Analysis of the effectiveness of traditional Chinese medicine in patients with COVID-19: a systematic review
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,011 | 0,010 |
| Bibliométrie | 0,009 | 0,009 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».