Surgical Site Infection (SSI)NCT07378683
A Clinical Prediction Model for Surgical Site Infection After Central Nervous System Tumor Surgery
A study testing ML-Based Enhanced Intervention Package for SSI Prevention and Standard Postoperative Care in people with Surgical Site Infection (SSI) and Central Nervous System Tumor, run by Ming Yang at 1 site in China.
Trial summary
1. Study Background For patients undergoing brain or spinal tumor surgery, postoperative surgical wound infection (known as "surgical site infection," SSI) is a recognized risk. Once an infection occurs, it may complicate and prolong the recovery process. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Surgical Site Infection (SSI), Central Nervous System Tumor
- What is being tested?
- ML-Based Enhanced Intervention Package for SSI Prevention and Standard Postoperative Care
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 500 participants
- Where
- 1 siteChina
- Study dates
- 1 Jun 2025to 30 Oct 2029
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
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 Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Who may be able to join
- Patients with a pathologically confirmed primary or metastatic central nervous system (brain or spinal) tumor.
- Scheduled for elective craniotomy or spinal tumor resection surgery.
- Age ≥ 18 years.
- Expected survival > 3 months, and able/willing to comply with postoperative follow-up.
- Voluntary participation and provision of written informed consent.
Who cannot join
- Presence of active systemic or local surgical site infection before surgery.
- Use of therapeutic antibiotics for any reason within 72 hours prior to surgery.
- Concurrent severe immunosuppressive conditions, or chronic use of high-dose immunosuppressants.
- Pregnancy or lactation.
- Known contraindications or severe allergy to the antibiotics planned for use in the study.
- Any other condition that, in the investigator's judgment, may affect study participation or outcome assessment.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Beijing, PUMC, 10010
Ming Yang, MD, +8613810655237, yangming@cicams.ac.cn
Fengchun Mu, 18888294650, alicemfc@163.com
About this study
Official title: A Prospective, Single-Center Clinical Validation Study: Machine Learning Model-Based Risk Stratification Intervention for Reducing Surgical Site Infection After Central Nervous System Tumor Surgery
- Study Background For patients undergoing brain or spinal tumor surgery, postoperative surgical wound infection (known as "surgical site infection," SSI) is a recognized risk. Once an infection occurs, it may complicate and prolong the recovery process. Currently, doctors primarily rely on clinical experience to judge which patients are at higher risk of infection. Our research team has previously developed an intelligent prediction model (a machine learning tool) that can very accurately identify which patients are at higher risk of postoperative infection. This study aims to validate whether implementing enhanced preventive measures for high-risk patients in advance, based on the model's predictions, can effectively reduce the occurrence of infection.
- Study Purpose The primary purpose of this study is to validate whether an individualized intervention strategy based on an intelligent prediction model can effectively reduce the incidence of surgical site infection in patients after central nervous system tumor surgery. Simultaneously, we will also evaluate the safety of this strategy, its impact on patient hospital stay length and medical costs, as well as its feasibility in practical clinical application.
- Study Design Type: This is a prospective, single-center clinical validation study. "Prospective" means the research plan is established first, followed by patient recruitment and data collection according to the plan; "single-center" indicates the study is conducted solely at the Chinese Academy of Medical Sciences Cancer Hospital. Process: For all patients who consent to participate in this study, within 72 hours after surgery, the research system will automatically calculate their infection risk based on 8 key clinical indicators (such as blood test results, medical history, etc.). High-Risk Group (model-predicted infection probability ≥50%): Will receive a set of enhanced, individualized infection prevention measures (e.g., adjusted antibiotic regimen, enhanced nutritional support, closer monitoring). Low-Risk Group (model-predicted infection probability <50%): Will receive the current standard, high-quality postoperative care. Duration: The study is planned to run from February 2026 to October 2029. Each participating patient will be followed for 3 months (90 days) to observe whether infection occurs. Sample Size: It is planned to recruit approximately 500 eligible patients.
- Primary Evaluation Indicators Primary Indicator: The incidence of surgical site infection within 90 days after surgery. The diagnosis of infection will be made by experts who are unaware of the patient's group assignment, strictly following international standards. Secondary Indicators: Include the accuracy of the intelligent prediction model in practical use, patient hospital stay length, other infection-related complications, medical costs, and the adoption rate of the model's recommendations by physicians.
- Eligibility Criteria (Inclusion Criteria Summary) You may be eligible to participate in this study if you meet the following conditions: Diagnosed with a brain or spinal tumor and scheduled for elective surgery. Aged 18 years or older. Expected survival exceeds 3 months and able to cooperate with postoperative follow-up. Voluntary participation and signing of a written informed consent form. (Note: This study has detailed exclusion criteria. Final confirmation of whether all criteria are met will be determined by your study doctor.)
