Variations of dry eye disease prevalence by age, sex and geographic characteristics in China: a systematic review and meta-analysis
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.
Bibliographic record
Abstract
BACKGROUND: Dry eye disease (DED) is one of the most prevalent ocular diseases in the world. In China, new lifestyles driven by information technology and the rapid ageing process have brought DED a severe public health concern. The aim of our study was to obtain the pooled prevalence of DED in China and explore its potential correlates. METHODS: A comprehensive systematic review was conducted to identify all relevant literature published since 1990. Meta-analysis and meta-regression approaches were adopted to estimate the prevalence of DED. The number of people with DED was obtained by multiplying the corresponding demographic data in 2010. RESULTS: Advanced age, female sex and larger latitude were significant risk factors for DED by symptoms and signs, whereas only advanced age was positively associated with an increased prevalence of DED by symptoms. In 2010, the prevalence of DED by symptoms and signs were 13.55% (95% CI = 10.00-18.05) and that of DED by symptoms was 31.40% (95% CI = 23.02-41.13) in Chinese people aged 5-89 years, corresponding to a total of 170.09 million (95% CI = 125.52-226.63) and 394.13 million (95% CI = 288.99-516.30) affected individuals respectively. CONCLUSIONS: The huge burden of DED in China calls for more public health attention and actions. Improved epidemiological studies on DED prevalence are still urgently needed.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it