Prevalence, risk factors and burden of diabetic retinopathy in China: a systematic review and meta-analysis
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Notice bibliographique
Résumé
BACKGROUND: Diabetic retinopathy (DR), the primary retinal vascular complication of diabetes mellitus (DM), is a leading cause of vision impairment and blindness in working-age population globally. Despite mounting concerns about the emergence of DM as a major public health problem in the largest developing country, China, much remains to be understood about the epidemiology of DR. We aimed to investigate the prevalence of and risk factors for DR, and estimate the burden of DR in China in 2010. METHODS: China National Knowledge Infrastructure (CNKI), Wanfang, Chinese Biomedicine Literature Database (CBM-SinoMed), PubMed, Embase and Medline were searched for studies that reported the prevalence of and risk factors for DR in Chinese population between 1990 and 2017. A random-effects meta-analysis model was adopted to pool the overall prevalence of DR. Variations in the prevalence of DR in different age groups, DM duration groups and settings were assessed by subgroup meta-analysis and meta-regression. Odds ratios (ORs) of major risk factors were pooled using random-effects meta-analysis. The number of people with DR in 2010 was estimated by multiplying the age-specific prevalence of DR in people with DM with the corresponding number of people with DM in China. Finally, the national number of people with DR was distributed into six geographic regions using a risk factor-based model. RESULTS: A total of 31 studies provided information on the prevalence of DR and 21 explored potential risk factors for DR. The pooled prevalence of any DR, nonproliferative DR (NPDR) and proliferative DR (PDR) was 1.14% (95% CI = 0.80-1.52), 0.90% (95% CI = 0.56-1.31) and 0.07% (95% CI = 0.02-0.14) in general population; In people with DM, the pooled prevalence rates were 18.45% (95% CI = 14.77-22.43), 15.06% (95% CI = 11.59-18.88) and 0.99% (95% CI = 0.40-1.80) for any DR, NPDR and PDR, respectively. The prevalence of any DR in DM patients peaked between 60 and 69 years of age, and increased steeply with the duration of DM. DM patients residing in rural China were at a higher risk to have DR than those in urban areas. In addition, insulin treatment, elevated FBG level and higher HbA1c concentration were confirmed to be associated with a higher prevalence of DR in people with DM, with meta-ORs of 1.99 (95% CI = 1.34-2.95), 1.33 (95% CI = 1.12-1.59) and 1.15 (95% CI = 1.09-1.20) respectively. In 2010, a total of 13.16 million (95% CI = 8.95-18.00) Chinese aged 45 years and above were living with DR, among whom the most were in South Central China and the least were in Northwest China. CONCLUSIONS: DR has become a serious public health problem in China. Optimal screening of and interventions on DR should be implemented. Improved epidemiological studies on DR are still required.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,012 | 0,002 |
| Bibliométrie | 0,000 | 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 découle