Intraocular pressure control after trans-scleral intraocular lens fixation in glaucoma patients
Bibliographic record
Abstract
BACKGROUND: Intraocular lens fixation surgery is associated with fluctuations in intraocular pressure. This may be significantly relevant in glaucoma patients. OBJECTIVES: To assess short- and medium-term intraocular pressure control after trans-scleral intraocular lens fixation surgery in glaucoma patients. METHODS: The charts of all glaucoma patients who underwent trans-scleral intraocular lens fixation surgery with at least 6 months follow-up by a single surgeon between the years 2004 and 2017 were reviewed. Primary outcomes were intraocular pressure at 1 day and 6 months after surgery. Secondary outcome measures were hypotensive medication use and the need for further intraocular pressure lowering interventions. RESULTS: Eleven eyes of 10 patients were included in the analysis. Mean follow-up post intraocular lens fixation surgery was 54.6 months. Mean intraocular pressure before, 6 months, and last follow-up after intraocular lens fixation surgery was 15.8 ± 5.3 mmHg (range 10.6-25.3), 13.5 ± 3.8 mmHg (range 8-21, p = 0.2), and 11.8 ± 5.6 (range 6-21, p = 0.09) on a mean of 2.3 ± 1.6, 2 ± 1.6 (p = 0.23), and 1.7 ± 1.5 (p = 0.08) hypotensive medications, respectively. A pressure spike was noted in 5 of the 11 eyes on the first post-operative day (mean spike 15.2 mmHg, range 6-23). Four of 11 eyes in the study (36%) needed additional interventions to control intraocular pressure by the 6-month point. One eye required the addition of two classes of topical medications, one eye required laser trabeculoplasty, and two eyes required trabeculectomy. CONCLUSION: Over a third of glaucomatous eyes required a change in the management of their disease in the early post-operative period. Close follow-up of patients undergoing trans-scleral intraocular lens fixation surgery is warranted.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".