SepsisEDAMMFSNCT04974411
Establishment of Early Diagnosis and Monitoring Model for Sepsis Patients
An observational study of Sepsis, run by First Affiliated Hospital Xi'an Jiaotong University at 1 site in China.
Trial summary
In recent years, although the clinical treatment of sepsis has been greatly improved, it is still an important cause of death in ICU patients, and seriously threatens human health. Read more about this study
- Who is it for?
- Ages 16 to 60 yearsHealthy volunteers can take part
- Conditions the study is for
- Sepsis
- What is being tested?
- infection and sepsis
- How many people
- 2,000 participants
- Where
- 1 siteChina
- Study dates
- 2 Feb 2021to 20 Mar 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 16 to 60 years
- All sexes
- Healthy volunteers accepted
- Child, Adult
Study population: Patients with infectious inflammation or sepsis
Who may be able to join
- Patients diagnosed with an infectious disease or Sepsis patients meeting the diagnostic criteria for sepsis 3.0 (determined by two doctors with senior professional titles)
- Older than 16 years and younger than 60 years
- Agree to cooperate with the investigation and sign the informed consent
Who cannot join
- The infection was preexisting with clinically diagnosed organ insufficiency or failure
- Hematological disorders predate infection
- Sepsis is preceded by a serious infectious disease
- Long-term use of immunosuppressant or immunodeficiency patients.
- A pregnant woman
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
The First Affiliated Hospital of Xi'an Jiaotong University
Xi'an, Shaanxi, 710061
Liu Chang, MD, 0086-18991232095, liuchangdoctor@163.com
Miao RunChen, MD, 0086-18229097849, miaozao@126.com
About this study
Official title: Establishment of a Model for Early Prediction, Diagnosis and Monitoring of Sepsis: a Cross Regional Multicenter Cohort Study
In recent years, although the clinical treatment of sepsis has been greatly improved, it is still an important cause of death in ICU patients, and seriously threatens human health. Its predictive biomarkers have become one of the bottlenecks in the field of disease diagnosis, treatment and development of effective drugs to reduce incidence rate and mortality. This will eventually become the key point of treatment for patients with sepsis. In the early stage, the investigators have established a single center sepsis database and sepsis animal model, and made a preliminary exploration on the mechanism and treatment of sepsis. Based on the previous results, this study intends to create a national multi center sepsis apparent database and sample bank, collect the data of sepsis patients' injury characteristics, clinical characteristics, biochemical indicators, micro multidimensional and omics results, etiological characteristics, etc., and integrate them. Using big data combined with machine learning method, the early warning and real-time course monitoring model of traumatic sepsis is established. The completion of this project can achieve early warning of sepsis, real-time monitoring of the progress of the disease, early rational allocation of medical care, and reduce the mortality of sepsis patients.
Read the detailed description
Sepsis is one of the most fatal diseases worldwide, characterized by high incidence rate (18.6/1 000 hospitalization) and high mortality (50%). The patients often need to be treated in ICU, and the medical cost accounts for a large proportion. The ideal state, that is, accurate and early identification, must be the key point to influence the clinical decision-making of sepsis and guide more accurate treatment and intervention. With the development and improvement of pre hospital emergency technology, surgical technology and intensive care technology, the early mortality of patients with sepsis decreased significantly, but the mortality caused by multiple organ dysfunction (MODS) increased significantly. However, there are few reports on early sepsis warning and real-time monitoring of sepsis patients.
The existing research on early warning and course monitoring of sepsis can be roughly divided into demographic data, trauma severity score system, physiological and biochemical indicators, genetic background and so on. However, most studies only focus on the significance of a single index in the early warning and diagnosis of sepsis, which can only reflect one aspect of the body, and the diagnostic sensitivity is not high. Although there are a few multi marker related studies, such as the haplotype (- 1082-819-592ata) of three gene polymorphisms in IL-10 promoter region can affect the risk of sepsis in a small population (114 cases). The combination of plasma and cell biomarkers in critically ill patients suggests that the combination of plasma PCT, sTREM-1 and neutrophil CD64 index is better than single index in the early warning diagnosis of sepsis risk. However, this kind of research is still limited to a certain kind of indicators, and its clinical guidance value is limited. In addition, metabonomics and proteomics also have great potential to help identify specific sepsis phenotypes, and to find much-needed predictive and prognostic biomarkers, so as to guide more personalized management and treatment. Therefore, it is necessary to integrate the injury characteristics, clinical characteristics, biochemical indicators, micro multidimensional and omics results, etiological characteristics and other data to make accurate and efficient early warning and course monitoring of sepsis.
The project team has established a single center sepsis database in the early stage, and how to expand the scale of the database in the future, and use the samples in the sample library for multidimensional and omics methods to screen 100 biological molecular targets. Further research will integrate sepsis patients' injury characteristics, clinical characteristics, biochemical indicators, micro multidimensional and omics results, etiological characteristics and other relatively independent parts, and use big data combined with machine learning method to establish early warning and real-time course monitoring model of traumatic sepsis.
