Literature DB >> 33044284

Characterizing the Patients, Hospitals, and Data Quality of the eICU Collaborative Research Database.

Heather M O'Halloran1, Kenneth Kwong1, Richard A Veldhoen1,2,3, David M Maslove1,2,3.   

Abstract

OBJECTIVES: The eICU Collaborative Research Database is a publicly available repository of granular data from more than 200,000 ICU admissions. The quantity and variety of its entries hold promise for observational critical care research. We sought to understand better the data available within this resource to guide its future use.
DESIGN: We conducted a descriptive analysis of the eICU Collaborative Research Database, including patient, practitioner, and hospital characteristics. We investigated the completeness of demographic and hospital data, as well as those values required to calculate an Acute Physiology and Chronic Health Evaluation score. We also assessed the rates of ventilation, intubation, and dialysis, and looked for potential errors in the vital sign data.
SETTING: American ICUs that participated in the Philips Healthcare eICU program between 2014 and 2015. PATIENTS: A total of 139,367 individuals who were admitted to one of the 335 participating ICUs between 2014 and 2015.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: Most encounters were from small- and medium-sized hospitals, and managed by nonintensivists. The median ICU length of stay was 1.57 days (interquartile range, 0.82-2.97 d). The median Acute Physiology and Chronic Health Evaluation IV-predicted ICU mortality was 2.2%, with an observed mortality of 5.4%. Rates of ventilation (20-33%), intubation (15-24%), and dialysis (3-5%) varied according to the query method used. Most vital sign readings fell into realistic ranges, with manually curated data less likely to contain implausible results than automatically entered data.
CONCLUSIONS: Data in the eICU Collaborative Research Database are for the most part complete and plausible. Some ambiguity exists in determining which encounters are associated with various interventions, most notably mechanical ventilation. Caution is warranted in extrapolating findings from the eICU Collaborative Research Database to larger ICUs with higher acuity.

Entities:  

Mesh:

Year:  2020        PMID: 33044284     DOI: 10.1097/CCM.0000000000004633

Source DB:  PubMed          Journal:  Crit Care Med        ISSN: 0090-3493            Impact factor:   7.598


  7 in total

1.  Association between basal platelet count and all-cause mortality in critically ill patients with acute respiratory failure: a secondary analysis from the eICU collaborative research database.

Authors:  Chuan Xiao; Zuoan Qin; Jingjing Xiao; Qing Li; Tianhui He; Shuwen Li; Feng Shen
Journal:  Am J Transl Res       Date:  2022-03-15       Impact factor: 4.060

2.  Systematic Review and Comparison of Publicly Available ICU Data Sets-A Decision Guide for Clinicians and Data Scientists.

Authors:  Christopher M Sauer; Tariq A Dam; Leo A Celi; Martin Faltys; Miguel A A de la Hoz; Lasith Adhikari; Kirsten A Ziesemer; Armand Girbes; Patrick J Thoral; Paul Elbers
Journal:  Crit Care Med       Date:  2022-03-02       Impact factor: 9.296

3.  Red Cell Distribution Width Is Independently Associated with Mortality in Sepsis.

Authors:  Daniel Dankl; Richard Rezar; Behrooz Mamandipoor; Zhichao Zhou; Sarah Wernly; Bernhard Wernly; Venet Osmani
Journal:  Med Princ Pract       Date:  2022-01-28       Impact factor: 2.132

4.  A Novel Method to Improve the Identification of Time of Intubation for Retrospective EHR Data Analysis During a Time of Resource Strain, the COVID-19 Pandemic.

Authors:  Alexander Makhnevich; Amir Gandomi; Yiduo Wu; Michael Qiu; Daniel Jafari; Daniel Rolston; Adey Tsegaye; Negin Hajizadeh
Journal:  Am J Med Qual       Date:  2022-03-11       Impact factor: 1.200

5.  Investigating the cognitive capacity constraints of an ICU care team using a systems engineering approach.

Authors:  Jaeyoung Park; Xiang Zhong; Yue Dong; Amelia Barwise; Brian W Pickering
Journal:  BMC Anesthesiol       Date:  2022-01-04       Impact factor: 2.217

Review 6.  Artificial intelligence in telemetry: what clinicians should know.

Authors:  David M Maslove; Paul W G Elbers; Gilles Clermont
Journal:  Intensive Care Med       Date:  2021-01-02       Impact factor: 17.440

7.  Development and validation of a score to predict mortality in ICU patients with sepsis: a multicenter retrospective study.

Authors:  Jie Weng; Ruonan Hou; Xiaoming Zhou; Zhe Xu; Zhiliang Zhou; Peng Wang; Liang Wang; Chan Chen; Jinyu Wu; Zhiyi Wang
Journal:  J Transl Med       Date:  2021-07-29       Impact factor: 5.531

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.