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identifying-aki-during-hospitalization-based-on-serum-creatinine-trends's Introduction

AKI Calculator

This program analyses a series of creatinine laboratory values and calculates the number of AKI, and their dates. It also has the ability to plot the results. The porgram is meant to assess a patient's baseline creatinine based on values before hospitalization, and the patient's peak creatinine during hospitalization.

Baseline creatinine is calculated based on the creatinines before the admission date. Two variables can be tweaked in the Patient.py file: WINDOW: timeframe in days within which creatinine values are used MEASUREFUNC: is how the baseline creatinine is estimated For example, if baseline creatinine is defined as the median creatinine within 6 months before hospitalization, then WINDOW = 180, and MEASUREFUNC = median.

Peak creatinine is defiend as the highest creatinine during the patient's hospitalization. AKI during hospitalization can be calculated via comparing the baseline creatinine, and the peak creatinine.

How to use the program

The program is written in Python 3. It requires Python 3.x, and the following packages installed: numpy, scipy, matplotlib, and pandas. In order to use the program, you have to include patients creatinine values in the input folder as Labsxx.csv files. If you also want the estimated glomerular filtration rate, then a Demographics.csv file is needed with patients identifiers, age, gender, and race, as these variables are used in the GER equation.

Input

Please see the current files in the input folder as an example of how the files are structured.

Output

Upon running Main.py, the information in the Input folder is proccessed, and the following files are written in the Output folder:

  • AKI.csv: This files contains a list of all patients, their estimated baseline creatinine, and baseline GFR, as well as their peak creatinine levels during their hospitalization.
  • Graphs folder: This folder contains a list of .png names by patients MRNs, and illustrate the patients creatinine trend.

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Contributors

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