文献类型：期刊文献

英文题名：Sharing is caring: A systematic review of publicly available intensive care data sets

作者：Jagesar, A. R.[1,2];Dam, T. A.[1,2];Struja, T.[3,4];Sauer, C. M.[4,5,6];Otten, M.[1,2];Biesheuvel, L. A.[1,2];Girbes, A. R. J.[1];Adhikari, L.[7];Zhang, Z.[8,9,10,11];Faltys, M.[12,13];Rodemund, N.[14];Thoral, P. J.[1];Celi, L. A.[4,15,16];Elbers, P. W. G.[1]

机构：[1]Vrije Univ, Amsterdam Inst Infect & Immun AII,Amsterdam Publ H, Ctr Crit Care Computat Intelligence C4I,Amsterdam, Dept Intens Care Med,Amsterdam Cardiovasc Sci ACS, Amsterdam, Netherlands;[2]Vrije Univ, Fac Sci, Dept Comp Sci, Quantitat Data Analyt Grp, Amsterdam, Netherlands;[3]Kantonsspital Aarau, Med Univ Clin, Div Endocrinol Diabet & Metab, Aarau, Switzerland;[4]MIT, Lab Computat Physiol, Cambridge, MA USA;[5]Univ Hosp Essen, Inst Artificial Intelligence Med IKIM, Essen, Germany;[6]Univ Hosp Essen, West German Canc Ctr, Dept Hematol & Stem Cell Transplantat, Essen, Germany;[7]Philips Res North Amer, Connected Care & Personal Hlth, Cambridge, MA USA;[8]Zhejiang Univ, Sch Med, Sir Run Run Shaw Hosp, Dept Emergency Med, Hangzhou, Peoples R China;[9]Zhejiang Univ, Sir Run Run Shaw Hosp, Sch Med, Prov Key Lab Precise Diag & Treatment Abdominal In, Hangzhou, Peoples R China;[10]Shaoxing Univ, Sch Med, Shaoxing, Peoples R China;[11]Longquan Ind Innovat Res Inst, Lishui, Peoples R China;[12]Univ Bern, Univ Hosp, Dept Intens Care Med, Bern, Switzerland;[13]Austin Hosp, Dept Intens Care, Melbourne, Australia;[14]Paracelsus Med Univ Salzburg, Dept Anaesthesiol Perioperat Med & Intens Care Med, Salzburg, Austria;[15]Beth Israel Deaconess Med Ctr, Div Pulm Crit Care & Sleep Med, Boston, MA USA;[16]Harvard TH Chan Sch Publ Hlth, Dept Biostat, Boston, MA USA

年份：2025

卷号：90

外文期刊名：JOURNAL OF CRITICAL CARE

收录：SCI-EXPANDED(收录号：WOS:001546802600001)、、Scopus(收录号：2-s2.0-105012569360)、WOS

基金：T.A. Dam's institution received funding from ZonMW/Netherlands Organization for Health Research and Development (10430012010003) . T.A. Dam is partially funded by Pacmed B.V. C.M. Sauer is supported by the German Research Foundation funded UMEA Clinician Scientist Program, grant number FU356/12-2. C.M. Sauer received consulting fees from Pacmed B.V. unrelated with this work. L. A. Celi is funded by the National Institute of Health through NIBIB R01 EB017205. Z.Z. received funding from the National Natural Science Foundation of China (Nos. 82472243 and 82272180) , the China National Key Research and Development Program (No. 2023YFC3603104) , the Huadong Medicine Joint Funds of the Zhejiang Provincial Natural Science Foundation of China (No. LHDMD24H150001) , the China National Key Research and Development Program (No. 2022YPC2504500) , a collaborative scientific project co-established by the Science and Technology Department of the National Administration of Traditional Chinese Medicine and the Zhejiang Provincial Administration of Traditional Chinese Medicine (No. GZY-ZJ-KJ-24082) , the General Health Science and Technology Program of Zhejiang Province (No. 2024KY1099) , the Project of Zhejiang University Longquan Innovation Center (No. ZJDXLQCXZCJBGS2024016) , and Wu Jieping Medical Foundation Special Research Grant (320.6750.2024-23-07) .

语种：英文

外文关键词：Critical care; Data science; Data set; ICU; Systematic review

外文摘要：Introduction: Multiple Intensive Care Unit (ICU) databases have been publicly released to advance data driven intensive care medicine. However, these public ICU data sets are prone to changes, updates and new releases. Therefore, the goal of this review is to provide clinicians and data scientists with a state-of-the-art overview and guide for choosing the relevant ICU data sets for their respective research questions. Methods: A systematic search was carried out in PubMed, PhysioNet, Arxiv, MedRxiv and BioRxiv to identify all publicly available intensive care data sets of adult patients. After data extraction of database characteristics, a qualitative synthesis of results was carried out. Results: 882 publications were identified. After screening, 7 publicly available ICU databases were included for analysis: AmsterdamUMCdb, eICU Collaborative Research Database (eICU-CRD), High Time Resolution ICU Dataset (HiRID), Medical Information Mart for Intensive Care (MIMIC)-IV, Northwestern ICU (NWICU), Salzburg Intensive Care database (SICdb) and Zigong Fourth People's Hospital (ZFPH) database of patients with infections. A qualitative synthesis showed notable differences in number of patients, usage of organ support, admission types and frequency of measurements. Conclusion: Each public ICU data set differs due to differences in medical practice, information technologies and approach to legal restrictions. This systematic review provides clinicians and data scientists with an overview of available public ICU data sets and their characteristics.