This study will be carried out from the following three levels: 1) to establish a multi center database of patients with sepsis; ② 100 biological molecular targets were screened by micro multidimensional and omics, and the data of injury characteristics, clinical characteristics, biochemical indexes, micro multidimensional and omics results, etiological characteristics and other aspects of sepsis patients were integrated to establish an early accurate early warning and real-time disease monitoring model of sepsis; ③ The application of the prediction model in sepsis patients was further verified by a cross regional multicenter prospective cohort study.
- Conditions
- Sepsis
- Being tested
- infection, sepsis
- Medical subject headings
- Sepsis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
infectionOther
this study had two observation cohorts, one that observed sepsis in the presence of infection; the other cohort was monitored during sepsis until septic shock appeared
sepsisOther
this study had two observation cohorts, one that observed sepsis in the presence of infection; the other cohort was monitored during sepsis until septic shock appeared
| Study group | Role | What they receive |
|---|---|---|
| Infection | Patients diagnosed with infection but did not reach the sepsis marker. Receives: Other: infection | |
| sepsis | The patient was diagnosed with sepsis but did not develop septic shock Receives: Other: infection; Other: sepsis | |
| sepsis shock | The patient was diagnosed with sepsis shock Receives: Other: infection; Other: sepsis |
What is being measured
The primary outcome is the main question the study is designed to answer.
mortality
Patient in-hospital mortality and all-cause deaths that occurred during follow-up
Measured: From date of first record until the date of death from any cause, assessed up to 24 months
Secondary outcomes (4)
Average length of stay
The total length of time from admission to discharge
Measured: From date of admission until the date of first documented progression or date of death from any cause, whichever came first, assessed up to 6 months
length of stay in the intensive care unit
The total length of time the patient is admitted to the ICU to leave the ICU
Measured: From the first day of admission to the end of the ICU,assessed up to 6 months
the time of using antibiotic
Duration of antibiotics used in the ICU
Measured: From the first day of admission to the end of the ICU,assessed up to 6 months
the number of organ dysfunction
Number of patients with heart, liver, kidney, lung and other organ disorders during ICU treatment
Measured: From the first day of admission to the end of the ICU,assessed up to 6 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 Jul 2021
- Study start2 Feb 2021
- Primary completion28 Feb 2024 (estimated)
- Study completion20 Mar 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for SepsisStudies of the same condition, open and under way.
- More trials run by First Affiliated Hospital Xi'an Jiaotong UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 2,000 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Collaborators
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Second Affiliated Hospital of Xi'an Jiaotong University, Tang-Du Hospital, First Affiliated Hospital of Harbin Medical University, Affiliated Hospital of Qinghai University, General Hospital of Ningxia Medical University, LanZhou University, The Fourth People's Hospital of Nanning, First Affiliated Hospital of Xinjiang Medical University
- Responsible party
- Sponsor
- Investigators
- Liu Chang, MD, Study director, First Affiliated Hospital Xi'an Jiaotong University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04974411
- Sponsor's protocol ID
- XJTU1AF-CRF-2020-003
- Acronym
- EDAMMFS
- Status last verified
- Jul 2021
- First submitted
- 4 Jul 2021
- Last updated
- 23 Jul 2021
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 23 Jul 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Establishment of a Model for Early Prediction, Diagnosis and Monitoring of Sepsis: a Cross Regional Multicenter Cohort Study
- ClinicalTrials.gov ID
- NCT04974411
- Acronym / sponsor ID
- EDAMMFS / XJTU1AF-CRF-2020-003
- Conditions
- Sepsis
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 2,000 participants (estimated)
- Lead sponsor
- First Affiliated Hospital Xi'an Jiaotong UniversityUniversity, hospital or other
- Collaborators
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Second Affiliated Hospital of Xi'an Jiaotong University, Tang-Du Hospital, First Affiliated Hospital of Harbin Medical University, Affiliated Hospital of Qinghai University, General Hospital of Ningxia Medical University, LanZhou University, The Fourth People's Hospital of Nanning, First Affiliated Hospital of Xinjiang Medical University
- Study start
- 2 Feb 2021 (actual)
- Primary completion
- 28 Feb 2024 (estimated)
- Study completion
- 20 Mar 2024 (estimated)
- First posted
- 23 Jul 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
In recent years, although the clinical treatment of sepsis has been greatly improved, it is still an important cause of death in ICU patients, and seriously threatens human health. Its predictive biomarkers have become one of the bottlenecks in the field of disease diagnosis, treatment and development of effective drugs to reduce incidence rate and mortality. This will eventually become the key point of treatment for patients with sepsis. In the early stage, the investigators have established a single center sepsis database and sepsis animal model, and made a preliminary exploration on the mechanism and treatment of sepsis. Based on the previous results, this study intends to create a national multi center sepsis apparent database and sample bank, collect the data of sepsis patients' injury characteristics, clinical characteristics, biochemical indicators, micro multidimensional and omics results, etiological characteristics, etc., and integrate them. Using big data combined with machine learning method, the early warning and real-time course monitoring model of traumatic sepsis is established. The completion of this project can achieve early warning of sepsis, real-time monitoring of the progress of the disease, early rational allocation of medical care, and reduce the mortality of sepsis patients.
