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

Completed
Conditions
COVID-19
Influenza
Post-COVID-19 Syndrome
Interventions
Other: Autonomous Treatment System for Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection and Influenza Based on Machine Learning
Registration Number
NCT06052527
Lead Sponsor
Lizora LLC
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.

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.

Recruitment & Eligibility

Status
COMPLETED
Sex
All
Target Recruitment
27
Inclusion Criteria
  • Either male or female (14 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)

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Arm && Interventions
GroupInterventionDescription
InfluenzaAutonomous Treatment System for Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection and Influenza Based on Machine LearningPatients 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.
Post-Covid-19 SyndromeAutonomous Treatment System for Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection and Influenza Based on Machine LearningPatients with positive Covid-19 antigen test results obtained more than 60 days before the start of the study will be administered pre-defined TCM prescriptions recommended by the Autonomous Treatment System based on machine learning.
Active Covid-19 InfectionAutonomous Treatment System for Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection and Influenza Based on Machine LearningPatients with positive SARS-CoV-2 rapid antigen test results within 60 days before the start of the study will be administered pre-defined TCM prescriptions recommended by the Autonomous Treatment System based on machine learning
Primary Outcome Measures
NameTimeMethod
Classification Accuracy1 Day

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

Secondary Outcome Measures
NameTimeMethod
Hospitalization Rate and Death28 Days

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

Trial Locations

Locations (1)

Sheng'Ai Traditional Medicine Hospital

🇨🇳

Kunming, Yunnan, China

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