Analysis of the effectiveness of traditional Chinese medicine in patients with COVID-19: a systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: COVID-19, a disease caused by the SARS-CoV-2 virus, was first identified in China. The clinical picture of COVID-19 varies from mild to severe and the mortality of critically ill patients is high. To date, no specific treatment or with high rates of effectiveness has been discovered for the disease. In contrast, Traditional Chinese Medicine (TCM), throughout history, has played an important role in the treatment of various infectious and epidemic diseases. TCM can provide an effective and personalized treatment, adjusting it specifically for each patient based on the severity of the case. OBJECTIVES: To analyze the effectiveness of TCM in the treatment of COVID-19 and to present information about changes in the clinical condition of sick individuals. MATERIAL AND METHODS: The work is characterized as a systematic review and was carried out based on the acronym PECOS. Inclusion and exclusion criteria were established, with characteristics of the studies to be selected. The search for the articles took place in Pubmed, Science Direct, Scopus and Web of Science databases. To manage the studies found, the StArt tool, a systematic review manager, and Zotero, a reference management software, were used. The studies included in the review went through a quality and risk of bias analysis process, based on the Newcastle Ottawa checklist and proceeded to data extraction. RESULTS: TCM interventions have proven to be beneficial in the treatment for COVID-19, reducing severe symptoms of patients. Herbal formulas are the main methods described that are more effective, in addition to decoction, acupuncture and other therapies characteristic of TCM, which were widely used based on the differentiation of the patient's clinical condition. However, it has been reported that some herbs used in TCM contain nephrotoxins and mutagens and that the toxicological characteristics of most Chinese herbal medicines have not yet been fully understood. Therefore, the safety of using herbal medicines and other TCM techniques used to treat emerging coronavirus infections should be carefully assessed. CONCLUSION: MTC has accumulated thousands of years of experience in the treatment of diseases and is a complementary alternative for the treatment of COVID-19. While the potential for resolution and effectiveness is great, you need to be aware of the challenges and limitations faced by these tools. Even so, TCM practices must be considered given the urgency to treat the growing number of patients infected with the new coronavirus and the viability of TCM experiences.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it