Complete Blood Count ReviewNCT07607184
Multi-center Validation Study of a Large Language Model-based Intelligent Agent for Blood Cell Analysis
An observational study of Complete Blood Count Review, run by Huashan Hospital.
Trial summary
I. Study Background: Currently, in most medical institutions, the review of blood cell analysis still heavily relies on manual verification by laboratory staff. This process requires a comprehensive analysis of instrument parameters, alarm flags, historical comparison results, and, when necessary, microscopic… Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Complete Blood Count Review
- What is being tested?
- LLM-Assisted Review Group
- How many people
- 20,000 participants
- Where
- No sites listed yet
- Study dates
- 14 May 2026to 31 Aug 2027
- How long will I take part?
- 1 Year
- 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 Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: The study subjects were consecutive individuals undergoing routine blood tests at each center, with no restrictions on gender or age. After inclusion, samples entered the corresponding review process based on the study week, with preliminary and secondary reviews conducted by predefined workflows and qualified personnel, respectively.
Who may be able to join
- Subjects who underwent routine blood tests in the outpatient, emergency, or inpatient departments of the participating centers during the study period.
- Corresponding samples must have complete instrument results, review trails, and report timestamp records.
- Approved for inclusion by the Ethics Committee.
Who cannot join
- Samples collected during periods of instrument malfunction or interface transmission anomalies.
- Missing key research data, particularly samples where the final review conclusion or key timestamps cannot be confirmed.
- Subjects or their legal representatives explicitly refuse to participate in the study.
About this study
- Study Background: Currently, in most medical institutions, the review of blood cell analysis still heavily relies on manual verification by laboratory staff. This process requires a comprehensive analysis of instrument parameters, alarm flags, historical comparison results, and, when necessary, microscopic examination. However, with the increasing volume of test samples and the high concentration of review tasks during peak hours, the traditional manual review model increasingly shows problems such as prolonged turnaround time (TAT), uneven workload distribution, and decreased consistency in reviews. In recent years, intelligent review systems based on Large Language Models (LLM) have shown potential in analyzing abnormal results and stratifying sample risks by integrating preset rules, clinical diagnostic information, and multi-dimensional laboratory data, which is expected to optimize the review workflow.
II. Study Objective: To evaluate the difference in overall sample review turnaround time between the experimental process and the control process during the formal study phase, and to test its superiority.
Read more
III. Subjects: The investigators need to recruit approximately 20,000 subjects, regardless of age or gender.
IV. Study Procedures: If participants agree to participate in the study, participants only need to allow us to use participants test results after participants have completed your routine blood test (CBC).
- Risks and Benefits:
- Risks: This study poses no risk to the subjects. The investigators only use the result data of patients after participants have had their routine blood test; there is no need for patients to undergo additional blood draws.
- Benefits: It will shorten the turnaround time for routine blood test results and share the workload of doctors in reviewing these results.
VI. Privacy: All of participants information will be kept strictly confidential and will only be used for this scientific research.
- Conditions
- Complete Blood Count Review
- Being tested
- LLM-Assisted Review Group
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
LLM-Assisted Review GroupOther
This study introduces an intelligent auxiliary review system based on a medical Large Language Model (LLM), aimed at optimizing the traditional CBC report review process. The core functions and intervention mechanisms are as follows:
Multi-source Data Integration: The system integrates seamlessly with the Laboratory Information System (LIS) to automatically retrieve patient demographics (age, sex), current CBC indices, historical results, and clinical diagnoses.
Deep Analysis and Anomaly Detection: Unlike traditional rule-based auto-verification, this system leverages the reasoning capability of LLMs to perform multidimensional clinical logic checks. It identifies out-of-range values and interprets their clinical significance by combining them with patient history (e.g., distinguishing physiological fluctuations from pathological changes).
