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

COVID-19 Clinical Trial

Official title:

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

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT06052527
• Other study ID #: Liz2023Covid19
• Status: Completed
• Start date: June 16, 2023
• Est. completion date: October 1, 2023

Study information

• Verified date: December 2023
• Source: Lizora LLC
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial 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.

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 information / eligibility

• Status: Completed
• Enrollment: 27
• Est. completion date: October 1, 2023
• Est. primary completion date: September 30, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 14 Years to 95 Years

Eligibility

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)

Related Conditions & MeSH terms

• COVID-19
• Influenza
• Influenza, Human
• Post-COVID-19 Syndrome

Intervention

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

Locations

Country	Name	City	State
China	Sheng'Ai Traditional Medicine Hospital	Kunming	Yunnan

Sponsors (2)

Lead Sponsor	Collaborator
Lizora LLC	Sheng'ai Traditional Chinese Medicine Hospital

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	Symptom Alleviation	Days of symptom disappearance	28 Days
Other	Re-infection Cases	Number of cases with recurrence-infection after treatment	28 days
Primary	Classification Accuracy	compare the classifications made by our machine learning system with those by physicians, to assess the model's reliability	1 Day
Secondary	Hospitalization Rate and Death	we assess Covid-19-related hospitalization or death from any cause through day 28	28 Days