Clinical trial NCT06052527: Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection (PASC) and Influenza Treatment System With Machine Learning
Official title: Autonomous Covid-19, Post-Acute Sequelae of SARS-CoV-2 Infection (PASC) and Influenza Treatment System With Machine Learning in Outpatient Settings
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: COVID-19
Post-COVID-19 Syndrome
Influenza
Lead sponsor: Lizora LLC
Sponsor class: INDUSTRY
Collaborators: name: Sheng'ai Traditional Chinese Medicine Hospital
First posted: 2023-09-25
Enrollment: 27
Sex: ALL
Minimum age (years): 14
Maximum age (years): 95
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
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.

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.

Eligibility criteria: 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)

Primary outcomes:
measure: Classification Accuracy
timeFrame: 1 Day
Secondary outcomes:
measure: Hospitalization Rate and Death
timeFrame: 28 Days
Other outcomes:
measure: Symptom Alleviation
timeFrame: 28 Days
measure: Re-infection Cases
timeFrame: 28 days
Locations:
city: Kunming
country: China
facility: Sheng'Ai Traditional Medicine Hospital
state: Yunnan
Study officials:
affiliation: Lizora LLC
name: jiale xian, MHA
role: STUDY_CHAIR
References: