Notice bibliographique
Résumé
The epidemiology of glaucoma in East Asia has been poorly understood until recently. Studies of Inuit populations in the arctic regions of Greenland, Canada and Alaska suggested that primary angle-closure glaucoma (PACG) was more prevalent than in European people, and was a leading cause of visual morbidity. Primary open-angle glaucoma (POAG) was reported to be scarce. A population- based study of glaucoma prevalence carried out in 1989 in Shun-yi County, Beijing, in the People's Republic of China gave similar findings. Ninety-eight percent of cases of primary glaucoma in adults were caused by angle-closure. Remarkably, there was only one case of POAG in subjects aged 40 years and older. In contrast, a nation-wide study of glaucoma prevalence in Japan found a high prevalence of open-angle glaucoma- 2.6% in men and 2.5% among women aged 40 years and older. The majority of cases were diagnosed as "normal tension glaucoma", with a screening intraocular pressure of < 22 mm Hg. The contradictory data from these two studies suggested that the clinical characteristics of glaucoma, and its importance as a cause of blindness in East Asian people, needed closer study. During 1991-92 Prof. Baasanhu carried out a population-based study of blindness in her native Mongolia. Her work suggested that rates of blindness from glaucoma and cataract were almost equal in adults (35% and 36% respectively)- a unique finding in a country with poorly developed cataract surgical services. Consequently, a population glaucoma survey in Mongolia was carried out in 1995 to ascertain the prevalence, clinical characteristics and visual morbidity of glaucoma in a Mongolian population. In 1996, I began working at the National Eye Centre in Singapore, and subsequently carried out a survey with similar objectives in a Chinese Singaporean population. The prevalence of glaucoma among people aged 40 years and older (when adjusted for age and sex differences between the populations) was 1.7% (95% Cl: 1.0 to 2.7) in Mongolia. In Singapore, the observed prevalence of glaucoma was calculated as 2.2% (95% Cl:1.4 to 2.9). Adjusting for those in Singapore who did not complete field testing gave a prevalence of 3.2% (95% Cl; 2.3 to 4.1). The prevalence of glaucoma increased with age in Mongolia and Singapore. Glaucoma was the leading cause of blindness in both populations. An island-wide, prospective study of the incidence of symptomatic primary angle-closure (PAC) in Singaporeans identified increasing age, female sex and Chinese ethnicity as factors that increased the risk of PAC. The annual incidence of 15.5/100,000/year in the population aged 30 years and older is the highest recorded rate of disease. The ratio of prevalent cases of POAG:PACG was 4:8 in Mongolia and 22:14 in Singapore. Narrow drainage angles were found in people with shallow anterior chambers, thicker, more anteriorly positioned lenses, shorter axial lengths, and higher degrees of lens opacity. Narrow drainage angles were more likely to be found in older people and women. Mean anterior chamber depth (ACD) was greater at all ages among Chinese Singaporeans than among Mongolians. The ACD in Mongolian men and women aged 40 to 49 years was 2.69 and 2.59 mm. In Singaporean men and women of the same age, the ACD was 2.87 and 2.71 mm respectively. Estimates of intraocular pressure (IOP) showed a significant positive association with central corneal thickness and systolic blood pressure. Estimated IOP increased with age in Singaporeans, and decreased with age in Mongolians. Among Chinese Singaporeans, there was a non-linear relationship between screening IOP and the risk of glaucomatous optic neuropathy, the risk being higher in people with higher IOP. Manometric validation of IOP measurements made using applanation tonometry and Tonopen suggested that there were large errors in the clinical estimates of IOP. Cautious extrapolation of these data to China suggests that around 1.7 million people are blind in both eyes from glaucoma, 91% of all cases being caused by PACG. This disease should become the subject of detailed clinical trials of screening and prophylaxis
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 | 0,001 |
| 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 | 0,001 |
| 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 ».