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Code for paper "Estimating Trustworthy Treatment Effects for Antibiotic Stewardship in Sepsis"

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T4

Introduction

Code for paper "Estimating Trustworthy Treatment Effects for Antibiotic Stewardship in Sepsis"

In this paper, we propose a novel method to estimate Trustworthy Treatment effects for Time-to-Treatment antibiotic stewardship in sepsis (T4).

We demonstrate that T4 can identify effective treatment timing with estimated trustworthy ITEs for antibiotic stewardship on two real-world datasets (AmsterdamUMCdb and MIMIC-III).

Requirement

Ubuntu16.04, python 3.6

Install pytorch 1.4

Data

Real-world data

Studied variables

The list of variables in MIMIC-III and AdmsterdamDB. There are 22 temporal covariates and 4 demographics andstatic variables. PT: Prothrombin Time; BUN: Blood Urea Nitrogen; WBC: White Blood Cells count.

Category MIMIC-III AmsterdamDB
Mean Std. Mean Std.
Demographics Age 65.55 16.44 61.30 17.90
Gender 43% Female - 42% Female -
Weight 81.67 25.50 79.83 13.61
Height 169.30 11.17 175.15 8.44
Lab test Anion gap 13.35 3.80 8.70 4.62
Bicarbonate 25.65 5.27 25.63 6.35
Bilirubin 3.36 6.41 3.15 6.85
Creatinine 1.50 1.46 1.28 1.03
Chloride 104.00 6.60 108.60 46.31
Glucose 134.00 66.83 133.9 45.74
Hematocrit 29.96 5.13 38.98 1.67
Hemoglobin 10.09 1.79 12.57 1.64
Lactate 2.44 2.14 2.40 2.95
Platelet 235.05 155.28 220.82 171.65
Potassium 4.08 0.63 5.58 602.56
PT 17.76 8.95 1.59 10.12
Sodium 138.84 5.32 140.88 43.45
BUN 29.85 23.54 14.15 9.80
WBC 11.23 7.64 14.56 11.80
Vital signs Heart Rate 87.81 18.30 92.70 23.65
SysBP 120.92 23.28 126.05 139.59
DiasBP 61.41 14.55 60.77 31.11
Meanbp 78.70 16.88 82.12 47.34
Respratory 20.48 5.90 21.99 7.71
Temperature 36.96 0.85 36.73 21.14
SpO2 97.00 3.27 96.09 7.43

Studied antibiotics

The list of antibiotics in MIMIC-III Dataset. There are 18 kinds of antibiotics in total.

Category Name
Antibiotic Cefazolin, Cefepime, Ceftazidime, Ciprofloxacin, Clindamycin, Erythromycin, Gentamicin, Levofloxacin, Metronidazole, Moxifloxacin, Piperacillin, Rifampin, Tobramycin, Vancomycin, Amikacin, Ampicillin, Azithromycin, Aztreonam

Synthetic data

Fully synthetic data

mkdir -p data
python simulation/gen_synthetic.py

Semi-synthetic data based on MIMIC-III

# put preprocessed MIMIC-III data into folder "data/"
python simulation/gen_synthetic_mimic.py

Train T4

Running example

bash run.sh 3 # number of follow-up steps

Results

Mortality rate comparison of two datasets. The results show that the mortality rate of patients who receive the antibiotics at the time werecommend is significantly lower than the patients who donot, indicating that our model offers effective timings of antibiotic administration that help to reduce the mortality rate.

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Code for paper "Estimating Trustworthy Treatment Effects for Antibiotic Stewardship in Sepsis"

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  • Python 97.5%
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