Redefining risk categories for pneumococcal disease in adults: critical analysis of the evidence
Notice bibliographique
Résumé
OBJECTIVE: To analyze the available published data (2005-2014) describing the prevalence of multimorbidity in adult patients with pneumococcal disease, with a focus on the comorbidities considered by the Advisory Committee on Immunization Practices (ACIP) of the US Centers for Disease Control and Prevention to increase the risk of pneumococcal disease in adults (immunocompetent persons with chronic medical conditions (at risk) and immunocompromised or immunosuppressed persons (high risk)). An analysis of case-control and population-based surveillance studies that have evaluated risk factors for community-acquired pneumonia (CAP) and invasive pneumococcal disease (IPD) was also performed in order to estimate the importance of risk stacking. METHODS: Studies that established the enrolment procedure for patients and reported the incidence of multimorbidity and risk factors for CAP and/or IPD were included. In order to obtain a risk stacking value based on the at-risk comorbidity odds ratios (OR), the multiplicative method described by Campbell was used. RESULTS: Thirty-eight articles were selected, 19 for multimorbidity and 19 for risk factors for CAP/IPD. With regard to multimorbidity, the prevalence among adults aged ≥65 years ranged from 23% to 98.7% for two or more comorbidities and from 18% to 89.7% for three or more comorbidities. Diabetes (DBT), chronic heart disease (CHD), and chronic obstructive pulmonary disease (COPD) were the three most frequent comorbidities described (7.6-28.5%, 6.9-25.8%, and 3.8-15.4%, respectively). With regard to risk factors, based on the multiplicative method, the hypothetical scenario of concurrence of the three most frequent at-risk conditions (DBT+CHD+COPD) showed an OR of ≥7.5. In this group of patients, the addition of smoking, another common at-risk factor for CAP (stacking four concurrent conditions) increased the OR from 8.5 to >40. These ORs were generally similar to rates described by other authors in persons with a high risk. CONCLUSIONS: The ORs for CAP and IPD of patients with two or more comorbidities, with or without smoking, were found to be similar to the ORs for CAP and IPD described in the literature for patients currently classified as high risk. The potential impact of multiple, stacking comorbidities is underestimated and there is a need for the risk categories for pneumococcal disease to be redefined.
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 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 | 0,000 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,000 |
| 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 ».