Acute Lung Injury(ALI)NCT07070362
Digital Early Warning System for Acute Lung Injury in Liver Surgery
An observational study of Acute Lung Injury(ALI) and Liver Cirrhosis, run by Beijing Tsinghua Chang Gung Hospital at 4 sites in China.
Trial summary
This study aims to develop an explainable machine learning model that takes into account the characteristics of cardiopulmonary interactions. This model will enable early prediction of acute lung injury (ALI) in patients undergoing major liver surgery. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Acute Lung Injury(ALI), Liver Cirrhosis, ARDS, Human
- How many people
- 3,000 participants
- Where
- 4 sitesChina
- Study dates
- 1 Nov 2024to 30 Nov 2027
- Phase
- Observational
- 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 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: * Patient refusal * Presence of comorbidities affecting outcome assessment * Incomplete outcome records * Postoperative follow-up failure * Participation in other studies that may interfere with outcome assessment
Who may be able to join
- Age ≥ 18 years
- Undergoing major liver surgery (including two-segment or more hepatectomy, liver transplantation, etc.)
- Voluntary participation with signed informed consent
Who cannot join
None listed.
Trial locations and contacts
4 sites in 1 country. Contact the study team or a site near you to ask about taking part.
China4 sites, 4 recruiting
- Recruiting
Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine，Tsinghua University
Beijing, Beijing Municipality, 102218
- Recruiting
Peking University International Hospital
Beijing
Lan Yao, Dr., 86+13671010819, yaolan@pkuih.edu.cn
- Recruiting
Southwest Hospital, The First Affiliated Hospital of Army Medical University
Chongqing
Zhiyu Chen, Dr., 86+18515886827, fixseve@qq.com
- Recruiting
Huangdao District People's Hospital of Qingdao
Qingdao
Gang Wang, Dr., +86-13051535765, 826387501@qq.com
About this study
Official title: The Construction of a Digital Intelligence Early Warning System for the Whole Process of Acute Lung Injury in Liver Surgery Based on Cardiopulmonary Interaction Characteristics
This study aims to develop an explainable machine learning model that takes into account the characteristics of cardiopulmonary interactions. This model will enable early prediction of acute lung injury (ALI) in patients undergoing major liver surgery. The research will create a digital early-warning system for ALI, thereby supporting clinical diagnosis and treatment decisions. This, in turn, should help reduce the incidence and mortality rates associated with ALI.
Read the detailed description
This study will leverage parameters to predict ALI in patients undergoing major liver surgery. Specifically, the research will collect data from preoperative, intraoperative, and postoperative phases. Machine learning algorithms-including logistic regression, random forest, support vector machines (SVM), and neural networks-will be used to develop and validate the prediction model. Model performance will be evaluated using metrics such as accuracy, sensitivity, specificity, and the receiver operating characteristic (ROC) curve. The ultimate objective is to develop a highly accurate and interpretable model that can be integrated into a digital early-warning system for clinical application.
- Conditions
- Acute Lung Injury(ALI), Liver Cirrhosis, ARDS, Human, MASLD, MASLD/MASH (Metabolic Dysfunction-Associated Steatotic Liver Disease / Metabolic Dysfunction-Associated Steatohepatitis), NAFLD (Nonalcoholic Fatty Liver Disease)
- Keywords
- Digital Intelligence, Acute Lung Injury, PPCs, Liver Surgery, Cardiopulmonary Interaction;
- Medical subject headings
- Acute Lung Injury, Liver Cirrhosis, Respiratory Distress Syndrome, Non-alcoholic Fatty Liver Disease, Carcinoma, Hepatocellular
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Multicentre External Validation Cohort | Consecutive eligible adults who underwent major hepatobiliary or pancreatic surgery or liver transplantation at three independent external centres: Peking University International Hospital (WYA), Southwest Hospital of Army Medical University (WYB), and Huangdao District People's Hospital of Qingdao (WYC). The frozen full perioperative M3 model developed at BTCH was applied using the same predictor definitions, imputation rules, model parameters, and classification threshold, without centre-specific model fitting or recalibration. Centre-specific and pooled validation analyses were performed. This was a retrospective observational cohort; no intervention was assigned and routine clinical care was not altered. | |
| BTCH Development and Validation Cohort | Consecutive eligible adults who underwent major hepatobiliary or pancreatic surgery or liver transplantation at Beijing Tsinghua Changgung Hospital (BTCH) between October 16, 2015, and December 24, 2025. The earliest 70% formed the development cohort and the most recent 30% formed the temporal-validation cohort. Model development was confined to the development cohort, and the frozen models were evaluated in the temporal-validation cohort. This was a retrospective observational study; no intervention was assigned and routine clinical care was not altered. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Occurrence of ALI within 7 Days after Surgery
Berlin Definition:
- Onset: Acute exacerbation of known injury or new/worsening respiratory symptoms within 1 week.
