Cataract surgical coverage remains lower in women
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: Cataract remains the leading cause of global blindness. Evidence from population-based surveys, carried out up to 2000, and the launch of the VISION 2020 initiative to address avoidable blindness showed that women in low- and middle-income countries had a lower cataract surgical coverage (CSC) than men. METHODS: A systematic review identified population-based surveys reporting CSC in low- and middle-income countries published since 2000. Researchers extracted data on sex-specific CSC rates and estimated the overall CSC differences using meta-analyses. RESULTS: Among the 23 surveys selected for this review, 21 showed higher CSC among men. The Peto odds ratio revealed that men were 1.71 times (95% CI 1.48 to 1.97) more likely to have cataract surgery than women. The risk difference in the rates of surgery varied from -0.025 to 0.276, and the combined average was 0.116 (95% CI 0.082 to 0.149). DISCUSSION: Gender inequity in use of cataract surgical services persists in the low- and middle-income countries. It is estimated in this study that blindness and severe visual impairment from cataract could be reduced by around 11% in the low- and middle-income countries if women were to receive cataract surgery at the same rate as men. Additional effort globally is needed to ensure that women receive the benefits of cataract surgery at the same rate as men.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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