| Study group | Role | What they receive |
|---|---|---|
| LLM-Assisted Review Group | Not described Receives: Other: LLM-Assisted Review Group | |
| Standard Manual Review Group | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
Overall Report Turnaround Time
Measured: one year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 May 2026
- Study start14 May 2026 (estimated)
- Primary completion31 Aug 2027 (estimated)
- Study completion31 Aug 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Complete Blood Count ReviewStudies 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
- 20,000 participants (estimated)
- Target duration
- 1 Year
Sponsor and investigators
- Lead sponsor
- Huashan Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- Peking University First Hospital, The Fifth Affiliated Hospital of Wenzhou Medical University & Lishui Central Hospital
- Responsible party
- Principal investigator, Ming Guan, Huashan Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07607184
- Sponsor's protocol ID
- KY2026-084
- Status last verified
- May 2026
- First submitted
- 19 May 2026
- Last updated
- 28 May 2026
- Results posted
- No
Study at a glance
From the registry record, last updated by the sponsor on 28 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Multi-center Validation Study of a Large Language Model-based Intelligent Agent for Blood Cell Analysis
- ClinicalTrials.gov ID
- NCT07607184
- Acronym / sponsor ID
- KY2026-084
- Conditions
- Complete Blood Count Review
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 20,000 participants (estimated)
- Lead sponsor
- Huashan HospitalUniversity, hospital or other
- Collaborators
- Peking University First Hospital, The Fifth Affiliated Hospital of Wenzhou Medical University & Lishui Central Hospital
- Study start
- 14 May 2026 (estimated)
- Primary completion
- 31 Aug 2027 (estimated)
- Study completion
- 31 Aug 2027 (estimated)
- First posted
- 26 May 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: Currently, in most medical institutions, the review of blood cell analysis still heavily relies on manual verification by laboratory staff. This process requires a comprehensive analysis of instrument parameters, alarm flags, historical comparison results, and, when necessary, microscopic examination. However, with the increasing volume of test samples and the high concentration of review tasks during peak hours, the traditional manual review model increasingly shows problems such as prolonged turnaround time (TAT), uneven workload distribution, and decreased consistency in reviews. In recent years, intelligent review systems based on Large Language Models (LLM) have shown potential in analyzing abnormal results and stratifying sample risks by integrating preset rules, clinical diagnostic information, and multi-dimensional laboratory data, which is expected to optimize the review workflow.
II. Study Objective: To evaluate the difference in overall sample review turnaround time between the experimental process and the control process during the formal study phase, and to test its superiority.
III. Subjects: The investigators need to recruit approximately 20,000 subjects, regardless of age or gender.
IV. Study Procedures: If participants agree to participate in the study, participants only need to allow us to use participants test results after participants have completed your routine blood test (CBC).
- Risks and Benefits:
- Risks: This study poses no risk to the subjects. The investigators only use the result data of patients after participants have had their routine blood test; there is no need for patients to undergo additional blood draws.
- Benefits: It will shorten the turnaround time for routine blood test results and share the workload of doctors in reviewing these results.
VI. Privacy: All of participants information will be kept strictly confidential and will only be used for this scientific research.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 1 Year
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| LLM-Assisted Review Group | – | Other: LLM-Assisted Review Group |
| Standard Manual Review Group | – | – |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- Study population
- The study subjects were consecutive individuals undergoing routine blood tests at each center, with no restrictions on gender or age. After inclusion, samples entered the corresponding review process based on the study week, with preliminary and secondary reviews conducted by predefined workflows and qualified personnel, respectively.
Key inclusion criteria (3 listed)
- Subjects who underwent routine blood tests in the outpatient, emergency, or inpatient departments of the participating centers during the study period.
- Corresponding samples must have complete instrument results, review trails, and report timestamp records.
- Approved for inclusion by the Ethics Committee.
Key exclusion criteria (3 listed)
- Samples collected during periods of instrument malfunction or interface transmission anomalies.
- Missing key research data, particularly samples where the final review conclusion or key timestamps cannot be confirmed.
- Subjects or their legal representatives explicitly refuse to participate 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 |
|---|---|---|
| LLM-Assisted Review GroupThis study introduces an intelligent auxiliary review system based on a medical Large Language Model (LLM), aimed at optimizing the traditional CBC report review process. The core functions and intervention mechanisms are as follows: Multi-source Data Integration: The system integrates seamlessly with the Laboratory Information System (LIS) to automatically retrieve patient demographics (age, sex), current CBC indices, historical results, and clinical diagnoses. Deep Analysis and Anomaly Detection: Unlike traditional rule-based auto-verification, this system leverages the reasoning capability of LLMs to perform multidimensional clinical logic checks. It identifies out-of-range values and interprets their clinical significance by combining them with patient history (e.g., distinguishing physiological fluctuations from pathological changes). | Other | LLM-Assisted Review Group |
Primary outcome
Overall Report Turnaround Time
Time frame: one year
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 28 May 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.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
An observational study of Complete Blood Count Review, run by Huashan Hospital.
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 3 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: opening soon, as of the sponsor's last update on 28 May 2026. Status can change between updates, so confirm with the study contact before making plans.
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?
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?
Overall Report Turnaround Time (time frame: one year). 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 28 May 2026.