- Chest Imaging (X-ray or CT): Bilateral pulmonary shadows not fully explained by exudation, atelectasis, or nodules.
- Pulmonary Edema Etiology: Respiratory failure not fully attributed to heart failure or fluid overload; if no related risk factors, objective tests (e.g., Doppler echocardiography) are needed to exclude hydrostatic pulmonary edema.
- Oxygenation Levels: Mild - With CPAP/PEEP >5 cmH2O, 200 mmHg < PaO2/FiO2 < 300 mmHg; Moderate - With CPAP/PEEP >5 cmH2O, 100 mmHg < PaO2/FiO2 < 200 mmHg; Severe - With CPAP/PEEP >5 cmH2O, PaO2/FiO2 < 100 mmHg.
Measured: Perioperative period (Perioperative): Refers to the entire process from the determination of surgical treatment to postoperative rehabilitation (e.g., from 1 day before surgery to 7 days after surgery).
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Jul 2025
- Study start1 Nov 2024
- Primary completion1 Jun 2027 (estimated)
- Study completion30 Nov 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Acute Lung Injury(ALI)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
- Observational
- Observational model
- Other
- Time perspective
- Other
- Enrolment
- 3,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Beijing Tsinghua Chang Gung Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- Huangdao District People's Hospital of Qingdao, Peking University International Hospital, Southwest Hospital, China
- Responsible party
- Principal investigator, Zhifeng Gao, Beijing Tsinghua Chang Gung Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07070362
- Sponsor's protocol ID
- BRWEP2024W032240113
- Other IDs
- 25254-0-01, （BA）KY2026022, LL-KY-2026008
- Status last verified
- Aug 2026
- First submitted
- 11 Jun 2025
- Last updated
- 17 Aug 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 17 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Construction of a Digital Intelligence Early Warning System for the Whole Process of Acute Lung Injury in Liver Surgery Based on Cardiopulmonary Interaction Characteristics
- ClinicalTrials.gov ID
- NCT07070362
- Acronym / sponsor ID
- BRWEP2024W032240113
- Conditions
- Acute Lung Injury(ALI), Liver Cirrhosis, ARDS, Human, MASLD, MASLD/MASH (Metabolic Dysfunction-Associated Steatotic Liver Disease / Metabolic Dysfunction-Associated Steatohepatitis), NAFLD (Nonalcoholic Fatty Liver Disease)
- Keywords
- Digital Intelligence, Acute Lung Injury, PPCs, Liver Surgery, Cardiopulmonary Interaction;
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 3,000 participants (estimated)
- Lead sponsor
- Beijing Tsinghua Chang Gung HospitalUniversity, hospital or other
- Collaborators
- Huangdao District People's Hospital of Qingdao, Peking University International Hospital, Southwest Hospital, China
- Study start
- 1 Nov 2024 (actual)
- Primary completion
- 1 Jun 2027 (estimated)
- Study completion
- 30 Nov 2027 (estimated)
- First posted
- 17 Jul 2025 (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.
This study aims to develop an explainable machine learning model that takes into account the characteristics of cardiopulmonary interactions. This model will enable early prediction of acute lung injury (ALI) in patients undergoing major liver surgery. The research will create a digital early-warning system for ALI, thereby supporting clinical diagnosis and treatment decisions. This, in turn, should help reduce the incidence and mortality rates associated with ALI.
