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

NCT06052527 | Completed DMC

• 1 other identifier: Liz2023Covid19
• Study Type: observational
• Target: 27
• Locations: 1 country
• Sites: 1

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.

Conditions

COVID-19; Post-COVID-19 Syndrome; Influenza

Outcome Measures

Primary Outcomes (1)

• Classification Accuracy

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

  1 Day

Secondary Outcomes (1)

• Hospitalization Rate and Death

  28 Days

Other Outcomes (2)

• Symptom Alleviation

  28 Days

• Re-infection Cases

  28 days

Study Arms (3)

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

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

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

Interventions

Autonomous Treatment System for Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection and Influenza Based on Machine Learning OTHER

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; Influenza; Post-Covid-19 Syndrome

Eligibility Criteria

• Age: 14 Years - 95 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• 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.

You may qualify if:

• Subjects with any high-risk conditions
• Subjects with positive sars-cov-2 rapid antigen results in 30 days
• Subjects with post Covid-19 syndrome

You may not qualify if:

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

Sponsors & Collaborators

• Lizora LLC: lead
• Sheng'ai Traditional Chinese Medicine Hospital: collaborator

Study Sites (1)

Sheng'Ai Traditional Medicine Hospital

Kunming, Yunnan, 650000, China

Location

MeSH Terms

Conditions

COVID-19; Post-Acute COVID-19 Syndrome; Influenza, Human

Condition Hierarchy (Ancestors)

Pneumonia, Viral; Pneumonia; Respiratory Tract Infections; Infections; Virus Diseases; Coronavirus Infections; Coronaviridae Infections; Nidovirales Infections; RNA Virus Infections; Lung Diseases; Respiratory Tract Diseases; Post-Infectious Disorders; Chronic Disease; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Orthomyxoviridae Infections

Study Officials

• jiale xian, MHA

  Lizora LLC

  STUDY CHAIR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 28 Days
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 21, 2023
• First Posted: September 25, 2023
• Study Start: June 16, 2023
• Primary Completion: September 30, 2023
• Study Completion: October 1, 2023
• Last Updated: December 29, 2023

Record last verified: 2023-12

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)