- Patients' Rights and Safety Voluntary Participation: Participation in this study is entirely voluntary. You have the right to withdraw from the study at any time, which will not affect the quality of any normal medical services you are entitled to at our hospital or your relationship with it. Informed Consent: Before the study begins, your study doctor will explain all study procedures, potential risks, and benefits in detail, and you will sign an "Informed Consent Form." Privacy Protection: All your personally identifiable information will be kept strictly confidential. Codes will replace your name and other identifiable information in research analyses and reports. Safety Assurance: This study has been reviewed and approved by the hospital's Ethics Committee. We have established an independent Data Safety Monitoring Board to monitor the study's safety throughout. Clinical trial liability insurance has been purchased for all participants to cover damages related to the trial.
- Contact Information
If you would like to learn more about this study, please contact us via:
Principal Investigator: Dr. Yang Ming National Cancer Center/National Clinical Research Center for Cancer/Cancer Research Unit: Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
- Being tested
- ML-Based Enhanced Intervention Package for SSI Prevention, Standard Postoperative Care
- Keywords
- surgical site infection, central nervous system tumor, machine learning, explainable artificial intelligence, SHAP, clinical decision support system
- Medical subject headings
- Surgical Wound Infection, Central Nervous System Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
ML-Based Enhanced Intervention Package for SSI PreventionOther
This is a comprehensive, individualized intervention package administered to patients identified as high-risk for surgical site infection (SSI) by a machine learning (LightGBM) model. The package is activated postoperatively and may include, but is not limited to: 1) Escalated/optimized antibiotic prophylaxis regimen; 2) Intensified nutritional support protocols; 3) Enhanced monitoring of vital signs and wound status. The specific components are tailored based on the patient's risk profile and clinical context. The intervention aims to validate the effectiveness of a model-driven strategy in reducing SSI incidence.
Standard Postoperative CareOther
This intervention represents the current standard of care provided to patients after elective central nervous system tumor surgery at this institution. It includes routine antibiotic prophylaxis, standard wound care, basic vital signs monitoring, and follow-up according to established clinical pathways. Patients in this group do not receive the enhanced, study-specific intervention package and serve as the control population for comparison.
| Study group | Role | What they receive |
|---|---|---|
| High-Risk: ML-Based Intervention | Experimental | This is the High-Risk Intervention Group. Patients identified as high-risk for SSI (predicted probability ≥ 50%) by the LightGBM model within 72 hours post-surgery receive an enhanced, individualized intervention package, which may include an escalated antibiotic regimen, intensified nutritional support, and closer monitoring. Receives: Other: ML-Based Enhanced Intervention Package for SSI Prevention |
| Low-Risk: Standard Care | Active comparator | This is the Low-Risk Routine Care Group. Patients identified as low-risk for SSI (predicted probability < 50%) by the same model receive the current standard postoperative care of the hospital, following established clinical pathways without the enhanced intervention package. This arm serves as the control. Receives: Other: Standard Postoperative Care |
What is being measured
The primary outcome is the main question the study is designed to answer.
Incidence of surgical site infection within 90 days postoperatively
The occurrence of a surgical site infection (SSI) following central nervous system tumor surgery, diagnosed according to the U.S. National Healthcare Safety Network (NHSN) criteria. Diagnosis will be adjudicated by a blinded independent endpoint adjudication committee.
Measured: 90 days post-surgery
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted30 Jan 2026
- Study start1 Jun 2025
- Primary completion30 Oct 2029 (estimated)
- Study completion30 Oct 2029 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Surgical Site Infection (SSI)Studies of the same condition, open and under way.
- 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Model description
- A prospective, single-center clinical validation study aimed at evaluating the effectiveness of a machine learning (LightGBM) model-based risk stratification intervention strategy in reducing the incidence of surgical site infection (SSI) in patients after central nervous system tumor surgery. The study plans to enroll 500 patients undergoing elective surgery. SSI risk will be calculated within 72 hours postoperatively using the model, which is based on 8 clinical features. The high-risk group (predicted probability ≥50%) will receive individualized enhanced interventions (e.g., antibiotic escalation, nutritional support), while the low-risk group (predicted probability \<50%) will receive standard care. The primary endpoint is the incidence of SSI within 90 days postoperatively (NHSN criteria), and secondary endpoints include model performance, hospital stay length, medical costs, etc.
- Masking
- None (open label)
- Enrolment
- 500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Ming Yang
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Ming Yang, Cancer Institute and Hospital, Chinese Academy of Medical Sciences
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07378683
- Sponsor's protocol ID
- NCC2025-CNS-SSI
- Other IDs
- 2024-I2M-3-014
- Status last verified
- Jan 2026
- First submitted
- 22 Jan 2026
- Last updated
- 30 Jan 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: De-identified individual participant data underlying the results reported in this article (including demographics, clinical characteristics, model input variables, and primary endpoint) will be shared. The study protocol, statistical analysis plan, and informed consent form will also be made available. Data will become available following publication of the primary results in a peer-reviewed journal and will be accessible for at least 5 years. Access will be granted to researchers whose methodologically sound proposals have been approved by a scientific review committee, via a controlled-access data repository or upon request.
