The national and subnational prevalence and burden of age–related macular degeneration in China
Bibliographic record
Abstract
BACKGROUND: Age-related macular degeneration (AMD) is the third most common cause of blindness, and the fourth leading cause of visual impairment worldwide, but little is known about the burden of this disease in the most populous country-China. This study provides the first comprehensive estimates of the prevalence and burden of AMD in China from 1990 to 2015, with projections till 2050. METHODS: In this study, a systematic review and meta-analysis was conducted to estimate the prevalence of AMD in China. China National Knowledge Infrastructure (CNKI), Wanfang, Chinese Biomedicine Literature Database (CBM-SinoMed), PubMed, Embase and Medline were searched before September 2016. Multilevel mixed-effect meta-regression was performed to define the prevalence rates of AMD and its subtypes. UN population data were used to estimate and project the number of people affected from 1990 to 2050. Based on different demographic and geographic features, the national burden of AMD in 2000 and 2010 was distributed to different regions in China. RESULTS: Our search returned 2016 citations, of which 25 met the inclusion criteria. The prevalence of any AMD ranged from 2.44% (95% CI = 1.85-3.22) in people aged 45-49 years to 18.98% (95% CI = 15.05-23.66) in people aged 85-89 years. Prevalence of early AMD ranged from 1.79% (95% CI = 1.05-3.02) to 10.05% (95% CI = 6.17-15.97), and, in the case of late AMD, from 0.38% (95% CI = 0.16-0.97) to 3.88% (95% CI = 1.68-9.13). In late AMD, the prevalence of geographic atrophy (GA) was 0.15% (95% CI = 0.05-0.47) in people aged 45-49 years and 1.09% (95% CI = 0.35-3.36) in those aged 85-89 years, and the prevalence of neovascular AMD (NVAMD) ranged between 0.24% (95% CI = 0.11-0.50) and 2.79% (95% CI = 1.33-5.77). The number of people with any AMD was 12.01 million (95% CI = 9.29-15.46) in 1990 and 26.65 million (95% CI = 20.62-34.27) in 2015. Within the same period, the number of people with early AMD increased from 9.44 million (95% CI = 7.74-11.15) to 20.91 million (95% CI = 17.16-24.68), and those with late AMD rose from 2.58 million (95% CI = 1.56-4.30) to 5.74 million (95% CI = 3.46-9.59). In late AMD, the number of people living with GA ranged from 0.87 million (95% CI = 0.40-1.83) in 1990 to 1.93 million (95% CI = 0.89-4.08) in 2015, and NVAMD from 1.71 million (95% CI = 1.16-2.47) to 3.81 million (95% CI = 2.57-5.51). The projected number of people with any AMD in 2020 is 31.23 million (95% CI = 24.18-40.14), increasing to 55.19 million (95% CI = 43.04-70.30) in 2050. Between different regions, the South Central owed the most AMD cases (5.50 million in 2000 and 7.52 million in 2010), whereas the North-West China the least (0.66 million in 2000 and 0.95 million in 2010). CONCLUSIONS: The estimates in this study suggest a substantial burden of AMD in China, with the ageing process in Chinese society, this burden will be increasing in the foreseen future. Primary and secondary prevention and treatment and effective government response are urgently needed. Improved epidemiological studies are also required to better develop eye-care strategies and health services.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".