A manuscript titled, “Development of a Perioperative Risk Mortality Calculator for Humanitarian Surgical Care,” was published in the World Journal of Surgery by authors Christopher W. Reynolds, Hannah Wild, Yen Sia Low, Saurabh Gombar, and Sherry M. Wren. This was an international collaboration across industry and academia – Dr. Reynolds is affiliated with University of Michigan Medicine, Ann Arbor, MI, Dr. Wild is affiliated with University of Washington, Seattle, WA, and the University of Southampton, U.K., Dr. Gombar and Dr. Low are affiliated with Atropos Health, Palo Alto, CA, and Dr. Wren is affiliated with Stanford University School of Medicine, Stanford CA.
Short Summary:
Risk models to predict perioperative mortality rates (POMR) are critical to surgical quality improvement yet are not widely adapted for use in humanitarian and low‐resource settings (LRS). This study developed a POMR and corresponding nomogram and calculator for use in humanitarian surgical care.
Electronic health record data from a high-income academic medical center from 2015 to 2019 were retrospectively extracted, selecting variables and operations specific to LRS. This development dataset was used to create a logistic regression POMR model, which was then prospectively validated using data from 2022 to 2023 from the same institution.
Key Conclusions:
The study validated a POMR model for use in LRS using eight variables that are readily available in the target environment. This model’s predictors and accompanying clinical tools of a calculator and nomogram make it simultaneously comprehensive and accessible in LRS.
This work proceeds the availability for Members of the Atropos Evidence™ Network to gain immediate access to Vector Databases and Clinical Definitions Library (CDL) via Atropos Health GENEVA OS™. Ready-built for AI classifier Development, the Vector Database and patient timelines are ideal for training classifiers. All data on the Atropos Evidence Network is represented as a Patient Object Vector and all data sets are organized under the same object-oriented schema.
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