Early Recognition and Dynamic Risk Warning System of Multiple Organ Dysfunction Syndrome Caused by Sepsis
1 other identifier
observational
60,000
1 country
18
Brief Summary
Background Sepsis still the main challenge of ICU patients, because of its high morbidity and mortality. The proportion of sepsis, severe sepsis, and septic shock in china were 3.10%, 43.6%, and 53.3% with a 2.78%, 17.69%, and 51.94%, of 90-day mortality, respectively. Besides, according to the latest definition of sepsis- "a life-threatening organ dysfunction caused by a dysregulated host response to infection. ", it is a disease with intrinsic heterogeneity. Sepsis as a syndrome with such great heterogeneity, there will be significant differences in the severity of sepsis. As a result, there will be significant differences in the treatment and monitoring intensity required by patients with severe sepsis and mild sepsis. No matter from the economic perspective or from the risk of treatment, a proper level of treatment will be the best chose of patient. However, the evaluation of the sepsis severity was not satisfied. Such of SOFA, the AUC of predict patients' mortality was only 69%. Weather these patients occurred multiple organ dysfunction syndrome (MODS) may had totally different outcome and needed totally different treatment. All these treatments need early interference, in order to achieve a good prognosis. Hence, early recognition of MODS caused by sepsis became an imperious demand. Study design On the base of regional critical medicine clinical information platform, a multi-center, sepsis big data platform (including clinical information database and biological sample database) and a long-term follow-up database will be established. Thereafter, an early identification, risk classification and dynamic early warning system of sepsis induced MODS will be established. This system was based on the real-time dynamic vital signs and clinical information, combined with biomarker and multi-omics information. And this system was evaluated sepsis patients via artificial intelligence, machine learning, bioinformatics analysis techniques. Finally, optimize the early diagnosis of sepsis induced MODS, standardized the treatment strategy, reduce the morbidity and mortality of MODS through this system.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Apr 2022
18 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
May 23, 2021
CompletedFirst Posted
Study publicly available on registry
May 27, 2021
CompletedStudy Start
First participant enrolled
April 21, 2022
CompletedPrimary Completion
Last participant's last visit for primary outcome
September 30, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
December 31, 2023
CompletedSeptember 6, 2022
September 1, 2022
1.4 years
May 23, 2021
September 2, 2022
Conditions
Keywords
Outcome Measures
Primary Outcomes (3)
Sensitivity of the MODS recognized system
90 days
Specificity of the MODS recognized system
90 days
The AUC of the MODS recognized system ROC
90 days
Secondary Outcomes (2)
The Incidence rate of MODS in sepsis patients
90 days
The mortality of MODS in sepsis patients
90 days
Study Arms (2)
Sepsis with MODS
Patients with sepsis occurred MODS.
Sepsis without MODS
Patients with sepsis did not occur MODS.
Interventions
We analyzed all data we can obtain from our databases
Eligibility Criteria
Patients with sepsis
You may qualify if:
- Patients diagnosed with sepsis3.0
You may not qualify if:
- Patients' data missing is greater than 20%
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (18)
Chinese PLA General Hospital
Beijing, Beijing Municipality, 100000, China
Peking Union Medical College Hospital
Beijing, Beijing Municipality, 100000, China
Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University
Guangzhou, Guangdong, 510000, China
The First Affiliated Hospital of Guangzhou Medical University
Guangzhou, Guangdong, 510000, China
The First Affiliated Hospital, Sun Yat-sen University
Guangzhou, Guangdong, 510080, China
Qingyuan People's Hospital
Qingyuan, Guangdong, China
Peking University Shenzhen Hospital
Shenzhen, Guangdong, China
Union Hospital affiliated to Tongji Medical College of Huazhong University of Science and Technology
Wuhan, Hubei, China
Nanjing General Hospital of Nanjing Military Commend
Nanjing, Jiangsu, 210000, China
The First Affiliated Hospital of Xi 'an Jiaotong University
Xi'an, Shaanxi, China
Shandong Provincial Hospital
Jinan, Shandong, 250014, China
Shanghai Ruijin Hospital
Shanghai, Shanghai Municipality, 200000, China
Shanghai Zhongshan Hospital, Fudan University
Shanghai, Shanghai Municipality, 200000, China
West China Hospital, Sichuan University
Chengdu, Sichuan, 610000, China
The Second Affiliated Hospital of Zhejiang University School of Medicine
Hangzhou, Zhejiang, 310000, China
Zhejiang Hospital
Hangzhou, Zhejiang, 310000, China
Zhejiang Provincial People's Hospital
Hangzhou, Zhejiang, 310000, China
Beijing Friendship Hospital, Capital Medical University
Beijing, China
Related Publications (4)
Xie J, Wang H, Kang Y, Zhou L, Liu Z, Qin B, Ma X, Cao X, Chen D, Lu W, Yao C, Yu K, Yao X, Shang H, Qiu H, Yang Y; CHinese Epidemiological Study of Sepsis (CHESS) Study Investigators. The Epidemiology of Sepsis in Chinese ICUs: A National Cross-Sectional Survey. Crit Care Med. 2020 Mar;48(3):e209-e218. doi: 10.1097/CCM.0000000000004155.
PMID: 31804299BACKGROUNDSinger M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, Bellomo R, Bernard GR, Chiche JD, Coopersmith CM, Hotchkiss RS, Levy MM, Marshall JC, Martin GS, Opal SM, Rubenfeld GD, van der Poll T, Vincent JL, Angus DC. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016 Feb 23;315(8):801-10. doi: 10.1001/jama.2016.0287.
PMID: 26903338BACKGROUNDStanski NL, Wong HR. Prognostic and predictive enrichment in sepsis. Nat Rev Nephrol. 2020 Jan;16(1):20-31. doi: 10.1038/s41581-019-0199-3. Epub 2019 Sep 11.
PMID: 31511662BACKGROUNDLiu Z, Meng Z, Li Y, Zhao J, Wu S, Gou S, Wu H. Prognostic accuracy of the serum lactate level, the SOFA score and the qSOFA score for mortality among adults with Sepsis. Scand J Trauma Resusc Emerg Med. 2019 Apr 30;27(1):51. doi: 10.1186/s13049-019-0609-3.
PMID: 31039813BACKGROUND
Biospecimen
Serum, Urine
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- RETROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- prof
Study Record Dates
First Submitted
May 23, 2021
First Posted
May 27, 2021
Study Start
April 21, 2022
Primary Completion
September 30, 2023
Study Completion
December 31, 2023
Last Updated
September 6, 2022
Record last verified: 2022-09