Study at a glance
From the registry record, last updated by the sponsor on 30 Jan 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Prospective, Single-Center Clinical Validation Study: Machine Learning Model-Based Risk Stratification Intervention for Reducing Surgical Site Infection After Central Nervous System Tumor Surgery
- ClinicalTrials.gov ID
- NCT07378683
- Acronym / sponsor ID
- NCC2025-CNS-SSI
- Keywords
- surgical site infection, central nervous system tumor, machine learning, explainable artificial intelligence, SHAP, clinical decision support system
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 500 participants (estimated)
- Lead sponsor
- Ming YangUniversity, hospital or other
- Study start
- 1 Jun 2025 (actual)
- Primary completion
- 30 Oct 2029 (estimated)
- Study completion
- 30 Oct 2029 (estimated)
- First posted
- 30 Jan 2026 (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.
- Study Background For patients undergoing brain or spinal tumor surgery, postoperative surgical wound infection (known as "surgical site infection," SSI) is a recognized risk. Once an infection occurs, it may complicate and prolong the recovery process. Currently, doctors primarily rely on clinical experience to judge which patients are at higher risk of infection. Our research team has previously developed an intelligent prediction model (a machine learning tool) that can very accurately identify which patients are at higher risk of postoperative infection. This study aims to validate whether implementing enhanced preventive measures for high-risk patients in advance, based on the model's predictions, can effectively reduce the occurrence of infection.
- Study Purpose The primary purpose of this study is to validate whether an individualized intervention strategy based on an intelligent prediction model can effectively reduce the incidence of surgical site infection in patients after central nervous system tumor surgery. Simultaneously, we will also evaluate the safety of this strategy, its impact on patient hospital stay length and medical costs, as well as its feasibility in practical clinical application.
- Study Design Type: This is a prospective, single-center clinical validation study. "Prospective" means the research plan is established first, followed by patient recruitment and data collection according to the plan; "single-center" indicates the study is conducted solely at the Chinese Academy of Medical Sciences Cancer Hospital. Process: For all patients who consent to participate in this study, within 72 hours after surgery, the research system will automatically calculate their infection risk based on 8 key clinical indicators (such as blood test results, medical history, etc.). High-Risk Group (model-predicted infection probability ≥50%): Will receive a set of enhanced, individualized infection prevention measures (e.g., adjusted antibiotic regimen, enhanced nutritional support, closer monitoring). Low-Risk Group (model-predicted infection probability <50%): Will receive the current standard, high-quality postoperative care. Duration: The study is planned to run from February 2026 to October 2029. Each participating patient will be followed for 3 months (90 days) to observe whether infection occurs. Sample Size: It is planned to recruit approximately 500 eligible patients.
- Primary Evaluation Indicators Primary Indicator: The incidence of surgical site infection within 90 days after surgery. The diagnosis of infection will be made by experts who are unaware of the patient's group assignment, strictly following international standards. Secondary Indicators: Include the accuracy of the intelligent prediction model in practical use, patient hospital stay length, other infection-related complications, medical costs, and the adoption rate of the model's recommendations by physicians.
- Eligibility Criteria (Inclusion Criteria Summary) You may be eligible to participate in this study if you meet the following conditions: Diagnosed with a brain or spinal tumor and scheduled for elective surgery. Aged 18 years or older. Expected survival exceeds 3 months and able to cooperate with postoperative follow-up. Voluntary participation and signing of a written informed consent form. (Note: This study has detailed exclusion criteria. Final confirmation of whether all criteria are met will be determined by your study doctor.)
- Patients' Rights and Safety Voluntary Participation: Participation in this study is entirely voluntary. You have the right to withdraw from the study at any time, which will not affect the quality of any normal medical services you are entitled to at our hospital or your relationship with it. Informed Consent: Before the study begins, your study doctor will explain all study procedures, potential risks, and benefits in detail, and you will sign an "Informed Consent Form." Privacy Protection: All your personally identifiable information will be kept strictly confidential. Codes will replace your name and other identifiable information in research analyses and reports. Safety Assurance: This study has been reviewed and approved by the hospital's Ethics Committee. We have established an independent Data Safety Monitoring Board to monitor the study's safety throughout. Clinical trial liability insurance has been purchased for all participants to cover damages related to the trial.
