Association of Cataract Surgery With Traffic Crashes
Bibliographic record
Abstract
Importance: Cataracts are the most common cause of impaired vision worldwide and may increase a driver's risk of a serious traffic crash. The potential benefits of cataract surgery for reducing a patient's subsequent risk of traffic crash are uncertain. Objective: To conduct a comprehensive longitudinal analysis testing whether cataract surgery is associated with a reduction in serious traffic crashes where the patient was the driver. Design, Setting, and Participants: Population-based individual-patient self-matching exposure-crossover design in Ontario, Canada, between April 1, 2006, and March 31, 2016. Consecutive patients 65 years and older undergoing cataract surgery (n = 559 546). Interventions: First eye cataract extraction surgery (most patients received second eye soon after). Main Outcomes and Measures: Emergency department visit for a traffic crash as a driver. Results: Of the 559 546 patients, mean (SD) age was 76 (6) years, 58% were women (n = 326 065), and 86% lived in a city (n = 481 847). A total of 4680 traffic crashes (2.36 per 1000 patient-years) accrued during the 3.5-year baseline interval and 1200 traffic crashes (2.14 per 1000 patient-years) during the 1-year subsequent interval, representing 0.22 fewer crashes per 1000 patient-years following cataract surgery (odds ratio [OR], 0.91; 95% CI, 0.84-0.97; P = .004). The relative reduction included patients with diverse characteristics. No significant reduction was observed in other outcomes, such as traffic crashes where the patient was a passenger (OR, 1.03; 95% CI, 0.96-1.12) or pedestrian (OR, 1.02; 95% CI, 0.88-1.17), nor in other unrelated serious medical emergencies. Patients with younger age (OR, 1.27; 95% CI, 1.13-1.14), male sex (OR, 1.64; 95% CI, 1.46-1.85), a history of crash (baseline OR, 2.79; 95% CI, 1.94-4.02; induction OR, 4.26; 95% CI, 2.01-9.03), more emergency visits (OR, 1.34; 95% CI, 1.19-1.52), and frequent outpatient physician visits (OR, 1.17; 95% CI, 1.01-1.36) had higher risk of subsequent traffic crashes (multivariable model). Conclusions and Relevance: This study suggests that cataract surgery is associated with a modest decrease in a patient's subsequent risk of a serious traffic crash as a driver, which has potential implications for mortality, morbidity, and costs to society.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".