Reinfection in patients with COVID-19: a systematic review
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Notice bibliographique
Résumé
BACKGROUND: With the continuation of the COVID-19 pandemic, some COVID-19 patients have become reinfected with the virus. Viral gene sequencing has found that some of these patients were reinfected by the different and others by same strains. This has raised concerns about the effectiveness of immunity after infection and the reliability of vaccines. To this end, we conducted a systematic review to assess the characteristics of patients with reinfection and possible causes. METHODS: A systematic search was conducted across eight databases: PubMed, Embase, Web of Science, The Cochrane Library, CNKI, WanFang, VIP and SinoMed from December 1, 2019 to September 1, 2021. The quality of included studies were assessed using JBI critical appraisal tools and Newcastle-Ottawa Scale. RESULTS: This study included 50 studies from 20 countries. There were 118 cases of reinfection. Twenty-five patients were reported to have at least one complication. The shortest duration between the first infection and reinfection was 19 days and the longest was 293 days. During the first infection and reinfection, cough (51.6% and 43.9%) and fever (50% and 30.3%) were the most common symptoms respectively. Nine patients recovered, seven patients died, and five patients were hospitalized, but 97 patients' prognosis were unknown. B.1 is the most common variant strain at the first infection. B.1.1.7, B.1.128 and B.1.351 were the most common variant strains at reinfection. Thirty-three patients were infected by different strains and 9 patients were reported as being infected with the same strain. CONCLUSIONS: Our research shows that it is possible for rehabilitated patients to be reinfected by SARS-COV-2. To date, the causes and risk factors of COVID-19 reinfection are not fully understood. For patients with reinfection, the diagnosis and management should be consistent with the treatment of the first infection. The public, including rehabilitated patients, should be fully vaccinated, wear masks in public places, and pay attention to maintaining social distance to avoid reinfection with the virus.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,000 |
| Bibliométrie | 0,001 | 0,005 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 découle