Reporting of absolute and relative risk measures in oral health and cardiovascular events studies: A systematic review
Notice bibliographique
Résumé
OBJECTIVES: To understand the magnitude of risk of health events, such as cardiovascular diseases (CVD), related to poor oral health, both relative and absolute risk measures should be reported. Our aim was to investigate the extent to which absolute and relative measures of risk are reported in longitudinal studies that assess the association between oral health indicators (OHIs) and CVD. METHODS: A systematic search of longitudinal studies investigating the association of any OHI with CVD was carried out using the Embase, Medline and Cochrane library databases. The search covered each database from its inception date to August 2021. Data about reporting relative and absolute risks of the relationship between CVD and OHI from the abstract were extracted. If the relative risk for OHIs and CVD was reported in the abstract, then the underlying absolute risks were searched from the full text, and it was assessed whether it was similarly adjusted for confounding than was the relative risk in the abstract. RESULTS: One hundred-six articles were included. From these, 85 (80%) studies reported the association of OHIs and CVD with one or more relative risks in the abstract. Of those 85 studies, the underlying absolute risks were accessible or calculable from the abstract or full text of 60 studies. However, of these 60 studies, in only 10 (12%), the underlying absolute risks were similarly adjusted, as were the relative risks in the abstract. The absolute risks of CVD by OHIs were rarely reported without corresponding relative risks in the abstract (n = 2, 2%). Median absolute risk difference in the CVD risk between exposure levels to which the first relative risk in the abstract referred was 1.8% (interquartile range 0.6-4.6, n = 63). CONCLUSIONS: Focusing on relative risks over absolute risks was a common practice in literature. Reporting similarly adjusted underlying absolute risks of relative risks was rare in most studies, despite those being helpful for comprehending the magnitude of CVD-risk increase related to poor oral health. Current reporting practices could lead to an overinterpretation of risk increase of CVD related to poor oral health.
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 | 0,048 | 0,064 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,011 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,004 |
| 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».