Immediately sequential bilateral cataract surgery (ISBCS) adapted protocol during COVID-19
Bibliographic record
Abstract
OBJECTIVE: To describe the steps, hurdles, and recommendations for implementation of the immediately sequential bilateral cataract surgery (ISBCS) evidence-based protocol at a high-volume Canadian tertiary care centre. DESIGN: Quality-improvement study. PARTICIPANTS: A total of 406 patients who underwent ISBCS from July 2020 to December 2020. Patients were selected based on specific inclusion and exclusion criteria including psychosocial factors, refractive error and consent. This initiative impacted staff at all levels involved with cataract surgery. METHODS: The Model of Improvement framework was used and involved numerous discussions with multidisciplinary teams of ophthalmologists, nursing and support staff, management, pharmacists, and medical device reprocessing teams. This initiative was created and refined via a thorough review of the literature and current best practices. It was implemented in July 2020 after a nursing "huddle." Any adverse outcomes and overall impact were collected from various levels of staff involved. RESULTS: Each eye was treated as a separate surgery with a double time-out per bilateral case. Additional measures were taken to ensure different lot numbers for medications, equipment, and materials. This practice increased surgical volume by approximately 25% and reduced the number of patient visits by 50%, reducing potential COVID-19 exposure. CONCLUSIONS: The resulting protocol from our study may be useful to other centres wishing to integrate ISBCS as one example of successful implementation. Of the 406 cases of ISBCS performed, we report zero cases of toxic anterior segment syndrome or endophthalmitis. In times of decreased elective surgeries, ISBCS is a safe and effective option to supplement surgical volume and provide significant patient benefits.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.005 | 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".