Factors predictive of cystoid macular oedema following endothelial keratoplasty: a single-centre review of 2233 cases
Bibliographic record
Abstract
AIMS: To describe the incidence of postoperative cystoid macular oedema (CMO) after endothelial keratoplasty (EK) and to identify its contributory risk factors. METHODS: 2233 patients undergoing EK at Ospedali Privati Forlì 'Villa Igea', between January 2005 to October 2018 for Descemet stripping automated endothelial keratoplasty (DSAEK) and June 2014 to August 2018 for Descemet membrane endothelial keratoplasty (DMEK) with a minimum follow-up of 18 months were evaluated. Univariate and multivariate analyses were conducted to identify and quantify contributory risk factors. Receiver operating characteristic (ROC) curve analysis were performed to determine ideal cut-off points of continuous variables. RESULTS: CMO was identified in 2.82% (n=63) of the cases. CMO occurred in 2.36% of DSAEK eyes and in 5.56% of DMEK eyes (p=0.001). Average onset of CMO was 4.27±6.63 months (range: 1-34 months) postoperatively. Compared with those who did not develop CMO, a higher proportion of patients in the CMO group had diabetes (24.2% vs 9.8%, p<0.001) (OR=3.16, 95% CI: 1.72 to 5.81, p<0.001), a higher proportion of patients who underwent DMEK rather than DSAEK (28.6% vs 14.1%, p=0.001) (OR=2.42, 95% CI: 1.35 to 4.33, p=0.003) and were older (70.5±10.0 vs 67.1±14.3 years, p=0.01). Using the cut-off of 67 years as identified by ROC curve analysis, subjects aged >67 years (OR=2.35, 95% CI: 1.30 to 4.26, p=0.005) were more likely to develop CMO. There were no other significant differences between the groups. CONCLUSIONS: Older age (>67 years), diabetes mellitus and DMEK have been identified as independent risk factors for postoperative CMO following EK. Close observation is necessary during the first postoperative year after EK, particularly in patients with risk factors.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 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".