{ "cells": [ { "cell_type": "markdown", "id": "9c3642d7", "metadata": {}, "source": [ "# Diagnostic clairance et DFG\n", "\n", "Analyse du patient :\n", "- Créatininémie : 18 mg/L de plasma\n", "- Créatininurie : 1,5 g/L d’urine \n", "- Volume urinaire sur 24 heures : 1,6 L\n", "\n", "Pour ces analyses, calculer la clairance, la DFG et l’estimation de la DFG par la seule mesure de la créatininémie. Conclure." ] }, { "cell_type": "code", "execution_count": 2, "id": "b9f63c32", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "La clairance est de : 37.03703703703704 mL/min\n", "1.6253865741715157\n", "Le débit de filtration glomulaire est de : 39.42082154009031 mL/(min*1,73m2\n", "159.1230551626591\n", "43.3875\n", "UV analysé 8.486562942008486 mmol/jour\n", "UV attendu 8.6775 mmol/jour\n", "DFG_Cockcroft est de : 39.592000000000006 mL/(min*1,73m2)\n", "DFG_MDRD est de : 31.201196208972213 mL/(min*1,73m2)\n", "DFG_CKD est de : 34.64122124846187 mL/(min*1,73m2)\n" ] } ], "source": [ "import numpy as np\n", "creatininémie=18 #mg/L de plasma\n", "creatininurie=1.2 #g/L d urine\n", "volume_urinaire_en_24h=0.8 #L\n", "\n", "clairance=creatininurie*volume_urinaire_en_24h*1000*1000/(creatininémie*1440)\n", "print ('La clairance est de :', clairance, ' mL/min')\n", "\n", "taille=160 #cm\n", "poids=60 #kg\n", "SC = 0.007184*taille**0.725*poids**0.4255\n", "\n", "print(SC)\n", "\n", "DFG= clairance*1.73/SC\n", "print ('Le débit de filtration glomulaire est de :', DFG, ' mL/(min*1,73m2')\n", "\n", "#methode simlifiée CKD-EPI\n", "M=113.12 #g/mol\n", "creat=creatininémie*1000/M #microM\n", "print(creat)\n", "femme=1\n", "age=40 #année\n", "poids=60 #kg\n", "\n", "massemaigre=1.07*poids-148*poids*poids/(taille*taille)\n", "\n", "print(massemaigre)\n", "\n", "print ('UV analysé',creatininurie*volume_urinaire_en_24h*1000/M, 'mmol/jour')\n", "print ('UV attendu',massemaigre*0.2, 'mmol/jour')\n", "\n", "fcock=np.where(femme==1,0.84,1)\n", "fmdrd=np.where(femme==1,0.742,1)\n", "k=np.where(femme==1,0.7,0.9)\n", "alpha=np.where(femme==1,-0.329,-0.411)\n", "comp=np.where(femme==1,1.018,1)\n", "\n", "DFG_cockcroft=1.25*poids*(140-age)*fcock/creat\n", "DFG_MDRD=175*(creat*0.0113)**-1.154*age**-0.203*fmdrd\n", "DFG_CKD=141*(np.min([creat*0.0113/k,1])**alpha)*(np.max([creat*0.0113/k,1])**-1.209)*(0.993**age)*comp\n", "\n", "print ('DFG_Cockcroft est de :', DFG_cockcroft, ' mL/(min*1,73m2)')\n", "print ('DFG_MDRD est de :', DFG_MDRD, ' mL/(min*1,73m2)')\n", "print ('DFG_CKD est de :', DFG_CKD, ' mL/(min*1,73m2)')\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.12" } }, "nbformat": 4, "nbformat_minor": 5 }