Risk of Severe Outcomes From COVID-19 in Immunocompromised People During the Omicron Era: A Systematic Review and Meta-Analysis
Notice bibliographique
Résumé
Abstract Key Points Question: What are the risks of severe outcomes from COVID-19 in people with immunocompromising/immunosuppressive (IC/IS) conditions in the Omicron era? Findings: This systematic review and meta-analysis found increased risk of severe outcomes for people with IC/IS conditions (e.g., autoimmunity, cancer, liver disease, renal disease, transplant) compared with people without the respective conditions. Of all meta-analyzed conditions, transplant recipients had the highest risk of severe COVID-19 outcomes, compared with non-transplant recipients or the general population. Meaning: People with IC/IS conditions remain at increased risk of severe outcomes from COVID-19 during the Omicron era; continued preventative measures and personalized care are crucial. Importance This is the first meta-analysis to investigate the risk of severe outcomes for individuals with immunocompromising/immunosuppressive (IC/IS) conditions specifically in the Omicron era. Objective To assess the risk of mortality and hospitalization from COVID-19 in people with IC/IS conditions compared with people without IC/IS conditions during the Omicron era. Data Sources A systematic search of Embase, MEDLINE, PubMed, Europe PMC, Latin American and Caribbean Health Sciences Literature, Cochrane COVID-19 Study Register, and WHO COVID-19 Database was performed to identify studies published between 1 January 2022 and 13 March 2024. Study Selection Inclusion criteria were observational studies that included people (all ages) with at least 1 of the following conditions: IC/IS unspecified groups, transplant (solid organ, stem cells, or bone marrow), any malignancy, autoimmune diseases, any liver diseases, chronic or end-stage kidney disease, and advanced/untreated HIV. In total, 72 studies were included in the review, of which 66 were included in the meta-analysis. Data Extraction and Synthesis Data were extracted by one reviewer and verified by a second. Studies were synthesized quantitively (meta-analysis) using random-effect models. PRISMA guidelines were followed. Main Outcomes and Measures Evaluated outcomes were risks of death, hospitalization, intensive care unit (ICU) admission, and any combination of these outcomes. Odds ratios, hazard ratios, and rate ratios were extracted; pooled relative risk (RR) and 95% confidence intervals (CI) were calculated. Results Minimum numbers of participants per IC/IS condition ranged from 12 634 to 3 287 816. Risks of all outcomes were increased in people with all meta-analyzed IC/IS conditions compared with people without the respective conditions. Of all meta-analyzed IC/IS conditions, transplant recipients had the highest risk of death (RR, 6.78; 95% CI, 4.41-10.43; P <.001), hospitalization (RR, 6.75; 95% CI, 3.41-13.37; P <.001), and combined outcomes (RR, 8.65; 95% CI, 4.01-18.65; P <.001), while participants in the unspecified IC/IS group had the highest risk of ICU admission (RR, 3.38; 95% CI, 2.37-4.83; P <.001) compared with participants without the respective IC/IS conditions or general population. Conclusions In the Omicron era, people with IC/IS conditions have a substantially higher risk of death and hospitalization from COVID-19 than people without these conditions.
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 | 0,011 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,013 | 0,035 |
| Bibliométrie | 0,005 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| 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 ».