SepsisNCT06724120
Artificial Intelligence Prognostic Model for Sepsis Based on Time Series Analysis
An observational study of Sepsis and Prognostic Model, run by West China Hospital at 1 site in China.
Trial summary
Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. It is one of the leading causes of death and disability worldwide, with an inpatient mortality rate of 10-20%. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Sepsis, Prognostic Model, Artificial Intelligence
- How many people
- 3,641 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2020to 31 Dec 2023
- 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 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Retrospective analysis of clinical data of patients diagnosed with sepsis at West China Hospital of Sichuan University from January 2020 to December 2023. Review and summarize the baseline data of patients (including age, gender, comorbidities, history of malignant tumors, lesion location, pathological type, etc.), occurrence of serious complications, total length of hospital stay, survival time, and construct a time-series based mortality risk prognosis prediction model for sepsis patients.
Who may be able to join
- Patients clinically diagnosed with sepsis at West China Hospital of Sichuan University from January 2020 to December 2023
Who cannot join
- Under the age of 18;
- Gender unknown;
- Incorrect or invalid discharge diagnosis;
- The hospitalization time is less than 24 hours;
- Data information is missing by more than 30%.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Construction of an Artificial Intelligence Prognostic Prediction Model for Sepsis Based on Time Series Analysis
Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. It is one of the leading causes of death and disability worldwide, with an inpatient mortality rate of 10-20%. Sepsis is a severe complication in critically ill patients and can lead to septic shock and multiple organ dysfunction syndrome (MODS), usually triggered by severe trauma, surgery, and infections. Despite the availability of advanced diagnostic, therapeutic, and monitoring technologies, the incidence and mortality of sepsis remain high, posing a significant global challenge to the medical community. Over 49 million people worldwide develop sepsis annually, with approximately 11 million deaths, resulting in a mortality rate of about 15%-25%.
This study aims to develop a prognosis prediction model for sepsis patients using a neural network architecture (Transformer algorithm), based on time-series data. The primary outcome observed is the mortality outcome of sepsis patients. The goal of the research is to enhance the early identification of high-risk sepsis patients, thereby optimizing the timing of sepsis treatment and intervention and improving the accuracy of prognosis prediction for sepsis patients.
Read the detailed description
- Research Background Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. It is one of the leading causes of death and disability worldwide, with an inpatient mortality rate of 10-20%. Sepsis is a severe complication in critically ill patients and can lead to septic shock and multiple organ dysfunction syndrome (MODS), usually triggered by severe trauma, surgery, and infections. Despite the availability of advanced diagnostic, therapeutic, and monitoring technologies, the incidence and mortality of sepsis remain high, posing a significant global challenge to the medical community. Over 49 million people worldwide develop sepsis annually, with approximately 11 million deaths, resulting in a mortality rate of about 15%-25%.
- Research Objectives and Content
- Research Objective This study aims to develop a prognosis prediction model for sepsis patients using a neural network architecture (Transformer algorithm), based on time-series data. The primary outcome observed is the mortality outcome of sepsis patients. The goal of the research is to enhance the early identification of high-risk sepsis patients, thereby optimizing the timing of sepsis treatment and intervention and improving the accuracy of prognosis prediction for sepsis patients.
- Research Content 2.1 Inclusion Criteria Patients diagnosed with sepsis at West China Hospital of Sichuan University from January 2020 to December 2023. 2.2 Exclusion Criteria 1) Age under 18 years; 2) Gender unknown; 3) Incorrect or invalid discharge diagnosis; 4) Hospitalization period less than 24 hours; 5) Missing data exceeds 30%. 2.3 Sample Size 3,000 cases. 2.4 Data to be Collected A retrospective analysis of the clinical data of patients diagnosed with sepsis at West China Hospital of Sichuan University from January 2020 to December 2023 will be conducted. The baseline data of patients (including age, gender, comorbidities, history of malignant tumors, lesion sites, pathological types, etc.), occurrence of severe complications, total hospital stay, survival time, and other relevant information will be summarized to build a time-series-based prognosis prediction model for sepsis mortality risk.