- Contact Information
If you would like to learn more about this study, please contact us via:
Principal Investigator: Dr. Yang Ming National Cancer Center/National Clinical Research Center for Cancer/Cancer Research Unit: Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Study design
- Primary purpose
- Diagnosis
- Allocation
- Non-randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- A prospective, single-center clinical validation study aimed at evaluating the effectiveness of a machine learning (LightGBM) model-based risk stratification intervention strategy in reducing the incidence of surgical site infection (SSI) in patients after central nervous system tumor surgery. The study plans to enroll 500 patients undergoing elective surgery. SSI risk will be calculated within 72 hours postoperatively using the model, which is based on 8 clinical features. The high-risk group (predicted probability ≥50%) will receive individualized enhanced interventions (e.g., antibiotic escalation, nutritional support), while the low-risk group (predicted probability <50%) will receive standard care. The primary endpoint is the incidence of SSI within 90 days postoperatively (NHSN criteria), and secondary endpoints include model performance, hospital stay length, medical costs, etc.
| Arm | Type | Receives |
|---|---|---|
| High-Risk: ML-Based Intervention | Experimental | Other: ML-Based Enhanced Intervention Package for SSI PreventionThis is the High-Risk Intervention Group. Patients identified as high-risk for SSI (predicted probability ≥ 50%) by the LightGBM model within 72 hours post-surgery receive an enhanced, individualized intervention package, which may include an escalated antibiotic regimen, intensified nutritional support, and closer monitoring. |
| Low-Risk: Standard Care | Active comparator | Other: Standard Postoperative CareThis is the Low-Risk Routine Care Group. Patients identified as low-risk for SSI (predicted probability < 50%) by the same model receive the current standard postoperative care of the hospital, following established clinical pathways without the enhanced intervention package. This arm serves as the control. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (5 listed)
- Patients with a pathologically confirmed primary or metastatic central nervous system (brain or spinal) tumor.
- Scheduled for elective craniotomy or spinal tumor resection surgery.
- Age ≥ 18 years.
- Expected survival > 3 months, and able/willing to comply with postoperative follow-up.
- Voluntary participation and provision of written informed consent.
Key exclusion criteria (6 listed)
- Presence of active systemic or local surgical site infection before surgery.
- Use of therapeutic antibiotics for any reason within 72 hours prior to surgery.
- Concurrent severe immunosuppressive conditions, or chronic use of high-dose immunosuppressants.
- Pregnancy or lactation.
- Known contraindications or severe allergy to the antibiotics planned for use in the study.
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 |
|---|---|---|
| ML-Based Enhanced Intervention Package for SSI PreventionThis is a comprehensive, individualized intervention package administered to patients identified as high-risk for surgical site infection (SSI) by a machine learning (LightGBM) model. The package is activated postoperatively and may include, but is not limited to: 1) Escalated/optimized antibiotic prophylaxis regimen; 2) Intensified nutritional support protocols; 3) Enhanced monitoring of vital signs and wound status. The specific components are tailored based on the patient's risk profile and clinical context. The intervention aims to validate the effectiveness of a model-driven strategy in reducing SSI incidence. | Other | High-Risk: ML-Based Intervention |
| Standard Postoperative CareThis intervention represents the current standard of care provided to patients after elective central nervous system tumor surgery at this institution. It includes routine antibiotic prophylaxis, standard wound care, basic vital signs monitoring, and follow-up according to established clinical pathways. Patients in this group do not receive the enhanced, study-specific intervention package and serve as the control population for comparison. | Other | Low-Risk: Standard Care |
Primary outcome
Incidence of surgical site infection within 90 days postoperatively
Time frame: 90 days post-surgery
The occurrence of a surgical site infection (SSI) following central nervous system tumor surgery, diagnosed according to the U.S. National Healthcare Safety Network (NHSN) criteria. Diagnosis will be adjudicated by a blinded independent endpoint adjudication committee.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 30 Jan 2026.
- Individual participant dataSharing planned: Yes. De-identified individual participant data underlying the results reported in this article (including demographics, clinical characteristics, model input variables, and primary endpoint) will be shared. The study protocol, statistical analysis plan, and informed consent form will also be made available. Data will become available following publication of the primary results in a peer-reviewed journal and will be accessible for at least 5 years. Access will be granted to researchers whose methodologically sound proposals have been approved by a scientific review committee, via a controlled-access data repository or upon request.
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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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing ML-Based Enhanced Intervention Package for SSI Prevention and Standard Postoperative Care in people with Surgical Site Infection (SSI) and Central Nervous System Tumor, run by Ming Yang 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 5 inclusion and 6 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: looking for participants now, as of the sponsor's last update on 30 Jan 2026. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Ming Yang, MD (+8613810655237, yangming@cicams.ac.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Incidence of surgical site infection within 90 days postoperatively (time frame: 90 days post-surgery). 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 30 Jan 2026; AzTrials last refreshed its copy on 7 Nov 2026.