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

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

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.

Study Overview

• Status: Completed
• Conditions: COVID-19; Influenza; Post-COVID-19 Syndrome
• Intervention / Treatment: 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 Type: Observational
• Enrollment (Actual): 27

Contacts and Locations

Study Locations

• China
  • Yunnan
    • Kunming, Yunnan, China, 650000
      • Sheng'Ai Traditional Medicine Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Patients with active SARS-Cov-2 infection within 30 days patients with Post-Acute Sequelae of SARS-CoV-2 infection and patients with influenza.

Description

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 Plan

How is the study designed?

Number of groups / cohorts

3

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
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
Active Covid-19 Infection; Patients 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	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 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.	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

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Classification Accuracy	compare the classifications made by our machine learning system with those by physicians, to assess the model's reliability	1 Day

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Hospitalization Rate and Death	we assess Covid-19-related hospitalization or death from any cause through day 28	28 Days

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Symptom Alleviation	Days of symptom disappearance	28 Days
Re-infection Cases	Number of cases with recurrence-infection after treatment	28 days

Collaborators and Investigators

• Sponsor: Lizora LLC
• Collaborators: Sheng'ai Traditional Chinese Medicine Hospital
• Investigators: Study Chair: jiale xian, MHA, Lizora LLC

Study record dates

Study Major Dates

• Study Start (Actual): June 16, 2023
• Primary Completion (Actual): September 30, 2023
• Study Completion (Actual): October 1, 2023

Study Registration Dates

• First Submitted: September 21, 2023
• First Submitted That Met QC Criteria: September 21, 2023
• First Posted (Actual): September 25, 2023

Study Record Updates

• Last Update Posted (Actual): December 29, 2023
• Last Update Submitted That Met QC Criteria: December 25, 2023
• Last Verified: December 1, 2023

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Pathologic Processes; Coronavirus Infections; Coronaviridae Infections; Nidovirales Infections; RNA Virus Infections; Virus Diseases; Infections; Respiratory Tract Infections; Respiratory Tract Diseases; Pneumonia, Viral; Pneumonia; Lung Diseases; Disease Attributes; Orthomyxoviridae Infections; Chronic Disease; Post-Infectious Disorders; COVID-19; Influenza, Human; Post-Acute COVID-19 Syndrome
• Other Study ID Numbers: Liz2023Covid19

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: No plan to share the individual participant data (IPD).

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No