Advance Chronic Liver Disease (ACLD)AI-ACLDNCT07721454
AI-ACLD Study: Artificial Intelligence in Advanced Chronic Liver Disease
An observational study of Advance Chronic Liver Disease (ACLD), run by Antonio Galante at 1 site in Switzerland.
Trial summary
The research project studies the possibility of using an artificial intelligence-based system in patients with advanced chronic liver disease (liver cirrhosis) to record variations in a patient's health status, with the aim of early identification of clinical improvement or deterioration. Read more about this study
- Who is it for?
- Ages 18 to 75 years
- Conditions the study is for
- Advance Chronic Liver Disease (ACLD)
- What is being tested?
- Apple Watch
- Type of treatment
- Medical device
- How many people
- 8 participants
- Where
- 1 siteSwitzerland
- Study dates
- 29 Dec 2022to 17 Jan 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 18 to 75 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients hospitalized at Ente Ospedaliero Cantonale (EOC) in Lugano or Bellinzona or patients followed at the Department for Gastroenterology and Hepatology, Ente Ospedaliero Cantonale will be assessed for inclusion in the study
Who may be able to join
- Adults aged 18-75 years
- Diagnosis of advanced chronic liver disease (ACLD).
- Either:
- hospitalized for hepatic decompensation or acute-on-chronic liver failure (ACLF), including ascites, hepatorenal syndrome, hepatic encephalopathy, bacterial infection, gastrointestinal bleeding, or jaundice; or
- outpatient with Child-Pugh B cirrhosis and no evidence of hepatic decompensation or ACLF at enrolment.
- Willing and able to provide written informed consent.
Who cannot join
- Inability or refusal to provide written informed consent
- Inability to wear or correctly use the Apple Watch
- Patients with hepatocellular carcinoma beyond the Milan Criteria (one lesion up to 5 cm or 3 lesions up to 3 cm in diameter)
- Presence of hepatic decompensation or ACLF
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Application of Artificial Intelligence Using Wearable Technology in Patients With Advanced Chronic Liver Disease (ACLD): a Trajectomics Approach.
The research project studies the possibility of using an artificial intelligence-based system in patients with advanced chronic liver disease (liver cirrhosis) to record variations in a patient's health status, with the aim of early identification of clinical improvement or deterioration. The system is based on the collection and processing of various clinical parameters through an Apple Watch. The study aims to evaluate whether the data generated by this system correlate with patients' clinical evolution and whether its use may ultimately contribute to improved care management and quality of life.
- Conditions
- Advance Chronic Liver Disease (ACLD)
- Being tested
- Apple Watch
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Apple WatchDevice
Apple Watch has been used to specifically monitor patients with liver cirrhosis, who worn it for the period specified by the study
What is being measured
The primary outcome is the main question the study is designed to answer.
Feasibility and accuracy of machine learning analysis of individual health data collected by wearable device.
The primary outcome is to assess the feasibility and accuracy of machine learning analysis of individual health data collected by wearable device and to describe their patterns during hospitalization due to symptoms of decompensation or ACLF and in outpatients until hospitalization due to decompensation or ACLF in patients with liver cirrhosis. Health data continuously collected through a dedicated wearable device application comprise: heart rate and heart rate variability (HR; HRV), oxygen saturation (SpO₂), ECG (QRS, PQ, PT Tpe interval), sleep quality and duration, daily step count, tremor intensity (Hz), typing speed (taps/time).
The single unit of measure used to assess the feasibility of the wearable device is the usable data acquisition rate (%), defined as the percentage of monitoring data successfully collected and suitable for analysis.
