Equity of continuous glucose monitoring in young people with type 1 diabetes: a systematic review
Notice bibliographique
Résumé
Background: Socioeconomic (SES) and ethnic inequalities in type 1 diabetes (T1D) outcomes are widespread. There is concern that unequal access to technologies, such as continuous glucose monitoring (CGM), may increase disparities. This systematic review summarises the evidence for inequalities in access to CGM for children and young people (CYP) and outcomes for CGM users. Methods: MEDLINE, Embase, and Web of Science were searched for observational studies published between January 2020 and July 2023 which report CGM use stratified by any PROGRESS-plus criteria for T1D patients under 26. Reports based in low- or middle-income countries or ≤ 500 participants were excluded. Primary outcomes were the proportion of patients using CGM and HbA1c of CGM users. Quality assessment was performed using the Newcastle-Ottawa Scale. Unadjusted odds ratios were calculated from extracted data, though heterogeneity precluded meta-analysis. The protocol was pre-registered with PROSPERO (CRD42023438139). Results: Of the 3,369 unique studies identified, 27 met inclusion criteria. We found decreased CGM use and higher discontinuation for low SES, low education, publicly insured, and minority ethnic, especially black, CYP. These associations were generally robust to adjustment for other sociodemographic variables, suggesting an independent effect. Lower SES inequalities were seen in countries where CGM is reimbursed. Although low SES and minority ethnicity were generally associated with poorer outcomes, there was no significant association between domains of disadvantage and higher HbA1c for CGM users, excepting parental education. Conclusions: There are significant SES, ethnic, and education inequalities in CGM use for CYP with T1D, particularly when reimbursement is limited. This is contributing to outcome inequalities. However, evidence suggests CYP benefit equally from CGM use, irrespective of ethnicity and SES. Increasing CGM funding and use is likely to reduce outcome inequalities. Key messages: • There are significant SES, ethnic, and education inequalities in continuous glucose monitoring use for young people with T1D. Inequalities are more marked when technology is not reimbursed. • Increasing access to CGM may reduce outcome inequalities, as evidence suggests that young people benefit equally from CGM use, regardless of ethnicity or SES.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 ».