- Clinical Research Ethical Principles and Requirements This clinical research will comply with the Declaration of Helsinki issued by the World Medical Association and the relevant regulations set forth by the National Health and Family Planning Commission of the People's Republic of China concerning the Ethical Review of Biomedical Research Involving Human Subjects. The research will only utilize retrospective medical records and/or specimens, with all personal identifiers removed. There will be no risk to the subjects, nor will it negatively impact their rights or health. Therefore, informed consent is waived. The research data will be stored at West China Hospital of Sichuan University, accessible to the researchers, supervising departments, and the ethics review committee. Any public reports related to the research findings will not disclose the personal identity of the subjects. We will make every effort within the legal framework to protect the privacy and personal medical information of the subjects.
- Conditions
- Sepsis, Prognostic Model, Artificial Intelligence, Individuality
- Being tested
- No interventions
- Medical subject headings
- Sepsis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
No interventionsOther
No interventions
| Study group | Role | What they receive |
|---|---|---|
| Survival Group | Not described Receives: Other: No interventions | |
| Non-survival Group | Not described Receives: Other: No interventions |
What is being measured
The primary outcome is the main question the study is designed to answer.
Biomarker level
Including inflammatory markers (such as C-reactive protein (CRP), interleukins (IL-6, IL-10), and procalcitonin (PCT)) and metabolic markers (such as lactate levels and arterial blood gas pH values) for sepsis prognostic analysis.
Measured: 5 Years
Secondary outcomes (3)
SOFA score
Standard measure of organ function for sepsis.
Measured: 5 Years
Length of ICU stay
Reflects the severity of illness and critical care needs.
Measured: 5 Years
APACHE II score
Standard measure of severity for sepsis.
Measured: 5 Years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Dec 2024
- Study start1 Jan 2020
- Primary completion31 Dec 2023
- Study completion31 Dec 2023
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 West China HospitalThe 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
- Retrospective
- Enrolment
- 3,641 participants (actual)
Sponsor and investigators
- Lead sponsor
- West China Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Chi Zhang, West China Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06724120
- Sponsor's protocol ID
- No.126 in 2024
- Status last verified
- Dec 2024
- First submitted
- 30 Nov 2024
- Last updated
- 9 Dec 2024
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 9 Dec 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Construction of an Artificial Intelligence Prognostic Prediction Model for Sepsis Based on Time Series Analysis
- ClinicalTrials.gov ID
- NCT06724120
- Acronym / sponsor ID
- No.126 in 2024
- Conditions
- Sepsis, Prognostic Model, Artificial Intelligence, Individuality
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 3,641 participants (actual)
- Lead sponsor
- West China HospitalUniversity, hospital or other
- Study start
- 1 Jan 2020 (actual)
- Primary completion
- 31 Dec 2023 (actual)
- Study completion
- 31 Dec 2023 (actual)
- First posted
- 9 Dec 2024 (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.
Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. It is one of the leading causes of death and disability worldwide, with an inpatient mortality rate of 10-20%. Sepsis is a severe complication in critically ill patients and can lead to septic shock and multiple organ dysfunction syndrome (MODS), usually triggered by severe trauma, surgery, and infections. Despite the availability of advanced diagnostic, therapeutic, and monitoring technologies, the incidence and mortality of sepsis remain high, posing a significant global challenge to the medical community. Over 49 million people worldwide develop sepsis annually, with approximately 11 million deaths, resulting in a mortality rate of about 15%-25%.
This study aims to develop a prognosis prediction model for sepsis patients using a neural network architecture (Transformer algorithm), based on time-series data. The primary outcome observed is the mortality outcome of sepsis patients. The goal of the research is to enhance the early identification of high-risk sepsis patients, thereby optimizing the timing of sepsis treatment and intervention and improving the accuracy of prognosis prediction for sepsis patients.
