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English
Gil Ben-Horin
Published: Sep 16, 2016
A study was performed to examine and validate a sepsis prediction method, InSight, for the new Sepsis-3 definitions in retrospective data, make predictions using a minimal set of variables from within the electronic health record data, compare the performance of this approach with existing scoring systems and investigate the effects of data sparsity on InSight performance. The authors found that despite using little more than vitals, InSight is an effective tool for predicting sepsis onset and performs well even with randomly missing data. The data for this study was taken from the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC)-III version 1.3 dataset, compiled from the Beth Israel Deaconess Medical Center in Boston between 2001 and 2012. The MIMIC-III set includes anonymised data from over 52,000 ICU stays and more than 40,000 patients using both CareVue and MetaVision. The authors point out that “The use of only MetaVision patients deserves special discussion. For ICU stays logged using the CareVue system, data about procedures performed (i.e., cultures being taken) does not appear in the MIMIC-III database in as detailed and comprehensive a fashion as for ICU stays logged using MetaVision. Further, while the MIMIC-III version 1.3 dataset includes information from the BIDMC microbiology lab, reporting positive cultures and the results thereof for all patients, negative cultures are not reported consistently. The combination of these facts means that negative cultures are underreported for CareVue patients. This in turn implies that suspicion of infection, as defined by the cooccurrence of culture and antibiotics, is systematically underrepresented in these ICU stays, resulting in a sepsis prevalence of 3.5% for CareVue patients versus 11.3% for MetaVision. In light of this disparity, we chose to exclude CareVue patients from our analyses.”
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