ClinicalTrials.gov
public full text
Public Domain
Vielight RX Plus for the Treatment of COVID-19 Respiratory Symptoms
The objective of this study is to obtain data on the efficacy of the Vielight RX Plus in decreasing time to recovery of symptoms in subjects with COVID-19. The study will be conducted among COVID-19 positive subjects at home in self-isolation via electronic data collection (EDC). There will be no physical contact between the subjects and the Qualified Investigator (QI) or other study staff. This study aims to demonstrate that the Vielight RX Plus is a useful adjunct to standard of care (SOC). We hypothesize that the Vielight RX Plus will accelerate recovery and reduce viral infection severity.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Influence of Prior Infection With COVID-19 on Occurrence of Influenza-like Illness or Acute Respiratory Infection#1170796
- Model of care to promote recovery in older people with long COVID: findings from interviews and a co-design workshop.#171913
- Reward Re-Training: A New Treatment to Address Reward Imbalance During the COVID-19 Pandemic#840820
- Covid-19 Long Haul Preventative and Health Promotion Care Clinical Trial Acceleration Program.#833621
- Cisco-19 Study ECGs#922129
Record · ID 832393
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive