The Effect of Successful Rebubbling After Descemet Stripping Automated Endothelial Keratoplasty on Endothelial Cell Counts
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Bibliographic record
Abstract
PURPOSE: To examine the effect of successful repositioning/rebubbling of the graft on endothelial cell counts (ECCs) in eyes after Descemet stripping automated endothelial keratoplasty. METHODS: This retrospective study reviewed the outcomes of 58 eyes that underwent Descemet stripping automated endothelial keratoplasty. Fifty-one eyes were attached after surgery. Seven were detached and underwent rebubbling with minimal manipulation in 5 and significant manipulation in 2, after which the graft was attached and clear. Visual outcomes and endothelial cell loss at 6 months were compared between eyes that underwent repositioning/rebubbling and those that did not. The following were excluded: 2 eyes that had primary failure, 2 eyes that had rejection, 1 eye that failed to attach after rebubbling, 2 eyes that failed to clear after rebubbling, and 24 eyes that did not have ECC at 6 months. RESULTS: The 2 groups were comparable considering age, preoperative best-corrected visual acuity, surgical variables, combined procedures, donor cell count, and graft size. The mean postoperative spherical equivalent, manifest and topographic astigmatism, uncorrected visual acuity, and best-corrected visual acuity did not differ significantly between the 2 groups at 6 months. Mean pre- and postoperative ECC did not differ significantly between the group that underwent repositioning/rebubbling and the group that did not (preoperative counts 2742 +/- 268 vs. 2747 +/- 353 and postoperative counts 1590 +/- 367 vs. 1746 +/- 491, respectively). Endothelial cell loss also did not differ significantly between the 2 groups, although there was a trend to greater cell loss in the reattachment group (-39.4% +/- 11.1% vs. -38.3% +/- 16.2%, respectively; P = 0.6). CONCLUSION: Successful reattachment procedure does not seem to cause significant endothelial cell loss.
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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) | 0.000 | 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 it