SEPRES: Sepsis prediction via the clinical data integration system in the ICU

Background The lack of information interoperability between different devices and systems in the ICU hinders further utilization of data, especially for early warning of specific diseases in the ICU. Objectives We aimed to establish a real-time early warning system for sepsis based on a data integration system that can be implemented at the bedside of the intensive care unit (ICU), named SEPRES. Methods Data is collected from bedside devices through the integration hub and uploaded to the integration system through the local area network. The data integration system was designed to integrate vital signs data, laboratory data, ventilator data, demographic data, pharmacy data, nursing data, etc. from multiple medical devices and systems. It integrates, standardizes, and stores information, making the real-time inference of the early warning module possible. The built-in sepsis early warning module can detect the onset of sepsis within 5 hours preceding at most. Results Our data integration system has already been deployed in Ruijin Hospital, confirming the effectiveness of our system. Conclusions We highlight that SEPRES has the potential to improve ICU management by helping medical practitioners identify at-sepsis-risk patients and prepare for timely diagnosis and intervention. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement W.L. received funding from Shanghai Municipal Science and Technology Major Project (2018SHZDZX01), the ZHANGJIANG LAB, and the Science and Technology Commission of Shanghai Municipality (19JC1420101). The funders of the study had no role in the study design, data collection, data analysis, data interpretation, or writing of the report. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Ruijin Hospital Ethics Committee gave ethical approval for this work (No. 2020 [140]). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All data produced in the present work are contained in the manuscript