Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection (PASC) and Influenza Treatment System With Machine Learning

Sponsor
Lizora LLC (Industry)
Overall Status
Enrolling by invitation
CT.gov ID
NCT06052527
Collaborator
Sheng'ai Traditional Chinese Medicine Hospital (Other)
27
1
3.5
7.7

Study Details

Study Description

Brief Summary

This is an open-tabled, one-arm observatory trial to assess the effectiveness and safety of the Autonomous Treatment System Based on Machine Learning in patients with Covid-19, Post-Acute Sequelae of SARS-CoV-2 infection and influenza.

Condition or Disease Intervention/Treatment Phase
  • Other: Autonomous Treatment System for Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection and Influenza Based on Machine Learning

Detailed Description

This study has enrolled 27 patients diagnosed with Covid-19, Post-Acute Sequelae of SARS-CoV-2 infection, and influenza. Of these patients, 26 are outpatients, and 1 is hospitalized. After screening based on the inclusion and exclusion criteria, eligible patients will receive prescriptions recommended by the Autonomous Treatment System Based on Machine Learning in this observational trial.

The objectives of this study are:
  1. To compare the classifications made by our machine learning system with those by physicians to assess the model's reliability and accuracy;

  2. To evaluate Covid-19-related hospitalizations or deaths from any cause through day 28;

  3. To determine if the machine learning system's recommended prescription alleviates symptoms of Covid-19, Post-Acute Sequelae of SARS-CoV-2 infection, and influenza;

  4. To monitor participants who tested positive for the Covid-19 for 28 days after initiating treatment, looking for potential rebound cases.

Participants will use an online application to receive the recommended prescription results and will forward these results to a physician for verification. Patients are instructed to complete the online analysis every 3 days or whenever their symptoms change, whichever comes first. They are also asked to adhere to the prescribed medication regimen. Research physicians will conduct follow-ups with patients every 3 days via phone calls. The potential treatments patients may receive include any of the following Traditional Chinese Medicine formulas: LizCovidCure-1, LizCovidCure-2, LizCovidCure-3, LizCovidCure-4, and LizCovid-5.

Study Design

Study Type:
Observational [Patient Registry]
Anticipated Enrollment :
27 participants
Observational Model:
Cohort
Time Perspective:
Prospective
Official Title:
Autonomous Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection (PASC) and Influenza Treatment System With Machine Learning in Outpatient Settings
Actual Study Start Date :
Jun 16, 2023
Anticipated Primary Completion Date :
Sep 30, 2023
Anticipated Study Completion Date :
Oct 1, 2023

Arms and Interventions

Arm Intervention/Treatment
Active Covid-19 Infection

Patients with positive SARS-CoV-2 rapid antigen test results within 30 days before the start of the study will be administered pre-defined TCM prescriptions recommended by the Autonomous Treatment System based on machine learning

Other: Autonomous Treatment System for Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection and Influenza Based on Machine Learning
A novel treatment recommendation system for Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection and Influenza, which is based on machine learning

Post-Covid-19 Syndrome

Patients with positive Covid-19 antigen test results obtained more than 30 days before the start of the study will be administered pre-defined TCM prescriptions recommended by the Autonomous Treatment System based on machine learning.

Other: Autonomous Treatment System for Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection and Influenza Based on Machine Learning
A novel treatment recommendation system for Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection and Influenza, which is based on machine learning

Influenza

Patients with negative SARS-CoV-2 rapid antigen test results and who are diagnosed with influenza will be administered pre-defined TCM prescriptions recommended by the Autonomous Treatment System based on machine learning.

Other: Autonomous Treatment System for Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection and Influenza Based on Machine Learning
A novel treatment recommendation system for Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection and Influenza, which is based on machine learning

Outcome Measures

Primary Outcome Measures

  1. Classification Accuracy [1 Day]

    compare the classifications made by our machine learning system with those by physicians, to assess the model's reliability

Secondary Outcome Measures

  1. Hospitalization Rate and Death [28 Days]

    we assess Covid-19-related hospitalization or death from any cause through day 28

Other Outcome Measures

  1. Symptom Alleviation [28 Days]

    Days of symptom disappearance

  2. Re-infection Cases [28 days]

    Number of cases with recurrence-infection after treatment

Eligibility Criteria

Criteria

Ages Eligible for Study:
15 Years to 95 Years
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
No
Inclusion Criteria:
  • Either male or female (15 years or older), and their COVID-19 vaccination status was not a factor for inclusion.

  • Subjects with any high-risk conditions

  • Subjects with positive sars-cov-2 rapid antigen results in 30 days

  • Subjects with post Covid-19 syndrome

Exclusion Criteria:
  • pregnant individuals

  • subjects with known histories of allergic reactions to medical herbs commonly used in Traditional Chinese Medicine (TCMs)

Contacts and Locations

Locations

Site City State Country Postal Code
1 Sheng'Ai Traditional Medicine Hospital Kunming Yunnan China 650000

Sponsors and Collaborators

  • Lizora LLC
  • Sheng'ai Traditional Chinese Medicine Hospital

Investigators

  • Study Chair: jiale xian, MHA, Lizora LLC

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
Lizora LLC
ClinicalTrials.gov Identifier:
NCT06052527
Other Study ID Numbers:
  • Liz2023Covid19
First Posted:
Sep 25, 2023
Last Update Posted:
Sep 26, 2023
Last Verified:
Sep 1, 2023
Individual Participant Data (IPD) Sharing Statement:
No
Plan to Share IPD:
No
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No
Additional relevant MeSH terms:

Study Results

No Results Posted as of Sep 26, 2023