G. Angelotti, L. Azzimonti, I. Bose, A. Colombo, T. Crupi, F. Faraci, M. Lubian, G. Maroni, A. Pagnamenta, L. Ruinelli, N. Stomeo, R. Švihrová

1. Access to AmsterdamUMCdb. Learn more here.
2. Project ID of a Google Project, make sure to have the necessary IAM permissions to run queries on Big Query.
3. Ensure that the Google SDK is properly installed in your environment with proper authentication.

Important Note: The google account enabled to access the AmsterdamUMCdb must the be same as the one associated with the Google Project.

Run:
pip install "git+https://github.com/jhn-nt/paten.git"

Afterwards run:
python3 -m paten.install

To investigate the dataset:

from paten.etl import dataset, intervention_proxy__uniform,intervention_proxy__capped_cumulative, intervention_proxy__duty_cycle

# estimating proxies of pronation as total cumulative pronations hours/ IMV duration.
df=dataset(intervention_proxy__uniform)

# estimating proxies of pronation as cumulative pronation hours until 24 hours.
df=dataset(intervention_proxy__capped_cumulative)

# estimating proxies of pronation hours as a duty cycle over a pseudo 24 hours cycle.
df=dataset(intervention_proxy__duty_cycle)

To replicate the entire study:

python3 -m paten.pjob --dir savedir --seed 0 

This will take several ours.

Our code was tested on a Linux environment only, milage may vary.