Detailed description
This study will leverage parameters to predict ALI in patients undergoing major liver surgery. Specifically, the research will collect data from preoperative, intraoperative, and postoperative phases. Machine learning algorithms-including logistic regression, random forest, support vector machines (SVM), and neural networks-will be used to develop and validate the prediction model. Model performance will be evaluated using metrics such as accuracy, sensitivity, specificity, and the receiver operating characteristic (ROC) curve. The ultimate objective is to develop a highly accurate and interpretable model that can be integrated into a digital early-warning system for clinical application.
Study design
- Observational model
- Other
- Time perspective
- Other
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Multicentre External Validation Cohort | – | –Consecutive eligible adults who underwent major hepatobiliary or pancreatic surgery or liver transplantation at three independent external centres: Peking University International Hospital (WYA), Southwest Hospital of Army Medical University (WYB), and Huangdao District People's Hospital of Qingdao (WYC). The frozen full perioperative M3 model developed at BTCH was applied using the same predictor definitions, imputation rules, model parameters, and classification threshold, without centre-specific model fitting or recalibration. Centre-specific and pooled validation analyses were performed. This was a retrospective observational cohort; no intervention was assigned and routine clinical care was not altered. |
| BTCH Development and Validation Cohort | – | –Consecutive eligible adults who underwent major hepatobiliary or pancreatic surgery or liver transplantation at Beijing Tsinghua Changgung Hospital (BTCH) between October 16, 2015, and December 24, 2025. The earliest 70% formed the development cohort and the most recent 30% formed the temporal-validation cohort. Model development was confined to the development cohort, and the frozen models were evaluated in the temporal-validation cohort. This was a retrospective observational study; no intervention was assigned and routine clinical care was not altered. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- * Patient refusal * Presence of comorbidities affecting outcome assessment * Incomplete outcome records * Postoperative follow-up failure * Participation in other studies that may interfere with outcome assessment
Key inclusion criteria (3 listed)
- Age ≥ 18 years
- Undergoing major liver surgery (including two-segment or more hepatectomy, liver transplantation, etc.)
- Voluntary participation with signed informed consent
Key exclusion criteria (0 listed)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Occurrence of ALI within 7 Days after Surgery
Time frame: Perioperative period (Perioperative): Refers to the entire process from the determination of surgical treatment to postoperative rehabilitation (e.g., from 1 day before surgery to 7 days after surgery).
Berlin Definition: 1. Onset: Acute exacerbation of known injury or new/worsening respiratory symptoms within 1 week. 2. Chest Imaging (X-ray or CT): Bilateral pulmonary shadows not fully explained by exudation, atelectasis, or nodules. 3. Pulmonary Edema Etiology: Respiratory failure not fully attributed to heart failure or fluid overload; if no related risk factors, objective tests (e.g., Doppler echocardiography) are needed to exclude hydrostatic pulmonary edema. 4. Oxygenation Levels: Mild - With CPAP/PEEP >5 cmH2O, 200 mmHg < PaO2/FiO2 < 300 mmHg; Moderate - With CPAP/PEEP >5 cmH2O, 100 mmHg < PaO2/FiO2 < 200 mmHg; Severe - With CPAP/PEEP >5 cmH2O, PaO2/FiO2 < 100 mmHg.
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 17 Aug 2026.
- Individual participant dataSharing planned: No
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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.
4 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Acute Lung Injury(ALI) and Liver Cirrhosis, run by Beijing Tsinghua Chang Gung Hospital at 4 sites 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 0 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 17 Aug 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 4 sites 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 Gao Zhifeng, MD (+8615801249466, btchgzf@hotmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Occurrence of ALI within 7 Days after Surgery (time frame: Perioperative period (Perioperative): Refers to the entire process from the determination of surgical treatment to postoperative rehabilitation (e.g., from 1 day before surgery to 7 days after 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 17 Aug 2026; AzTrials last refreshed its copy on 26 Oct 2026.