External Validation of a Smartphone App Model to Predict the Need for Massive Transfusion Using Five Different Definitions

Introduction Previously, a model to predict massive transfusion protocol (activation) was derived using a single-institution dataset. The PROMMTT database was used to externally validate this model’s ability to predict both massive transfusion protocol (MTP) activation and massive transfusion (MT) administration using multiple MT definitions. Methods The app model was used to calculate the predicted probability of massive transfusion protocol activation or massive transfusion delivery. The five definitions of MT used were: 1) 10 units packed red blood cells (PRBCs) in 24 hours; 2) Resuscitation Intensity score ≥ 4; 3) Critical Administration Threshold; 4) 4 units PRBCs in 4 hours; and 5) 6 units PRBCs in 6 hours. Receiver operating curves were plotted to compare the predicted probability of MT with observed outcomes. Results Of 1245 patients in the dataset, 297 (24%) met definition 1, 570 (47%) met definition 2, 364 (33%) met definition 3, 599 met definition 4 (49.1%), and 395 met definition 5 (32.4%). Regardless of the outcome (MTP activation or MT administration), the predictive ability of the app model was consistent: when predicting activation of the MTP, the area under the curve (AUC) for the model was 0.694 and when predicting MT administration the AUC ranged from 0.695 – 0.711. Conclusion Regardless of the definition of massive transfusion used, the app model demonstrates moderate ability to predict the need for massive transfusion in an external, homogenous population. Importantly, the app allows the model to be iteratively re-calibrated (“machine learning”) and thus could improve its predictive capability as additional data are accrued. Level of Evidence III Study Type Diagnostic test study Funding/Support: This work was supported by subcontract W81XWH-08-C-0712 from the US Army Medical Research and Materiel Command. Infrastructure for the Data Coordinating Center was supported by Clinical and Translational Science Awards funds of grant UL1 RR024148 from the National Institutes of Health. Role of the Sponsors: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. Disclaimer: The views and opinions expressed in this article are those of the authors and do not reflect the official policy or position of the Army Medical Department, the Department of the Army, the Department of Defense, or the US government. © 2017 Lippincott Williams & Wilkins, Inc.

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