Detailed description
- Research Background Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. It is one of the leading causes of death and disability worldwide, with an inpatient mortality rate of 10-20%. Sepsis is a severe complication in critically ill patients and can lead to septic shock and multiple organ dysfunction syndrome (MODS), usually triggered by severe trauma, surgery, and infections. Despite the availability of advanced diagnostic, therapeutic, and monitoring technologies, the incidence and mortality of sepsis remain high, posing a significant global challenge to the medical community. Over 49 million people worldwide develop sepsis annually, with approximately 11 million deaths, resulting in a mortality rate of about 15%-25%.
- Research Objectives and Content
- Research Objective This study aims to develop a prognosis prediction model for sepsis patients using a neural network architecture (Transformer algorithm), based on time-series data. The primary outcome observed is the mortality outcome of sepsis patients. The goal of the research is to enhance the early identification of high-risk sepsis patients, thereby optimizing the timing of sepsis treatment and intervention and improving the accuracy of prognosis prediction for sepsis patients.
- Research Content 2.1 Inclusion Criteria Patients diagnosed with sepsis at West China Hospital of Sichuan University from January 2020 to December 2023. 2.2 Exclusion Criteria 1) Age under 18 years; 2) Gender unknown; 3) Incorrect or invalid discharge diagnosis; 4) Hospitalization period less than 24 hours; 5) Missing data exceeds 30%. 2.3 Sample Size 3,000 cases. 2.4 Data to be Collected A retrospective analysis of the clinical data of patients diagnosed with sepsis at West China Hospital of Sichuan University from January 2020 to December 2023 will be conducted. The baseline data of patients (including age, gender, comorbidities, history of malignant tumors, lesion sites, pathological types, etc.), occurrence of severe complications, total hospital stay, survival time, and other relevant information will be summarized to build a time-series-based prognosis prediction model for sepsis mortality risk.
- Clinical Research Ethical Principles and Requirements This clinical research will comply with the Declaration of Helsinki issued by the World Medical Association and the relevant regulations set forth by the National Health and Family Planning Commission of the People's Republic of China concerning the Ethical Review of Biomedical Research Involving Human Subjects. The research will only utilize retrospective medical records and/or specimens, with all personal identifiers removed. There will be no risk to the subjects, nor will it negatively impact their rights or health. Therefore, informed consent is waived. The research data will be stored at West China Hospital of Sichuan University, accessible to the researchers, supervising departments, and the ethics review committee. Any public reports related to the research findings will not disclose the personal identity of the subjects. We will make every effort within the legal framework to protect the privacy and personal medical information of the subjects.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Survival Group | – | Other: No interventions |
| Non-survival Group | – | Other: No interventions |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Retrospective analysis of clinical data of patients diagnosed with sepsis at West China Hospital of Sichuan University from January 2020 to December 2023. Review and summarize the baseline data of patients (including age, gender, comorbidities, history of malignant tumors, lesion location, pathological type, etc.), occurrence of serious complications, total length of hospital stay, survival time, and construct a time-series based mortality risk prognosis prediction model for sepsis patients.
Key inclusion criteria (1 listed)
- Patients clinically diagnosed with sepsis at West China Hospital of Sichuan University from January 2020 to December 2023
Key exclusion criteria (5 listed)
- Under the age of 18;
- Gender unknown;
- Incorrect or invalid discharge diagnosis;
- The hospitalization time is less than 24 hours;
- Data information is missing by more than 30%.
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 |
|---|---|---|
| No interventionsNo interventions | Other | Non-survival Group, Survival Group |
Primary outcome
Biomarker level
Time frame: 5 Years
Including inflammatory markers (such as C-reactive protein (CRP), interleukins (IL-6, IL-10), and procalcitonin (PCT)) and metabolic markers (such as lactate levels and arterial blood gas pH values) for sepsis prognostic analysis.
3 secondary outcomes
SOFA score
Time frame: 5 Years
Length of ICU stay
Time frame: 5 Years
APACHE II score
Time frame: 5 Years
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 9 Dec 2024.
- Individual participant dataSharing planned: Undecided
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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.
The record lists no contact. Use the official record to reach the sponsor.
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 and Prognostic Model, run by West China Hospital 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 1 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: finished, as of the sponsor's last update on 9 Dec 2024. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Biomarker level (time frame: 5 Years). 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 9 Dec 2024.