Detailed description
Sepsis is one of the most fatal diseases worldwide, characterized by high incidence rate (18.6/1 000 hospitalization) and high mortality (50%). The patients often need to be treated in ICU, and the medical cost accounts for a large proportion. The ideal state, that is, accurate and early identification, must be the key point to influence the clinical decision-making of sepsis and guide more accurate treatment and intervention. With the development and improvement of pre hospital emergency technology, surgical technology and intensive care technology, the early mortality of patients with sepsis decreased significantly, but the mortality caused by multiple organ dysfunction (MODS) increased significantly. However, there are few reports on early sepsis warning and real-time monitoring of sepsis patients.
The existing research on early warning and course monitoring of sepsis can be roughly divided into demographic data, trauma severity score system, physiological and biochemical indicators, genetic background and so on. However, most studies only focus on the significance of a single index in the early warning and diagnosis of sepsis, which can only reflect one aspect of the body, and the diagnostic sensitivity is not high. Although there are a few multi marker related studies, such as the haplotype (- 1082-819-592ata) of three gene polymorphisms in IL-10 promoter region can affect the risk of sepsis in a small population (114 cases). The combination of plasma and cell biomarkers in critically ill patients suggests that the combination of plasma PCT, sTREM-1 and neutrophil CD64 index is better than single index in the early warning diagnosis of sepsis risk. However, this kind of research is still limited to a certain kind of indicators, and its clinical guidance value is limited. In addition, metabonomics and proteomics also have great potential to help identify specific sepsis phenotypes, and to find much-needed predictive and prognostic biomarkers, so as to guide more personalized management and treatment. Therefore, it is necessary to integrate the injury characteristics, clinical characteristics, biochemical indicators, micro multidimensional and omics results, etiological characteristics and other data to make accurate and efficient early warning and course monitoring of sepsis.
The project team has established a single center sepsis database in the early stage, and how to expand the scale of the database in the future, and use the samples in the sample library for multidimensional and omics methods to screen 100 biological molecular targets. Further research will integrate sepsis patients' injury characteristics, clinical characteristics, biochemical indicators, micro multidimensional and omics results, etiological characteristics and other relatively independent parts, and use big data combined with machine learning method to establish early warning and real-time course monitoring model of traumatic sepsis.
This study will be carried out from the following three levels: 1) to establish a multi center database of patients with sepsis; ② 100 biological molecular targets were screened by micro multidimensional and omics, and the data of injury characteristics, clinical characteristics, biochemical indexes, micro multidimensional and omics results, etiological characteristics and other aspects of sepsis patients were integrated to establish an early accurate early warning and real-time disease monitoring model of sepsis; ③ The application of the prediction model in sepsis patients was further verified by a cross regional multicenter prospective cohort study.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Infection | – | Other: infectionPatients diagnosed with infection but did not reach the sepsis marker. |
| sepsis | – | Other: infection, Other: sepsisThe patient was diagnosed with sepsis but did not develop septic shock |
| sepsis shock | – | Other: infection, Other: sepsisThe patient was diagnosed with sepsis shock |
Who may qualify
- Ages
- 16 to 60 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult
- Study population
- Patients with infectious inflammation or sepsis
Key inclusion criteria (3 listed)
- Patients diagnosed with an infectious disease or Sepsis patients meeting the diagnostic criteria for sepsis 3.0 (determined by two doctors with senior professional titles)
- Older than 16 years and younger than 60 years
- Agree to cooperate with the investigation and sign the informed consent
Key exclusion criteria (5 listed)
- The infection was preexisting with clinically diagnosed organ insufficiency or failure
- Hematological disorders predate infection
- Sepsis is preceded by a serious infectious disease
- Long-term use of immunosuppressant or immunodeficiency patients.
- A pregnant woman
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| infectionthis study had two observation cohorts, one that observed sepsis in the presence of infection; the other cohort was monitored during sepsis until septic shock appeared | Other | Infection, sepsis, sepsis shock |
| sepsisthis study had two observation cohorts, one that observed sepsis in the presence of infection; the other cohort was monitored during sepsis until septic shock appeared | Other | sepsis, sepsis shock |
Primary outcome
mortality
Time frame: From date of first record until the date of death from any cause, assessed up to 24 months
Patient in-hospital mortality and all-cause deaths that occurred during follow-up
4 secondary outcomes
Average length of stay
Time frame: From date of admission until the date of first documented progression or date of death from any cause, whichever came first, assessed up to 6 months
length of stay in the intensive care unit
Time frame: From the first day of admission to the end of the ICU,assessed up to 6 months
the time of using antibiotic
Time frame: From the first day of admission to the end of the ICU,assessed up to 6 months
the number of organ dysfunction
Time frame: From the first day of admission to the end of the ICU,assessed up to 6 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Jul 2021.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Liu Chang, MD study director
First Affiliated Hospital Xi'an Jiaotong University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Sepsis, run by First Affiliated Hospital Xi'an Jiaotong University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 23 Jul 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Miao RunChen, MD (0086-18229097849, miaozao@126.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
mortality (time frame: From date of first record until the date of death from any cause, assessed up to 24 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 23 Jul 2021.