SEVERITAS: An externally validated mortality prediction for critically ill patients in low and middle-income countries-Reference-Cited by-同舟云学术

SEVERITAS: An externally validated mortality prediction for critically ill patients in low and middle-income countries

Published:2019-11 Issue: Volume:131 Page:103959
ISSN:1386-5056
Container-title:International Journal of Medical Informatics
language:en
Short-container-title:International Journal of Medical Informatics

Author:

Deliberato Rodrigo Octávio,Escudero Guilherme Goto,Bulgarelli Lucas,Neto Ary Serpa,Ko Stephanie Q,Campos Niklas Soderberg,Saat Berke,Amaro Edson,Lopes Fabio Silva,Johnson Alistair EW

Funder

National Institutes of Health

MISTI MIT-Brazil Internship Program and the MIT-TVML Foundation

Publisher

Elsevier BV

Subject

Health Informatics

Reference26 articles.

1. Performance of critical care prognostic scoring system in low and middle-income countries: a systematic review;Haniffa;Crit Care,2018

2. Acute Physiology and Chronic Health Evaluation (APACHE) IV: hospital mortality assessment for today’s critically ill patients;Zimmerman;Crit. Care Med.,2006

3. SAPS 3 - from evaluation of the patient to evaluation of the intensive care unit;Metnitz;Intensive Care Med.,2005

4. Updated mortality probability model - MPM0-III;Higgins;Chest,2005

5. New perspectives to improve critical care benchmarking;Salluh;Ann. Intensive Care,2018

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