Association Between Indication for Descemet Stripping Automated Endothelial Keratoplasty and Rural Residency
Bibliographic record
Abstract
PURPOSE: Residing in rural locations can be a barrier to health care access. This study investigated the impact of residing in rural and small town (RST) areas on Descemet stripping automated endothelial keratoplasty (DSAEK) indications and outcomes in Atlantic Canada. METHODS: A retrospective cohort analysis examined consecutive DSAEKs performed in Nova Scotia between 2017 and 2020. Patient rurality was determined by the Statistical Area Classification system developed by Statistics Canada. Univariate and multivariate logistic regression models were used to assess for factors associated with DSAEK indication, including repeat keratoplasty, RST residence status, and travel time. RESULTS: Of 271 DSAEKs during the study period, 87 (32.1%) were performed on the eyes of RST residents. The median postoperative follow-up time was 1.6 years. Undergoing DSAEK for a previous failed keratoplasty was not associated with a higher odds of RST residency (odds ratio [OR], 0.50; 95% confidence interval [CI], 0.19-1.16; P = 0.13) but was associated with travel time (OR, 0.78 for each increasing hour of travel; 95% CI, 0.61-0.99; P = 0.044). RST residency was not associated with the occurrence of graft failure (OR, 0.48; 95% CI, 0.17-1.17; P = 0.13). CONCLUSIONS: Residing in a rural area in Atlantic Canada was not associated with DSAEK graft failure. Repeat endothelial keratoplasty was associated with shorter travel time for corneal surgery but not rural residency status. Further research in this field could inform regional health strategies aimed at improving equity and accessibility to ophthalmology subspecialist care.
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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) | 0.000 | 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) | 0.000 | 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".