DOI: 10.5061/dryad.f4qrfj733
title: Data from: Digital twin mathematical models suggest individualized hemorrhagic shock resuscitation strategies

description: Background: Optimizing resuscitation to reduce inflammation and organ
 dysfunction following human trauma-associated hemorrhagic shock is a major
 clinical hurdle. This is limited by the short duration of pre-clinical
 studies and the sparsity of early data in the clinical setting. Methods:
 We sought to bridge this gap by linking preclinical data in the porcine
 model with clinical data from patients from the Prospective,
 Observational, Multicenter, Major Trauma Transfusion (PROMMTT) study via a
 three-compartment ordinary differential equation model of inflammation and
 coagulation. Results: The model accurately predicts physiologic,
 inflammatory, and laboratory measures in both the porcine model and
 patients, as well as the outcome and time of death in the PROMMTT cohort.
 Model simulation suggests that resuscitation with plasma and red blood
 cells outperformed resuscitation with crystalloid or plasma alone, and
 that earlier plasma resuscitation reduced injury severity and increased
 survival time. Conclusions: This workflow may serve as a translational
 bridge from pre-clinical to clinical studies in trauma-associated
 hemorrhagic shock and other complex disease settings.
description: # Data from: Digital twin mathematical models suggest individualized
 hemorrhagic shock resuscitation strategies This README file was generated
 on 2024-05-18 by Jeremy Cannon. GENERAL INFORMATION 1\. Title of Dataset:
 Data from: Digital twin mathematical models suggest individualized
 hemorrhagic shock resuscitation strategies 2\. Author Information ``` A.
 Principal Investigator Contact Information Name: Jeremy Cannon
 Institution: University of Pennsylvania Address: Philadelphia, PA USA
 Email: jeremy.cannon@pennmedicine.upenn.edu B. Associate or
 Co-investigator Contact Information Name: Yoram Vodovotz Institution:
 University of Pittsburgh Address: Pittsburgh, PA USA Email:
 vodovotzy@upmc.edu ``` 3\. Date of data collection (single date, range,
 approximate date): A) Animal Data: 2009 B) Human Data: 2009-2010 C)
 Modeling Data: 2018-2020 4\. Geographic location of data collection: A)
 Animal Data: Oregon Health and Science University, Portland, OR, USA B)
 Human Data: Brooke Army Medical Center, San Antonio, TX, USA; Medical
 College of Wisconsin, Milwaukee, WI, USA; Oregon Health and Science
 University, Portland, OR, USA; University of California, San Francisco,
 San Francisco, CA, USA; University of Cincinnati, Cincinnati, OH, USA;
 University of Pittsburgh Medical Center, Pittsburgh, PA, USA; University
 of Texas Health Science Center at Houston, Houston, TX, USA; University of
 Texas Health Science Center at San Antonio, San Antonio, TX, USA;
 University of Texas Southwestern Medical Center, Dallas, TX, USA;
 University of Washington, Seattle, WA, USA C) Modeling Data: Immunetrics,
 Pittsburgh, PA, USA 5\. Information about funding sources that supported
 the collection of the data: A) Animal Data: US Army Medical Research
 Acquisition Activity (Award: W81XWH-04-1-0104) B) Human Data: US Army
 Medical Research and Materiel Command (Subcontract: W81XWH-08-C-0712) and
 National Institutes of Health (UL1 RR024148) C) Modeling Data: US Army
 Medical Department (AMEDD) Advanced Medical Technology Initiative (AAMTI)
 SHARING/ACCESS INFORMATION 1\. Licenses/restrictions placed on the data:
 Not in the public domain. 2\. Links to publications that cite or use the
 data: A) Animal Data: Spoerke, N., et al. Lyophilized plasma for
 resuscitation in a swine model of severe injury. Archives of Surgery.
 144;829-834 (2009). B) Human Data: Holcomb, J.B., et al.The Prospective,
 Observational, Multicenter, Major Trauma Transfusion (PROMMTT) study:
 Comparative effectiveness of a time-varying treatment with competing
 risks. JAMA Surgery. 148;127-136 (2013). 3\. Links to other publicly
 accessible locations of the data: None 4\. Links/relationships to
 ancillary data sets: None 5\. Was data derived from another source? No A.
 If yes, list source(s): NA 6\. Recommended citation for this dataset:
 Cannon, J. W., et al. Data from: Digital twin mathematical models suggest
 individualized hemorrhagic shock resuscitation strategies. Dryad Digital
 Repository.