Measured: From enrollment to the end of the study (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 2026
- Study start29 Dec 2022
- Primary completion17 Jan 2024
- Study completion17 Jan 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Advance Chronic Liver Disease (ACLD)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
- Cohort
- Time perspective
- Prospective
- Enrolment
- 8 participants (actual)
Sponsor and investigators
- Lead sponsor
- Antonio Galante
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Antonio Galante, Fondazione Epatocentro Ticino
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07721454
- Sponsor's protocol ID
- AI-ACLD Study
- Acronym
- AI-ACLD
- Status last verified
- Jul 2026
- First submitted
- 16 Jul 2026
- Last updated
- 23 Jul 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 23 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Application of Artificial Intelligence Using Wearable Technology in Patients With Advanced Chronic Liver Disease (ACLD): a Trajectomics Approach.
- ClinicalTrials.gov ID
- NCT07721454
- Acronym / sponsor ID
- AI-ACLD / AI-ACLD Study
- Conditions
- Advance Chronic Liver Disease (ACLD)
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 8 participants (actual)
- Lead sponsor
- Antonio GalanteUniversity, hospital or other
- Study start
- 29 Dec 2022 (actual)
- Primary completion
- 17 Jan 2024 (actual)
- Study completion
- 17 Jan 2024 (actual)
- First posted
- 23 Jul 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.
The research project studies the possibility of using an artificial intelligence-based system in patients with advanced chronic liver disease (liver cirrhosis) to record variations in a patient's health status, with the aim of early identification of clinical improvement or deterioration. The system is based on the collection and processing of various clinical parameters through an Apple Watch. The study aims to evaluate whether the data generated by this system correlate with patients' clinical evolution and whether its use may ultimately contribute to improved care management and quality of life.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 to 75 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients hospitalized at Ente Ospedaliero Cantonale (EOC) in Lugano or Bellinzona or patients followed at the Department for Gastroenterology and Hepatology, Ente Ospedaliero Cantonale will be assessed for inclusion in the study
Key inclusion criteria (6 listed)
- Adults aged 18-75 years
- Diagnosis of advanced chronic liver disease (ACLD).
- Either:
- hospitalized for hepatic decompensation or acute-on-chronic liver failure (ACLF), including ascites, hepatorenal syndrome, hepatic encephalopathy, bacterial infection, gastrointestinal bleeding, or jaundice; or
- outpatient with Child-Pugh B cirrhosis and no evidence of hepatic decompensation or ACLF at enrolment.
Key exclusion criteria (4 listed)
- Inability or refusal to provide written informed consent
- Inability to wear or correctly use the Apple Watch
- Patients with hepatocellular carcinoma beyond the Milan Criteria (one lesion up to 5 cm or 3 lesions up to 3 cm in diameter)
- Presence of hepatic decompensation or ACLF
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 |
|---|---|---|
| Apple WatchApple Watch has been used to specifically monitor patients with liver cirrhosis, who worn it for the period specified by the study | Device | – |
Primary outcome
Feasibility and accuracy of machine learning analysis of individual health data collected by wearable device.
Time frame: From enrollment to the end of the study (6 months)
The primary outcome is to assess the feasibility and accuracy of machine learning analysis of individual health data collected by wearable device and to describe their patterns during hospitalization due to symptoms of decompensation or ACLF and in outpatients until hospitalization due to decompensation or ACLF in patients with liver cirrhosis. Health data continuously collected through a dedicated wearable device application comprise: heart rate and heart rate variability (HR; HRV), oxygen saturation (SpO₂), ECG (QRS, PQ, PT Tpe interval), sleep quality and duration, daily step count, tremor intensity (Hz), typing speed (taps/time). The single unit of measure used to assess the feasibility of the wearable device is the usable data acquisition rate (%), defined as the percentage of monitoring data successfully collected and suitable for analysis.
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 23 Jul 2026.
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 Advance Chronic Liver Disease (ACLD), run by Antonio Galante at 1 site in Switzerland.
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 6 inclusion and 4 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 23 Jul 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 Switzerland. 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?
Feasibility and accuracy of machine learning analysis of individual health data collected by wearable device. (time frame: From enrollment to the end of the study (6 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 2026.