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Record W2772439167 · doi:10.7189/jogh.07.020703

The national and subnational prevalence and burden of age–related macular degeneration in China

2017· review· en· W2772439167 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Global Health · 2017
Typereview
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsCentre for Global Health Research
FundersChina Scholarship Council
KeywordsMedicineChinaMacular degenerationMeta-analysisBlindnessDemographyMEDLINEPopulationEpidemiologyDisease burdenConfidence intervalEnvironmental healthOptometryGeographyInternal medicineOphthalmology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score0.289

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.054
GPT teacher head0.450
Teacher spread0.395 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it