 [https://doi.org/10.5061/dryad.f4qrfj733](https://doi.org/10.5061/dryad.f4qrfj733) DATA & FILE OVERVIEW 1\. File List: A) Fig_3.csv B) Fig_4.csv C) Fig_5.csv D) Supp_Fig_3.csv E) Supp_Fig_4.csv F) Supp_Fig_5.csv G) Supp_Fig_7.csv H) Time_death.csv 2\. Relationship between files, if important: None 3\. Additional related data collected that was not included in the current data package: None 4\. Are there multiple versions of the dataset? No ``` A. If yes, name of file(s) that was updated: NA i. Why was the file updated? NA ii. When was the file updated? NA ``` \######################################################################### DATA-SPECIFIC INFORMATION FOR: Fig_3.csv Model fit verification for porcine subjects. Comparison of different resuscitation strategies in an animal model (n=2 in each group). 1\. Number of variables: 4 2\. Number of cases/rows: 24,408 3\. Variable List: ``` * uid: animal subject number * parameter: study variables (*_real denotes measured values; all others represent model outputs) * time: in minutes relative to t=0 (negative values represent times before t=0) * value: parameter value (units vary by parameter) ``` 4\. Missing data codes: NA 5\. Specialized formats or other abbreviations used: None \######################################################################### DATA-SPECIFIC INFORMATION FOR: Fig_4.csv Model validation in humans. Comparison of survivors (n=10) and non-survivors (n=6) using models fit to human data from the PROMMTT Study for blood pressure and oxygen saturation (O2Sat). All other parameters are derived values. 1\. Number of variables: 4 2\. Number of cases/rows: 118,854 3\. Variable List: ``` * uid: de-identified patient number * parameter: study variables (*_real denotes measured values; all others represent model outputs) * time: in minutes relative to t=0 (negative values represent times before t=0) * value: parameter value (units vary by parameter ``` 4\. Missing data codes: NA 5\. Specialized formats or other abbreviations used: None \######################################################################### DATA-SPECIFIC INFORMATION FOR: Fig_5.csv In silico experimental infusions in humans. Treatments include baseline representing the model predictions for survivors (n=5 patients) and non-survivors (n=5) without modification to the original resuscitation algorithm received during the original data collection. In silico experiments represent predicted outcomes with variations in the resuscitation approach including pre-hospital plasma given in addition to baseline resuscitation (Pre-Hosp Plas) in-hospital resuscitation started 30 minutes earlier than baseline (Early t-30); in-hospital resuscitation started 10 minutes earlier than baseline (Early t-10); in-hospital resuscitation delayed by 10 minutes from baseline (Late t-10); and in-hospital resuscitation delayed by 30 minutes from baseline (Late t-30). 1\. Number of variables: 6 2\. Number of cases/rows: 135,656 3\. Variable List: ``` * uid: de-identified patient number * group: in silico experiment including baseline comparison and five additional variations as described above * outcome: survival (s) or non-survival (ns) * time: in minutes relative to t=0 (negative values represent times before t=0) * parameter: study variables * value: parameter value (units vary by parameter ``` 4\. Missing data codes: None 5\. Specialized formats or other abbreviations used: None \######################################################################### DATA-SPECIFIC INFORMATION FOR: Supp_Fig_3.csv Model training using animal subjects undergoing alternative resuscitation strategies: n=6 animals resuscitated with plasma only and n=6 animals resuscitated with plasma and packed red blood cells. 1\. Number of variables: 4 2\. Number of cases/rows: 73,657 3\. Variable List: ``` * uid: animal subject number * parameter: study variables (*_real denotes measured values; all others represent model outputs) * time: in minutes relative to t=0 (negative values represent times before t=0) * value: parameter value (units vary by parameter) ``` 4\. Missing data codes: NA 5\. Specialized formats or other abbreviations used: None \######################################################################### DATA-SPECIFIC INFORMATION FOR: Supp_Fig_4.csv Model training in n=35 patients from the PROMMTT study including n=20 survivors and n=15 non-survivors. 1\. Number of variables: 4 2\. Number of cases/rows: 254,881 3\. Variable List: ``` * uid: de-identified patient number * parameter: study variables (*_real denotes measured values; all others represent model outputs) * time: in minutes relative to t=0 (negative values represent times before t=0) * value: parameter value (units vary by parameter) ``` 4\. Missing data codes: NA 5\. Specialized formats or other abbreviations used: None \######################################################################### DATA-SPECIFIC INFORMATION FOR: Supp_Fig_5.csv Model verification in n=17 patients from the PROMMTT study including n=9 survivors and n=8 non-survivors. 1\. Number of variables: 4 2\. Number of cases/rows: 102,592 3\. Variable List: ``` * uid: de-identified patient number * parameter: study variables (*_real denotes measured values; all others represent model outputs) * time: in minutes relative to t=0 (negative values represent times before t=0) * value: parameter value (units vary by parameter) ``` 4\. Missing data codes: NA 5\. Specialized formats or other abbreviations used: None \######################################################################### DATA-SPECIFIC INFORMATION FOR: Supp_Fig_7.csv In silico trauma simulations for seven virtual animal populations (100 animals in each group). 1\. Number of variables: 5 2\. Number of cases/rows: 12,600 3\. Variable List: ``` * uid: virtual animal number * group: In silico simulation group * parameter: study variables * value: parameter value (units vary by parameter) ``` 4\. Missing data codes: None 5\. Specialized formats or other abbreviations used: None \######################################################################### DATA-SPECIFIC INFORMATION FOR: Time_Death.csv Time of death in non-survivors used for model fitting (Suppl Fig 4), verification (Suppl Fig 5), validation (Fig 4), and in silico experiments (Fig 5). 1\. Number of variables: 3 2\. Number of cases/rows: 53 3\. Variable List: ``` * uid * group (fitting, verification, validation, exp_* where * represents the in silico experimental group) * time_death (from t=0 in minutes) ``` 4\. Missing data codes: None 5\. Specialized formats or other abbreviations used: None