['gender']
+        race = 'Not Found'
+        for extension in patient.get('extension', []):
+            if extension['url'] == 'http://hl7.org/fhir/us/core/StructureDefinition/us-core-race':
+                for ext in extension.get('extension', []):
+                    if ext['url'] == 'ombCategory':
+                        race = race_mapping.get(ext['valueCoding']['display'], 'white')
+                        break
+        return {'age': age, 'sex': sex, 'race': race}
+    else:
+        return {'age': 'Not Found', 'sex': 'Not Found', 'race': 'Not Found'}
+
+def get_patient_observations(patient_id, credentials):
+    observations = {}
+    demographics = get_patient_demographics(patient_id, credentials)
+    for obs_name, code in observation_codes.items():
+        response = requests.get(FHIR_SERVER_BASE_URL + f"/Observation?patient={patient_id}&code={code}", auth=credentials)
+        if response.status_code == 200:
+            data = response.json()
+            if 'entry' in data and data['entry']:
+                observations[obs_name] = get_latest_observation(data['entry'])
+            else:
+                observations[obs_name] = 'Not Found'
+        else:
+            observations[obs_name] = 'Not Found'
+    return observations, demographics
 
 @app.route('/', methods=['GET', 'POST'])
 def index():
-    result = None
-    credentials = (username, password)
+    observations = None
+    demographics = None
+    ascvd_risk = None
 
-    if request.method == 'POST':
-        try:
-            condition_id = request.form['condition_id']
-            result = search_patients_by_condition(condition_id, credentials)
-        except ValueError:
-            result = 'Invalid input. Please enter a valid condition ID.'
-
-    return render_template('index.html', result=result)
+    return render_template('index.html', observations=observations, demographics=demographics, ascvd_risk=ascvd_risk)
 
+@app.route('/fetch_patient_data', methods=['POST'])
+def fetch_patient_data():
+    patient_id = request.form['patient_id']
+    credentials = (username, password)
+    observations, demographics = get_patient_observations(patient_id, credentials)
+    return render_template('index.html', observations=observations, demographics=demographics, patient_id=patient_id)
+
+@app.route('/calculate_risk', methods=['POST'])
+def calculate_risk():
+    patient_id = request.form.get('patient_id')
+    age = int(request.form['age'])
+    sex = request.form['sex']
+    race = request.form['race']
+    total_cholesterol = float(request.form['total_cholesterol'])
+    hdl_cholesterol = float(request.form['hdl_cholesterol'])
+    systolic_bp = float(request.form['systolic_blood_pressure'])
+    diabetes = request.form['diabetes']
+    smoker = request.form['smoker']
+    hypertension = request.form['hypertension']
+
+    # Convert sex and race to R compatible formats
+    sex_r = StrVector([sex])
+    race_r = StrVector([race_mapping.get(race, 'white')])
+
+    # Convert other inputs to R compatible formats
+    age_r = FloatVector([age])
+    total_cholesterol_r = FloatVector([total_cholesterol])
+    hdl_cholesterol_r = FloatVector([hdl_cholesterol])
+    systolic_bp_r = FloatVector([systolic_bp])
+    diabetes_r = StrVector(['yes' if diabetes == 'yes' else 'no'])
+    smoker_r = StrVector(['yes' if smoker == 'yes' else 'no'])
+    hypertension_r = StrVector(['yes' if hypertension == 'yes' else 'no'])
+
+    # Call the ASCVD risk calculation function from PooledCohort
+    ascvd_risk_r = pooled_cohort.predict_10yr_ascvd_risk(
+        sex=sex_r,
+        race=race_r,
+        age_years=age_r,
+        chol_total_mgdl=total_cholesterol_r,
+        chol_hdl_mgdl=hdl_cholesterol_r,
+        bp_sys_mmhg=systolic_bp_r,
+        bp_meds=hypertension_r,
+        smoke_current=smoker_r,
+        diabetes=diabetes_r
+    )
+
+    # Convert the result back to Python
+    ascvd_risk = list(ascvd_risk_r)[0]*100
+
+    demographics = {'age': age, 'sex': sex, 'race': race}
+    observations = {
+        'Total Cholesterol': total_cholesterol,
+        'HDL Cholesterol': hdl_cholesterol,
+        'Systolic Blood Pressure': systolic_bp,
+        'Diastolic Blood Pressure': request.form['diastolic_blood_pressure'] if 'diastolic_blood_pressure' in request.form else 'Not Found'
+    }
+
+    return render_template('index.html', ascvd_risk=ascvd_risk, demographics=demographics, observations=observations, patient_id=patient_id)
 
 if __name__ == '__main__':
-    port_str = os.environ['FHIR_PORT']
+    port_str = os.getenv('FHIR_PORT', '5000')
     port_int = int(port_str)
-    app.run(debug=True, port=port_int)
+    app.run(debug=True, port=port_int)