Blindness and eye disease in a Tibetan region of China: findings from a Rapid Assessment of Avoidable Blindness survey
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
INTRODUCTION: The only population-based survey of blindness and visual impairment of a Tibetan population was conducted in the Tibet Autonomous Region in 1999. METHODS AND ANALYSIS: The Rapid Assessment of Avoidable Blindness methodology was used to conduct a survey of Kandze Tibetan Autonomous Prefecture, Sichuan Province of China in the Fall 2017. Using the 2010 census, 100 clusters of 50 participants aged 50 years or older were randomly sampled using probability proportionate to size. RESULTS: Among the 5000 people enumerated, 4763 were examined (95.3% response). The age-adjusted and sex-adjusted prevalence of blindness, severe visual impairment, moderate visual impairment and early visual impairment (EVI) were 1.6% (95% CI: 1.08 to 2.38)), 0.9% (95% CI:0.7 to 1.5), 5.1% (95% CI:4.4 to 5.7), and 7.45% (95% CI:6.67 to 8.2), respectively. The prevalence of blindness among Tibetans was significantly higher than that among Han Chinese (2.2% (95% CI:1.8 to 2.6) and 0.6 (95% CI:0.2 to 1.7), respectively, p<0.05). Women bore a significant excess burden of EVI compared with men (8.5% (95% CI:7.5 to 9.6) and 6.1% (95% CI:5.1 to 7.2), respectively, p<0.05). Cataract was the primary cause of blindness (39.4%) followed by macular degeneration (10.6%) and corneal opacity (5.3%). CONCLUSION: Blindness and visual impairment in Kandze Tibetan Autonomous Prefecture is substantially less than an earlier study of a Tibetan region and now resembles other regions of China. About 58% of blindness and 67% of SVIwere avoidable, primarily by providing cataract services. Eighty-three percent of EVI was avoidable by providing refractice services throughout the region.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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