International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality
Authors: Weber Griffin M. , Hong Chuan , Xia Zongqi , Palmer Nathan P. , Avillach Paul , L’Yi Sehi , Keller Mark S. , Murphy Shawn N. , Gutiérrez-Sacristán Alba , Bonzel Clara-Lea , Serret-Larmande Arnaud , Neuraz Antoine , Omenn Gilbert S. , Visweswaran Shyam , Klann Jeffrey G. , South Andrew M. , Loh Ne Hooi Will , Cannataro Mario , Beaulieu-Jones Brett K. , Bellazzi Riccardo , Agapito Giuseppe , Alessiani Mario , Aronow Bruce J. , Bell Douglas S. , Benoit Vincent , Bourgeois Florence T. , Chiovato Luca , Cho Kelly , Dagliati Arianna , DuVall Scott L. , Barrio Noelia García , Hanauer David A. , Ho Yuk-Lam , Holmes John H. , Issitt Richard W. , Liu Molei , Luo Yuan , Lynch Kristine E. , Maidlow Sarah E. , Malovini Alberto , Mandl Kenneth D. , Mao Chengsheng , Matheny Michael E. , Moore Jason H. , Morris Jeffrey S. , Morris Michele , Mowery Danielle L. , Ngiam Kee Yuan , Patel Lav P. , Pedrera-Jimenez Miguel , Ramoni Rachel B. , Schriver Emily R. , Schubert Petra , Balazote Pablo Serrano , Spiridou Anastasia , Tan Amelia L. M. , Tan Byorn W. L. , Tibollo Valentina , Torti Carlo , Trecarichi Enrico M. , Wang Xuan ,   The Consortium for Clinical Characterization of COVID-19 by EHR (4CE), Aaron James R. , Albayrak Adem , Albi Giuseppe , Alloni Anna , Amendola Danilo F. , Angoulvant François , Anthony Li L. L. J. , Ashraf Fatima , Atz Andrew , Avillach Paul , Azevedo Paula S. , Balshi James , Beaulieu-Jones Brett K. , Bellasi Antonio , Benoit Vincent , Beraghi Michele , Bernal-Sobrino José Luis , Bernaux Mélodie , Bey Romain , Bhatnagar Surbhi , Blanco-Martínez Alvar , Boeker Martin , Booth John , Bosari Silvano , Bradford Robert L. , Brat Gabriel A. , Bréant Stéphane , Brown Nicholas W. , Bruno Raffaele , Bryant William A. , Bucalo Mauro , Bucholz Emily , Burgun Anita , Cai Tianxi , Carmona Aldo , Caucheteux Charlotte , Champ Julien , Chen Krista Y. , Chen Jin , Chiudinelli Lorenzo , Cho Kelly , Cimino James J. , Colicchio Tiago K. , Cormont Sylvie , Cossin Sébastien , Craig Jean B. , Cruz-Bermúdez Juan Luis , Cruz-Rojo Jaime , Daniar Mohamad , Daniel Christel , Das Priyam , Devkota Batsal , Dionne Audrey , Duan Rui , Dubiel Julien , Esteve Loic , Estiri Hossein , Fan Shirley , Follett Robert W. , Ganslandt Thomas , García-Barrio Noelia , Garmire Lana X. , Gehlenborg Nils , Getzen Emily J. , Geva Alon , Gradinger Tobias , Gramfort Alexandre , Griffier Romain , Griffon Nicolas , Grisel Olivier , Gutiérrez-Sacristán Alba , Han Larry , Hanauer David A. , Haverkamp Christian , Hazard Derek Y. , He Bing , Henderson Darren W. , Hilka Martin , Huling Kenneth M. , Hutch Meghan R. , Issitt Richard W. , Jannot Anne Sophie , Jouhet Vianney , Kavuluru Ramakanth , Kennedy Chris J. , Kernan Kate F. , Key Daniel A. , Kirchoff Katie , Klann Jeffrey G. , Kohane Isaac S. , Krantz Ian D. , Kraska Detlef , Krishnamurthy Ashok K. , Le Trang T. , Leblanc Judith , Lemaitre Guillaume , Lenert Leslie , Leprovost Damien , Liu Molei , Long Qi , Lozano-Zahonero Sara , Mahmood Sadiqa , Maidlow Sarah E. , Makoudjou Adeline , Maram Anupama , Martel Patricia , Martins Marcelo R. , Marwaha Jayson S. , Masino Aaron J. , Mazzitelli Maria , Mensch Arthur , Milano Marianna , Minicucci Marcos F. , Moal Bertrand , Ahooyi Taha Mohseni , Moore Jason H. , Moraleda Cinta , Morris Jeffrey S. , Moshal Karyn L. , Mousavi Sajad , Murad Douglas A. , Murphy Shawn N. , Naughton Thomas P. , Neto Carlos Tadeu Breda , Newburger Jane , Ngiam Kee Yuan , Njoroge Wanjiku F. M. , Norman James B. , Obeid Jihad , Okoshi Marina P. , Olson Karen L. , Omenn Gilbert S. , Orlova Nina , Ostasiewski Brian D. , Palmer Nathan P. , Paris Nicolas , Patel Lav P. , Pedrera-Jiménez Miguel , Pfaff Ashley C. , Pfaff Emily R. , Pillion Danielle , Pizzimenti Sara , Prokosch Hans U. , Prudente Robson A. , Prunotto Andrea , Quirós-González Víctor , Ramoni Rachel B. , Raskin Maryna , Rieg Siegbert , Roig-Domínguez Gustavo , Rojo Pablo , Rubio-Mayo Paula , Sacchi Paolo , Sáez Carlos , Salamanca Elisa , Samayamuthu Malarkodi Jebathilagam , Sanchez-Pinto L. Nelson , Sandrin Arnaud , Santhanam Nandhini , Santos Janaina C. C. , Sanz Vidorreta Fernando J. , Savino Maria , Schuettler Juergen , Scudeller Luigia , Sebire Neil J. , Serrano-Balazote Pablo , Serre Patricia , Serret-Larmande Arnaud , Shah Mohsin , Abad Zahra Shakeri Hossein , Silvio Domenick , Sliz Piotr , Son Jiyeon , Sonday Charles , South Andrew M. , Sperotto Francesca , Strasser Zachary H. , Tan Amelia L. M. , Tan Bryce W. Q. , Tanni Suzana E. , Taylor Deanne M. , Terriza-Torres Ana I. , Tippmann Patric , Toh Emma M. S. , Tseng Yi-Ju , Vallejos Andrew K. , Varoquaux Gael , Vella Margaret E. , Verdy Guillaume , Vie Jill-Jênn , Visweswaran Shyam , Vitacca Michele , Wagholikar Kavishwar B. , Waitman Lemuel R. , Wassermann Demian , Weber Griffin M. , Wolkewitz Martin , Wong Scott , Xia Zongqi , Xiong Xin , Ye Ye , Yehya Nadir , Yuan William , Zambelli Alberto , Zhang Harrison G. , Zöller Daniela , Zuccaro Valentina , Zucco Chiara , Kohane Isaac S. , Cai Tianxi , Brat Gabriel A. 
Published: June 2022

Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size largely retain good transportability performance when porting to different sites. The combination of routine laboratory test values at admission along with basic demographic features can predict mortality in patients hospitalized with COVID-19. Importantly, this potentially deployable model differs from prior work by demonstrating not only consistent performance but also reliable transportability across healthcare systems in the US and Europe, highlighting the generalizability of this model and the overall approach.