Risk of Severe Outcomes From COVID-19 in Comorbid Populations in the Omicron Era: A Meta-analysis
Notice bibliographique
Résumé
Abstract Importance This is the first meta-analysis to investigate risk of death and hospitalization in individuals with comorbidities, specifically during the Omicron era. Objective To assess the risk of mortality and hospitalization from COVID-19 in individuals with comorbidities in comparison with individuals without comorbidities 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 including people (all ages) with at least 1 of the following comorbidities: cardiovascular/ cerebrovascular disease, chronic lung conditions, diabetes, and obesity. In total, 72 studies were included in the review, of which 68 were meta-analyzed. 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 the 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 comorbidity across included studies ranged from 328 870 for thrombosis to 13 720 480 for hypertension. Risks of death, hospitalization, and the combined outcome were increased in individuals with cerebrovascular disease, COPD, diabetes, respiratory diseases, heart disease, and heart failure versus those without (pooled RRs ranged from 1.27 [heart disease, hospitalization; 95% CI, 1.17-1.38, P < .001] to 1.78 [heart failure, death: 95% CI, 1.46-2.16, P < .001]). Individuals with diabetes and obesity had increased risk of ICU admission (RR: 1.20; 95% CI: 1.04-1.38, P = .0141 and RR: 1.32; 95% CI: 1.11-1.57, P = .00158, respectively). Conclusions During the Omicron era, risk of death and hospitalization from COVID-19 is increased amongst individuals with comorbidities including cerebrovascular/cardiovascular conditions, chronic lung diseases, and diabetes, with the highest risk in those with heart failure. Individuals with diabetes and obesity are at increased risk of ICU admission. Key Points Question What are the risks of severe outcomes from COVID-19 in individuals with comorbidities during the Omicron era? Findings This systematic review and meta-analysis found increased risk of mortality and hospitalization among individuals with a range of comorbidities, including cerebrovascular/cardiovascular conditions, chronic lung diseases, and diabetes, with the highest risk in those with heart failure, versus those without. Risk of ICU admission was higher in individuals with obesity and diabetes. Meaning This study identified comorbid populations most at risk of severe outcomes from COVID-19. Targeting these populations with public health measures, such as vaccination, may be beneficial.
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 | 0,021 | 0,043 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,018 | 0,068 |
| Bibliométrie | 0,006 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,003 |
| 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 ».