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NCT Number: NCT06052527

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

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.

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Key information

Conditions

COVID-19 Chronic Disease Coronaviridae Infections Coronavirus Infections Disease Attributes Infections Influenza Influenza, Human Lung Diseases Nidovirales Infections Orthomyxoviridae Infections Pathologic Processes Pathological Conditions, Signs and Symptoms Pneumonia Pneumonia, Viral Post-Acute COVID-19 Syndrome Post-COVID-19 Syndrome Post-Infectious Disorders RNA Virus Infections Respiratory Tract Diseases Respiratory Tract Infections Virus Diseases

Age range

14 year–95 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Sheng'Ai Traditional Medicine Hospital

Kunming, Yunnan, 650000, China

About this study

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:

  • To compare the classifications made by our machine learning system with those by physicians to assess the model's reliability and accuracy;
  • To evaluate Covid-19-related hospitalizations or deaths from any cause through day 28;
  • 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;
  • 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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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)

Treatment and study plan

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

Primary outcomes

  1. Classification Accuracy

    Time frame: 1 Day

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

Secondary outcomes

  1. Hospitalization Rate and Death

    Time frame: 28 Days

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

Other outcomes

  1. Symptom Alleviation

    Time frame: 28 Days

    Days of symptom disappearance

  2. Re-infection Cases

    Time frame: 28 days

    Number of cases with recurrence-infection after treatment

Sponsors and collaborators

Lead sponsor

Lizora LLC

Industry

Collaborators

  • Sheng'ai Traditional Chinese Medicine Hospital

Registry information

Official study title

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

Important dates

Study start
2023
Primary completion
2023
Study completion
2023
First posted
Sep 25, 2023
Registry last updated
Dec 29, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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