Development and internal validation of a prediction model for new-onset macular oedema following vitrectomy for diabetic retinopathy: a single-centre retrospective analysis

Objective To develop and internally validate a compact model for estimating the 1-year risk of new-onset postoperative macular oedema in patients with diabetic retinopathy undergoing vitrectomy. Methods This single-centre retrospective cohort included 650 recorded patients treated from January 2023 to April 2025. The primary analysis comprised 607 patients with ascertainable 1-year outcomes, with one study eye per patient; 43 patients lost to follow-up were assessed separately. New-onset macular oedema required new intraretinal cystoid spaces and/or subretinal fluid on optical coherence tomography during postoperative days 30–365, together with central macular thickness ≥300 μm or an increase ≥30 μm from baseline. The five-predictor logistic model used pre-incision measurements and was fitted in all 607 patients. Internal validation used 1, 000 bootstrap resamples; a 32-candidate, 10-fold cross-validated least absolute shrinkage and selection operator (LASSO) analysis with selection-inclusive bootstrap validation assessed the stability of the separate LASSO procedure. Results New-onset postoperative macular oedema occurred in 207 of 607 patients (34.1%). The apparent area under the receiver operating characteristic curve (AUC) was 0.823 and the optimism-corrected AUC was 0.818. The corresponding Brier scores were 0.159 and 0.163; the corrected calibration intercept and slope were −0.011 and 0.969. At an illustrative probability threshold of 0.30, 40 of 323 patients (12.4%) in the lower-risk group and 167 of 284 (58.8%) in the higher-risk group developed the outcome. Selection-inclusive validation of the LASSO sensitivity model yielded a corrected AUC of 0.805. Systolic pressure was not statistically significant in the five-predictor model (P = 0.329). Conclusion The five-variable model showed useful discrimination and acceptable bootstrap-corrected calibration in this single-centre cohort. It should be regarded as an internally validated risk-stratification model that requires external and prospective validation before clinical implementation.