Immune-Mediated Mechanisms in Patients Testing Positive for SARS-CoV-2: Protocol for a Multianalysis Study
Notice bibliographique
Résumé
BACKGROUND: The novel coronavirus has a high mortality rate (over 1% for patients older than 50 years). This can only be partially ascribed to other comorbidities. A possible explanation is a factor that assures a prompt response to SARS-CoV-2 in younger people, independent from the novelty of the virus itself. A factor is believed to stimulate the immune system and provide immunity against more antigens. The only external stimulation received by healthy people is vaccination (eg, the diphtheria, tetanus, and pertussis [DTP] vaccine). One hypothesis is that vaccination helps develop specific immunity but generates sprouting immunity against antigens in transit. The underlying immunological phenomena are the "bystander effect" and "trained immunity." The developed immunity gives protection for years until it naturally fades out. After the fifth decade of life, the immune system is almost incompetent when a viral infection occurs, and thus, at this stage, the novel coronavirus can enter the body and cause acute respiratory distress syndrome. OBJECTIVE: The initial aim is to demonstrate that blood monocytes and natural killer cells show overpowering hyperactivity, while CD4+ and CD8+ T cells experience impediments to their defensive functions in patients with severe SARS-CoV-2 infection. The secondary objectives are to correlate clinical data and vaccination history with laboratory immune patterns in order to identify protective factors. Subsequently, we are also interested in characterizing the phenotypes and state of the degree of activation of peripheral blood mononuclear cells, including monocytes, natural killer cells, and CD4+ and CD8+ T cells, in healthy subjects vaccinated with the Pfizer vaccine. METHODS: Data will be collected using the following 3 approaches: (1) an experimental analysis to study the innate immune response and to identify genetic profiles; (2) an epidemiological analysis to identify the patients' vaccination history; and (3) a clinical analysis to detect the immunological profile. RESULTS: The protocol was approved by the Ethics Committee on April 16, 2020, and the study started on April 27, 2020. As of February 2021, enrollment has been completed. Immunological analysis is ongoing, and we expect to complete this analysis by December 2022. CONCLUSIONS: We will recognize different populations of patients, each one with a specific immunological pattern in terms of cytokines, soluble factor serum levels, and immune cell activity. Anamnestic data, such as preceding vaccinations and comorbidities, biochemical findings like lymphocyte immunophenotyping, and pre-existing persistent cytomegalovirus infection, allow depicting the risk profile of severe COVID-19. Proof of the roles of these immunological phenomena in the development of COVID-19 can be the basis for the implementation of therapeutic immunomodulatory treatments. TRIAL REGISTRATION: ClinicalTrials.gov NCT04375176; https://clinicaltrials.gov/ct2/show/NCT04375176. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/29892.
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Comment cette classification a été obtenuedéplier
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, 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 ».