Visual functional outcomes of cataract surgery in the United States, Canada, Denmark, and Spain
Bibliographic record
Abstract
PURPOSE: To compare functional outcomes after cataract surgery performed at 4 sites in 4 countries that have been described as having significant differences in the organization of care and patterns of clinical practice. SETTING: Multicenter cohort study from the United States, Canada, Denmark, and Spain. METHODS: Clinical data and patient interview data were collected preoperatively and 4 months postoperatively. Functional outcomes were assessed by the Visual Function Index (VF-14), a self-reported measure of visual function. Scores on the VF-14 range from 0 (maximum impairment) to 100 (no impairment). RESULTS: Unilateral surgery was performed in 1073 patients. In this subgroup, the odds of achieving an optimal functional outcome (VF-14 score > or =95) were similar among sites after controlling for differences in case mix. Bilateral surgery was performed in 211 patients. A postoperative visual acuity of 0.50 or better in both eyes was reported in 155 patients. However, 37% of these patients reported visual function impairment (VF-14 score <95). CONCLUSIONS: A previously identified variation in treatment modalities among the 4 sites did not have a significant effect on the odds of achieving an optimal functional outcome. In addition to visual acuity measurements, the VF-14 index provides information on functional outcomes that is useful, especially in studies assessing the benefits of cataract surgery in a public health care setting.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| 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".