Cataract prevalence following a nationwide policy to shorten wait time for cataract surgery
Bibliographic record
Abstract
Background: Cataract is an age-related eye disease. Visual impairment from cataract can be restored by cataract surgery. In 2004 the Canadian federal government invested in a multibillion dollar wait time strategy to shorten the wait time for cataract surgery, a government-insured health service in all Canadian jurisdictions. We assessed if this nationwide policy reduced the number of Canadians waiting for cataract surgery as more individuals with cataract were free of cataract following the rapidly conducted surgery. Methods: In this cross-sectional study we analyzed data from randomly selected individuals aged greater than or equal to 45 years responding to the Canadian Community Health Survey (CCHS) in 2000/2001, 2003, 2005, and the CCHS Healthy Aging in 2008/2009. Information on cataract was obtained from self-reported questionnaire. The age- and sex-standardized prevalence of cataract was calculated for comparisons. Results: Cataract was reported by 0.93 million Canadians in 2000/2001, 0.99 million in 2003, 1.10 million in 2005, and 1.34 million in 2008/2009. This corresponds to an age- and sex-standardized prevalence of 8.9% in 2000/2001, 9.0% in 2003, 9.5% in 2005, and 10.2% (P <0.05) in 2008/2009. The increase in age- and sex-standardized prevalence was greater in individuals without secondary school graduation than those with secondary school graduation or higher (4.3% versus 1.3%, P < 0.05) and was seen in all Canadian provinces. The largest increase was documented in a province (Saskatchewan, from 9.8% in 2000/2001 to 12.6% in 2008/2009, P < 0.05) with the longest median wait times for cataract surgery (118 days in 2008) and the lowest number of ophthalmologists per 100,000 population (1.96 versus 3.35 national average). Conclusions: The age- and sex-standardized prevalence of cataract increased 4-5 years after the multibillion-dollar wait time strategy was launched in 2004. A lower threshold to diagnose cataract may be one potential reason for this finding. Further research is needed to understand the true reasons for the increase. How to cite this article: Yang G, El-Defrawy S, Trope GE, Buys YM, Liu SY, Jin YP. Cataract prevalence following a nationwide policy to shorten wait time for cataract surgery. Med Hypothesis Discov Innov Ophthalmol. 2021 Summer; 10(2): 86-94. https://doi.org/10.51329/mehdiophthal1426
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".