Efficacy of the Direct Anterior Chamber Air Replacement Method During Descemet Stripping Automated Endothelial Keratoplasty
Bibliographic record
Abstract
PURPOSE: This study aimed to describe a novel technique of direct anterior chamber (AC) air replacement (DACAR) for the management of Descemet stripping automated endothelial keratoplasty (DSAEK) in postvitrectomized eyes and eyes with previous glaucoma surgery. METHODS: DACAR was performed after a corneal donor graft was transplanted through a wound using the pull-through technique. DACAR involves stabilizing the graft with forceps while introducing air into the AC via an infusion cannula to ensure complete air exchange. The air was maintained in the AC at all times using a vitrectomy machine. The air pressure was maintained at 30 mm Hg for 15 minutes. RESULTS: The DACAR technique was performed in 34 patients, and conventional pull-through technique DSAEK was performed in 32 high-risk patients. The DACAR group had shorter DSAEK surgical procedures ( P = 0.009) and a lower incidence of corneal graft detachment in the early postoperative period ( P < 0.001) than the conventional DSAEK group. CONCLUSIONS: DACAR is performed in patients having previously undergone vitrectomy or glaucoma surgery to prevent corneal graft detachment during the early postoperative period and to reduce the length of surgery.
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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 | 0.001 |
| 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) | 0.001 | 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".